EP2237573B1 - Procédé de suppression adaptative de couplage acoustique et dispositif correspondant - Google Patents

Procédé de suppression adaptative de couplage acoustique et dispositif correspondant Download PDF

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Publication number
EP2237573B1
EP2237573B1 EP10157933.2A EP10157933A EP2237573B1 EP 2237573 B1 EP2237573 B1 EP 2237573B1 EP 10157933 A EP10157933 A EP 10157933A EP 2237573 B1 EP2237573 B1 EP 2237573B1
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signal
noise
unit
output
filter
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EP2237573A1 (fr
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Jesper Jensen
Thomas Bo Elmedyb
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Oticon AS
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Oticon AS
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Priority to EP13164634.1A priority patent/EP2621198A3/fr
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R3/00—Circuits for transducers, loudspeakers or microphones
    • H04R3/02—Circuits for transducers, loudspeakers or microphones for preventing acoustic reaction, i.e. acoustic oscillatory feedback
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
    • G10K11/17813—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms
    • G10K11/17819—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms between the output signals and the reference signals, e.g. to prevent howling
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1785—Methods, e.g. algorithms; Devices
    • G10K11/17853—Methods, e.g. algorithms; Devices of the filter
    • G10K11/17854—Methods, e.g. algorithms; Devices of the filter the filter being an adaptive filter
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1785—Methods, e.g. algorithms; Devices
    • G10K11/17855—Methods, e.g. algorithms; Devices for improving speed or power requirements
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1787—General system configurations
    • G10K11/17879—General system configurations using both a reference signal and an error signal
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1787—General system configurations
    • G10K11/17879—General system configurations using both a reference signal and an error signal
    • G10K11/17881—General system configurations using both a reference signal and an error signal the reference signal being an acoustic signal, e.g. recorded with a microphone
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1787—General system configurations
    • G10K11/17885—General system configurations additionally using a desired external signal, e.g. pass-through audio such as music or speech
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/45—Prevention of acoustic reaction, i.e. acoustic oscillatory feedback
    • H04R25/453—Prevention of acoustic reaction, i.e. acoustic oscillatory feedback electronically
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/10—Applications
    • G10K2210/108—Communication systems, e.g. where useful sound is kept and noise is cancelled
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/10—Applications
    • G10K2210/108—Communication systems, e.g. where useful sound is kept and noise is cancelled
    • G10K2210/1081—Earphones, e.g. for telephones, ear protectors or headsets
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3055—Transfer function of the acoustic system
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2460/00—Details of hearing devices, i.e. of ear- or headphones covered by H04R1/10 or H04R5/033 but not provided for in any of their subgroups, or of hearing aids covered by H04R25/00 but not provided for in any of its subgroups
    • H04R2460/01—Hearing devices using active noise cancellation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/55—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception using an external connection, either wireless or wired
    • H04R25/552—Binaural
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/55—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception using an external connection, either wireless or wired
    • H04R25/554—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception using an external connection, either wireless or wired using a wireless connection, e.g. between microphone and amplifier or using Tcoils

Definitions

  • the present invention relates to methods of feedback cancellation in audio systems, e.g. listening devices, e.g. hearing aids.
  • the invention relates specifically to an audio processing system, e.g. a listening device or a communication device, for processing an input sound to an output sound.
  • the invention furthermore relates to a method of estimating a feedback transfer function in an audio processing system, e.g. a listening device.
  • the invention further relates to a data processing system and to a computer readable medium.
  • the invention may e.g. be useful in applications such as public address systems, entertainment systems, hearing aids, head sets, mobile phones, wearable/portable communication devices, etc.
  • probe noise Another way to deal with the AC problem is to introduce so-called probe noise, where an, ideally inaudible, noise sequence is combined with the receiver signal before play back (being presented to a user).
  • this well-known class of methods see e.g. EP 0 415 677 A2 (GN Danavox), completely eliminates the AC problem.
  • the probe noise variance must be very small for the noise to be inaudible, the resulting adaptive system becomes very slow.
  • An improvement can be obtained by using masked noise as e.g. described in US 2007/172080 A1 (Philips).
  • WO 2007/125132 A2 (Phonak) describes a method for cancelling or preventing feedback.
  • the method comprises the steps of estimating an external transfer function of an external feedback path defined by sound travelling from the receiver to the microphone, estimating the input signal having no feedback components of the external feedback path using an auxiliary signal, which does not comprise feedback components of the external feedback path, and using the estimated input signal for estimating the external transfer function of the external feedback path.
  • EP 0 579 152 A1 deals with a noise and feedback suppression system comprising an adaptive filter.
  • the reference and error signals of the system are pre-filtered to focus the noise or feedback suppression to a particular selected frequency range, e.g. to a frequency range below 1 kHz for noise suppression and e.g. to a frequency range from 3 kHz to 5 kHz for feedback.
  • FIG. 1a shows an example of an audio processing system, e.g. a listening device, comprising a traditional adaptive system based on probe noise, where the goal is to approximate the unknown, time-varying transfer function F(z,n) (representing leakage feedback from receiver to microphone) by an estimate Fh(z,n), which here is assumed to be an FIR system.
  • F(z,n) representing leakage feedback from receiver to microphone
  • Fh(z,n) which here is assumed to be an FIR system.
  • a forward path is defined between the microphone and the receiver.
  • the estimate Fh(z,n) may be updated using any of the standard adaptive filtering algorithms such as NLMS, RLS, etc. (cf.
  • the probe noise (generated by Probe signal unit in FIG. 1a ) is denoted as us(n) and can be generated in a variety of ways (cf. e.g. methods A and B discussed below or any other appropriate method, e.g. by filtering a white noise sequence through an analysis-modification-synthesis filter bank, or through an IIR filter).
  • the probe signal us(n) is connected to the Algorithm part of the adaptive FBC-filter as well as being added to output signal y(n) from the forward gain unit G(z,n) in output SUM unit '+', whose output u(n) is connected to the receiver and to the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • the Algorithm part additionally bases the estimate of filter coefficients of the variable filter part Fh(z,n) of the FBC-filter on the feedback corrected input signal e(n) generated by a subtraction in input SUM unit '+' of the feedback estimate vh(n) of the variable filter part Fh(z,n) of the FBC-filter from the input signal comprising feedback signal v(n) and target signal x(n) as picked up by the microphone. Due to the preferably inaudible nature of the probe noise, such prior art solutions lead to relatively slow adaption rates of the adaptive system.
  • the present invention is defined in the appended independent claims and relates in general to methods for feedback cancellation in audio processing systems, e.g. listening devices, e.g. hearing aids.
  • the methods can in principle be used with any Dynamic Feedback Cancellation (DFC) system based on the traditional setup where a model (e.g. a FIR or IIR model) of the feedback channel transfer function is updated using any adaptive filter algorithm, e.g. normalized least mean square (NLMS), recursive least squares (RLS), affine projection type of algorithms, etc., see e.g. [Haykin, 1996] or [Sayed, 2003].
  • DFC Dynamic Feedback Cancellation
  • NLMS normalized least mean square
  • RLS recursive least squares
  • affine projection type of algorithms etc.
  • warping e.g. in the form of warped filters, cf. e.g. [Härffle et al., 2000]
  • other functional elements e.g. linear filters, such as FIR or IIR filters
  • Preferred embodiments of the invention are defined in the appended dependent claims.
  • some of, such as a majority of, the features of the present invention are implemented as software algorithms adapted for running on a processor of an audio processing system, e.g. a public address system, e.g.
  • the applications may comprise a single or a multitude of microphones and a single or a multitude of loudspeakers.
  • the present inventive concept can be used in a configuration comprising a forward path comprising a microphone, an amplifier for amplifying the microphone signal and a loudspeaker for outputting the amplified microphone signal, wherein the distance between a microphone and a speaker of the system is such that acoustic feedback from the receiver to the microphone (at least at some time instances) is enabled.
  • the microphone(s) and speaker(s) in question may be located in the same or separate physical units.
  • the invention relates to the introduction and identification of specific characteristic properties in an output signal of the forward path of an audio processing system, e.g. a listening device.
  • a signal comprising the identified or introduced properties is propagated through the feedback path from output to input transducer and extracted or enhanced on the input side in an Enhancement unit matching (in agreement between the involved units) the introduced and/or identified specific characteristic properties.
  • the signals comprising the specific characteristic properties on the input and output sides, respectively, are used to estimate the feedback path transfer function in a feedback estimation unit.
  • the invention relates in particular to the retrieval or enhancement of characteristics (e.g. modulation index, periodicity, correlation time, noise or noise-like parts) of a signal in the forward path of an audio processing system, e.g. a listening device, and to the use of the retrieved or enhanced characteristics in the estimation of acoustic feedback.
  • FIG. 1b illustrates the general concept of and the basic functional elements of a method and system using retrieval or enhancement of characteristics of a signal in the forward path, e.g. intrinsic noise-like signals, in the estimation of the feedback path as suggested by the present invention.
  • the embodiment in FIG. 1b comprises the same elements as the listening device of FIG. 1a , except that the Probe signal generator (in the most general embodiment) is omitted.
  • An Enhancement unit e.g. a noise retrieval unit for extracting characteristics (e.g. noise-like parts) of the output signal u(n) is inserted in a first input path to the algorithm part of the adaptive FBC filter. It takes the output signal u(n) as an input and provides as an output an estimate us(n) consisting of components having certain specified characteristics (e.g. components with a certain modulation index, components with a certain correlation time, e.g. noise-like parts, etc.) of the output signal u(n) , the estimate being connected to the Algorithm part of the adaptive FBC-filter.
  • the ideal purpose of the Enhancement unit is to ensure that the signal us(n) is uncorrelated with the (target) input signal x(n).
  • an Enhancement unit may be located on the input side of the forward path (cf. the Enhancement unit in FIG. 1b with a dashed outline).
  • an additional Enhancement unit is provided on the input side (dashed outline in FIG. 1b ), which is matched to the Enhancement unit on the output side, in this case to extract the same characteristics from the (here) feedback corrected input signal e(n) that are extracted or estimated from the output signal u(n) by the Enhancement unit on the output side.
  • An object of the present invention is to provide an alternative scheme for minimizing feedback in audio processing systems, e.g. listening devices.
  • An audio processing system e.g. a listening device or a communication device:
  • an audio processing system e.g. a listening device or a communication device for processing an input sound to an output sound as defined in claim 1.
  • the audio processing system e.g. a listening device, comprises among others,
  • the output transducer is a receiver (loudspeaker) for converting an electric input (e.g. said processed electric output signal) to an acoustic output (a sound).
  • the aim of the enhancement unit is to extract signal components with certain pre-specified characteristics (e.g. inserted modulation characteristics, e.g. an AM-function, noise-like signal components, etc.) in the input signal to the enhancement unit, or in other words to eliminate or reduce signal components (in the input to the feedback path estimation unit), which are NOT related to a deliberately inserted probe signal or NOT related to the 'noise' intrinsically present in the signal (e.g. the receiver signal).
  • certain pre-specified characteristics e.g. inserted modulation characteristics, e.g. an AM-function, noise-like signal components, etc.
  • 'originating from' is in the present context taken to mean being equal to or related to by means of attenuation, amplification, compression, filtering or other audio processing algorithms.
  • terms 'noise' or 'noise-like components' in relation to signal components of the audio processing system e.g. a listening device (e.g. related to a signal of the forward path, e.g. to an input signal to a receiver of the audio processing system (listening device)), refer to signals or signal components (e.g. viewed in a particular frequency range or band), which are uncorrelated with the (target) input signal x(n).
  • This noise or these noise-like components of a signal typically having very little structure (or short correlation time) and therefore noisy in appearance, is/are of key importance to the present invention.
  • a 'noise like part of the (receiver) signal' is taken to mean one or more components in the (receiver) signal, which are substantially uncorrelated with the input signal.
  • the terms 'uncorrelated' or 'substantially uncorrelated' are in the present context taken to mean 'having a correlation time smaller than or equal to a predefined value'. Since, typically, the receiver signal is approximately a delayed (and scaled) version of the input signal, this is equivalent to saying that a noise-like part of the receiver signal comprises signal components in the receiver signal with a correlation time smaller than the delay of the forward path.
  • these components would correspond to time-frequency regions corresponding to 'noise-like' speech sounds such as /s/ and /f/, or high-frequency regions of some vowel speech sounds.
  • these components would typically include time-frequency regions where the acoustical noise is dominant as well, assuming that the acoustical noise has low correlation time itself; this is the case for many noise sources, see e.g. [Lotter, 2005].
  • the term 'time-frequency region' implies that a signal is available in a time-frequency representation, where a time representation of the signal exist for the frequency bands constituting the frequency range considered in the processing.
  • a 'time-frequency region' may comprise one or more frequency bands and one or more time units.
  • a 'time-frequency region' may comprise one or more time-frequency units.
  • the concepts and methods of the present invention may in general be used in a full band processing system (i.e. a system wherein each processing step is applied to the full frequency range considered).
  • a full range considered by the audio processing system e.g. a listening device (i.e. a part of the human audible frequency range (20 Hz - 20 kHz), such as e.g. the range from 20 Hz to 12 kHz) is split into a number of frequency bands (e.g. 2 or more, such as e.g. 8 or 64 or 256 or 512 or 1024 or more), where at least some of the bands are processed individually in at least some of the processing steps.
  • the feedback path estimation unit comprises an adaptive filter.
  • the adaptive filter comprises a variable filter part and an algorithm part, e.g. an LMS or an RLS algorithm, for updating filter coefficients of the variable filter part, the algorithm part being adapted to base the update at least partly on said noise signal estimate output from the enhancement unit and/or on a probe signal from a probe signal generator.
  • the duration in time of X samples is thus given by X/fs.
  • the signal processing unit is adapted for processing the input signal originating from the electric input signal in frequency bands.
  • the processing of the signal in the forward path e.g. the application of a frequency dependent gain
  • the processing of the signal in the forward path is performed in a number of frequency bands.
  • a control path for determining gains to be applied to the signal of the forward path is defined.
  • the processing in the control path (or a part thereof) is performed in a number of frequency bands.
  • a frame can in principle be of any length in time. Typically consecutive frames are of equal length in time.
  • a time frame is typically of the order of ms, e.g.
  • a time frame has a length in time of at least 8 ms, such as at least 24 ms, such as at least 50 ms, such as at least 80 ms.
  • the sampling frequency can in general be any frequency appropriate for the application (considering e.g. power consumption and bandwidth).
  • the sampling frequency f s of an analog to digital conversion unit is larger than 1 kHz, such as larger than 4 kHz, such as larger than 8 kHz, such as larger than 16 kHz, e.g. 20 kHz, such as larger than 24 kHz, such as larger than 32 kHz.
  • the sampling frequency is in the range between 1 kHz and 64 kHz.
  • the audio processing system comprises at least one input transducer (e.g. a microphone) for picking up a noise signal (termed ANC-reference) from the environment.
  • the audio processing system comprises at least one input transducer (e.g. a microphone) for picking up (measuring) a residual (noise) signal (termed ANC-error).
  • the audio processing system is adapted to provide an anti-noise signal presented by the output transducer of the system in the form of an acoustic signal having an amplitude and phase adapted for cancelling the noise signal from the environment, whereby an active noise cancelling system is provided.
  • no probe signal generator is included in the audio processing system, e.g. a listening device.
  • the enhancement unit block Retrieval of intrinsic noise in FIG. 2c
  • the enhancement unit is adapted to extract noise-like parts of the receiver signal (and/or of a signal on the input side), e.g. originating from a speech signal, and to use the extracted noise estimate as an input to the estimation of the acoustic feedback path.
  • the enhancement unit is adapted for retrieving intrinsic noise-like signal components in the electric signal of the forward path.
  • the enhancement unit is adapted for extracting noise-like parts of the output signal u(n).
  • the enhancement unit takes the output signal u(n) as an input and provides as an output an estimate us(n) of the noise-like parts of the output signal u(n) , the estimate being connected to the feedback path estimation unit, e.g. the Algorithm part of an adaptive FBC-filter (cf. e.g. FIG. 1b ).
  • an enhancement unit for extracting noise-like parts of the feedback corrected input signal e(n) may be inserted (as indicated in FIG.
  • the output from the additional or alternative enhancement unit provides an estimate es (n) of characteristics (e.g. noise-like parts) in the feedback corrected input signal e(n), which is connected to the feedback path estimation unit, e.g. the Algorithm part of an adaptive FBC-filter and used in the calculation of update filter coefficients of the variable filter part Fh(z,n) of the adaptive FBC-filter (cf. e.g. FIG. 1b ).
  • characteristics e.g. noise-like parts
  • the retrieval of intrinsic noise may be combined with insertion of probe signal(s). Examples thereof are described in the section on 'Modes for carrying out the invention' (cf. e.g. FIG. 2e , 2f , 2g , 6b ).
  • the correlation time N 1 of the noise signal estimate output from the enhancement unit is adapted to obey the relation N 1 ⁇ dG + dA, where dG is the delay of the forward path and dA is the average acoustic propagation delay of an acoustic sound from the output of the receiver to the input of the microphone, when following a direct physical path (not including reflections e.g. from external objects).
  • the correlation time N 1 of the noise signal estimate output obeys N 1 ⁇ dG.
  • the delay of the forward path is in the present context taken to mean the delay from the microphone input via the electric forward path to the output of the receiver.
  • the forward path delay can e.g.
  • the average acoustic propagation delay can e.g. be determined in a similar manner with the hearing device mounted on/in the ear.
  • the enhancement unit comprises an adaptive filter.
  • the sub-band signals are down-sampled, so that the efficient sample rate is much lower.
  • the time span e.g. 6.4 ms can be the same, but since the sample rate is usually much lower, the filter order used for each sub-band filter can then be correspondingly lower.
  • the enhancement unit(s) is/are fully or partially implemented as software algorithms.
  • the audio processing system e.g. a listening device, comprises a probe signal generator for generating a probe signal (e.g. embodied in the signal processing unit).
  • the probe signal contributes to the estimation of the feedback transfer function.
  • the probe signal generator is adapted to provide that the probe signal has predefined characteristics
  • the enhancement unit is adapted to provide a signal estimate output based on said characteristics (it is matched to the predefined characteristics).
  • the characteristics of the probe signal are e.g. selected from the group comprising a modulation index, periodicity, correlation time, noise-like signal components and combinations thereof.
  • the probe signal generator is adapted to provide that the probe signal has a correlation time N 0 ⁇ 64 samples (corresponding to 3.2 ms at a sampling rate of 20 kHz).
  • N 0 a correlation time
  • N 0 a correlation time
  • P the correlation time N 0 of the generated noise
  • the probe signal us(n) is adapted to be inaudible when combined with the output signal y(n) from the forward gain unit.
  • the algorithm part of the feedback path estimation unit comprises a step length control block for controlling the step length of the algorithm in a given frequency region, and wherein the step length control block receives a control input from the probe signal generator.
  • the step length control block adjusts the speed at which the adaptive filter estimation algorithm converges (or diverges).
  • the step length control algorithm would typically increase the convergence rate.
  • the probe signal generator(s) is/are fully or partially implemented as software algorithms.
  • FIG. 1c illustrates the general concept of the use of retrieval of characteristics (e.g. noise or any other specific property) AND insertion of a probe signal for estimating a feedback transfer function.
  • the example of an audio processing system, e.g. a listening device, in FIG. 1c comprises the same components as the audio processing system, e.g. a listening device, of FIG. 1a .
  • the example in FIG. 1c comprises an Enhancement unit for extracting characteristics (e.g. noise-like parts) of the feedback corrected input signal e(n) and providing an estimate es(n) of such characteristics to the Algorithm part of the adaptive FBC-filter (instead of the feedback-corrected input signal e(n) ) as discussed in connection with FIG. 1b .
  • the Enhancement unit is matched to the characteristics of the inserted probe signal (be the inserted probe signal characterized by its correlation time, its modulation form, its periodicity, or the like).
  • the Probe signal generator unit receives its input from the output y(n) from the forward gain unit G(z,n).
  • the Probe signal unit may alternatively (or additionally) receive its input from the input side of the forward path to provide sufficient processing time for the generation of the Probe signal relative to the output signal u(n). This is illustrated by the dashed arrow connecting the feedback corrected input signal e(n) to the Probe signal unit.
  • the probe signal may be generated in any appropriate way, e.g. fulfilling the requirements of non-correlation indicated in the following.
  • a signal us(n) for use in feedback estimation which is substantially uncorrelated with the input signal x(n) is generated.
  • us(n) consists of a synthetic noise sequence added to y(n)
  • us(n) consists of filtered noise replacing signal components in y(n)
  • us(n) consists of signal components already present in y(n).
  • probe signal generation and/or enhancement/retrieval methods are:
  • Methods A and B modify the signal y(n) (cf. e.g. FIG. 1d ) by adding/substituting filtered noise, whereas the method of intrinsic noise retrieval mentioned above under the heading 'Noise retrieval.
  • No probe signal inserted' (and referred to in the detailed description of embodiments as Method C) does not modify the signal but simply aims at extracting (retrieving) the signal components which are uncorrelated with x(n), and which are intrinsically present in a signal of the forward path (the intrinsic 'noise-like part of the signal'), e.g. signal u(n) in the examples of FIG. 1b and 1d .
  • the probe signal generator is adapted to provide a probe signal based on masked added noise.
  • the probe signal generator comprises an adaptive filter for filtering a white noise input sequence w , the output of the variable part M of the adaptive filter forming the masked probe signal, and the variable part M of the adaptive filter being updated based on a signal from the forward path by an algorithm part comprising a model of the human auditory system.
  • the masked probe signal is based on a signal from the output side. Alternatively or additionally, it may be based on a signal from the input side of the forward path.
  • 'a white noise sequence' is taken to mean a sequence representing a digital version of a white noise signal.
  • White noise is in the present context taken to mean a signal with a substantially flat power spectral density (in the meaning that the signal contains substantially equal power within a fixed bandwidth when said fixed bandwidth is moved over the frequency range of interest, e.g. a part of the human audible frequency range).
  • the white noise sequence may e.g. be generated using pseudo random techniques, e.g. using a pseudo-random binary sequence generator.
  • the probe signal generator is adapted to provide a probe signal based on perceptual noise substitution, PNS.
  • the probe signal generator comprises a PNS-part located in the forward path, and bases its output on a perceptual noise substitution algorithm (PNS) for substituting one or more spectral regions of its input signal with filtered noise sequences.
  • PNS perceptual noise substitution algorithm
  • the PNS-part receives an input from the output side of the forward path, i.e. originating from the signal processing unit.
  • the PNS-part receives an input from the input side of the forward path, e.g. originating from the feedback corrected input signal.
  • the purpose of the PNS-part is to process the signal y(n) so as to ensure that the receiver signal u(n) is uncorrelated to the (target) input signal x(n), at least in certain frequency regions (cf. e.g. FIG. 2b ). This is achieved by substituting selected spectral regions of the output signal y(n) of the forward path unit G(z,n) (cf. FIG. 1d and 2b ) and/or of another signal of the forward path (e.g. the feedback corrected input signal e(n) ) with filtered noise sequences and thereby ensure a predefined degree of (un-) correlation in the frequency regions in question.
  • the signal e(n) comprises inserted characteristics, e.g. noise components, or intrinsic noise components (filtered through the feedback channel F(z,n) and the estimated feedback channel Fh(z,n) ) along with nonnoise components, e.g. speech (which typically have much higher energy).
  • the noise-like components in e(n) represent the signal of interest, whereas the 'rest' of e(n) (here) is considered as 'interference'.
  • the adaptive Fh filter estimation block may operate using e(n) as an input, as is done in traditional probe noise solutions (cf. e.g. EP 0 415 677 A2 ), but due to the unfavourable target noise-to-interference ratio (NIR), the adaptation must be very slow, leading to a system which is generally too slow to track real-world feedback paths.
  • NIR target noise-to-interference ratio
  • the algorithms for noise enhancement/retrieval include, but are not limited to:
  • any method (or combination of methods) of generating noise including the methods outlined above are intended to be combinable with any method (or combination of methods) for noise enhancement/retrieval including the methods outlined in the following.
  • the enhancement unit comprises an adaptive filter.
  • the adaptive filter can be non-linear or linear.
  • the non-linear and linear filters can be based on forward prediction or backward prediction or a combination of both.
  • a linear adaptive filter can be of the IIR or FIR-type.
  • the enhancement unit is adapted to base the signal estimate output on an adaptive long-term prediction, LTP, filter D(z,n) adapted for filtering a feedback corrected input signal on the input side of the forward path to provide a noise signal estimate output comprising noise-like signal components of said feedback corrected input signal.
  • D(z,n) represents the resulting filter
  • LE(z,n) represents the variable filter part
  • N 2 is the maximum correlation time
  • d p are the filter coefficients adapted to minimize a statistical deviation measure of es(n) (e.g.
  • the filter coefficients d l are estimated here to provide the MSE-optimal linear predictor, although other criteria than MSE (Mean Square Error) may be equally appropriate (e.g. minimize ⁇ [
  • the feedback path delay (dF) is taken to mean the time it takes an impulse in the electrical receiver signal u(n) to be registered in the electrical microphone signal.
  • the efficient impulse response length ( d IR,eff ) is taken to mean the time span from the impulse is registered in the electrical microphone signal until the final decay of the impulse response.
  • the feedback path delay can e.g. be estimated from the distance from the receiver to the microphone (and the speed of sound), or determined more accurately using acoustical/electrical measurements.
  • the order P 2 of the LTP-filter is in the range from 16 to 512.
  • the enhancement unit comprises a sensitivity function estimation unit.
  • this unit aims at compensating for the fact that the hearing aid operates in closed-loop in any practical situation, while the feedback path estimation algorithms are designed with an open-loop situation in mind.
  • the algorithms are brought closer to the situation for which they were designed, and their performance is improved.
  • the estimation of the sensitivity function has the largest impact on the performance at high loop gains.
  • the sensitivity function is e.g. discussed in [Forsell, 1997].
  • the enhancement unit is adapted to provide a noise signal estimate output based on binaural prediction filtering, wherein an adaptive noise retrieval unit is adapted for filtering a signal y c from another microphone, e.g. from the input side of the forward path (e.g. a feedback corrected input signal) of a contra-lateral listening device.
  • an adaptive noise retrieval unit is adapted for filtering a signal y c from another microphone, e.g. from the input side of the forward path (e.g. a feedback corrected input signal) of a contra-lateral listening device.
  • a signal from another microphone has the advantage that it allows, in principle, more of the introduced noise to be retrieved than with the LTP method described above. This is the case since the proposed filtering is based on current signal samples (from an external sensor) rather than past samples from the current sensor.
  • N 3 is chosen in the range 0 ⁇ N3 ⁇ 400 samples (corresponding to 20 ms at a sampling rate of 20 kHz).
  • the order P 3 of the filter LB(z,n) is in the range from 32 to 1024 or larger than 1024.
  • the audio processing system comprises a first enhancement unit on the input side and a second enhancement unit on the output side, each enhancement unit being electrically connected to the feedback estimation unit, and an enhancement control unit adapted to improve, e.g. optimize, the working conditions of the feedback estimation unit, e.g. maximize the ratio between the probe signal and the interfering signal, the interfering signal comprising all other signal components which are NOT associated with the probe signal.
  • the audio processing system comprises a master enhancement unit on the input side and a slave enhancement unit on the output side, each enhancement unit being electrically connected to the feedback estimation unit, wherein the slave enhancement unit is adapted to provide the same transfer function as the master enhancement unit.
  • the master and slave enhancement units are electrically connected to an algorithm part of an adaptive filter forming part of or constituting the feedback estimation unit, the inputs to the algorithm part from the master and slave enhancement units constituting e.g. the error signal and the reference signal, respectively.
  • the master and slave enhancement units each comprise an adaptive filter.
  • the (time varying) filter coefficients of the master enhancement unit are copied to the slave enhancement unit to provide a filtering function which is equal to the filtering function of the master enhancement unit.
  • the adaptive filter comprises an algorithm part and a variable filter part.
  • the algorithm part of the adaptive filter of the master enhancement unit simply controls the variable filter parts of the adaptive filters of the master and slave enhancement units.
  • the audio processing system comprises a public address system (e.g. for use in a classroom or auditorium, in a theatre, at concerts, etc.), an entertainment system (e.g. a karaoke system), a teleconferencing system, a communication system (e.g. a telephone, e.g. a cellular phone, a PC, etc.), a listening device (e.g. a hearing aid, a headset, an active ear protection system, a head phone, etc.).
  • the audio processing system comprises two or more separate physical units, e.g. separate microphone and/or speaker unit(s), which are connected to other parts of the system via wired or wireless connection(s).
  • use of the audio processing system in a communication device or in a listening device or in an audio delivery system is provided.
  • use in connection with active noise control ANC e.g. adaptive noise cancellation
  • use of the audio processing system for active noise control in a communication device or in a listening device is provided.
  • use of the audio processing system for active noise control of noise from a machine is provided.
  • a low delay acoustic system is a system with a low delay between input and output transducer (low forward path delay), in particular a system with a low loop delay (loop delay being defined as the sum of the processing delay in the forward path and the delay in the feedback path), in particular a system where a large correlation exists between the target input microphone signal and the loudspeaker signal.
  • 'low delay' is e.g. taken to mean less than 50 ms, such as less than 20 ms, such as less than 10 ms, such as less than 5 ms, such as such than 2 ms.
  • a method of operating an audio processing system e.g. a listening device or a communication device:
  • a method of estimating a feedback transfer function in an audio processing system comprising a feedback estimation system for estimating acoustic feedback as defined in claim 13 is furthermore provided by the present invention.
  • the audio processing system e.g. a listening device or a communication device, comprises, among others, forward path between an input transducer and an output transducer and comprising a signal processing unit adapted for processing an input signal originating from the electric input signal and to provide a processed output signal u , an electric feedback loop from the output side to the input side comprising a feedback path estimation unit for estimating the feedback transfer function from the output transducer to the input transducer, the method comprising
  • characteristics of the electric signal of the forward path comprise one or more of the following: modulation index, periodicity, correlation time, noise or noise-like parts.
  • extracting characteristics of the electric signal of the forward path comprises estimating signal components in the electric signal of the forward path originating from noise-like signal parts and the estimated characteristics output comprises a noise signal estimate output.
  • noise-like signal parts in the forward path are provided in the form of intrinsic noise in the target signal.
  • the method further comprises inserting noise-like signal parts in the forward path, e.g. in the form of a probe signal.
  • a computer-readable medium :
  • a tangible computer-readable medium storing a computer program comprising program code means for causing a data processing system to perform at least some of the steps (such as a majority or all of the steps) of the method described above, in the detailed description of 'mode(s) for carrying out the invention' and in the claims, when said computer program is executed on the data processing system is furthermore provided by the present invention.
  • the computer program can also be transmitted via a transmission medium such as a wired or wireless link or a network, e.g. the Internet, and loaded into a data processing system for being executed at a location different from that of the tangible medium.
  • connection or “coupled” as used herein may include wirelessly connected or coupled.
  • the term “and/or” includes any and all combinations of one or more of the associated listed items. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless expressly stated otherwise.
  • FIG. 1a A prior art probe noise based solution of an adaptive feedback cancellation (FBC) system is shown in FIG. 1a and described in the Background art section above.
  • FBC adaptive feedback cancellation
  • FIG. 1b illustrates the general concept of noise retrieval using enhancement of (possibly) intrinsic noise-like signals in the estimation of the feedback path.
  • the embodiment of an audio processing system e.g. a listening device or a communication device, according to the example in FIG. 1b comprises the same components as the audio processing system, e.g. a listening device or a communication device, of FIG. 1a , except that the Probe signal generator (and the output SUM unit '+') is omitted so that the output signal to the receiver u(n) is the output of the forward gain unit G(z,n).
  • a forward path is defined between the microphone and the receiver.
  • An input side of the forward path is defined by the microphone and an output side of the forward path is defined by the receiver.
  • a delimiting functional unit between input and output side of the forward path can e.g. be a block in the forward gain unit G(z,n) providing a frequency dependent gain.
  • An Enhancement unit for extracting noise-like parts of the output signal u(n) is provided. It takes the output signal u(n) as an input and provides as an output an estimate us(n) of the noise-like parts of the output signal, the estimate being connected to the Algorithm part of the adaptive FBC-filter. Additionally (or alternatively), an Enhancement unit for extracting noise-like parts (and/or other characteristics) of the feedback corrected input signal e(n) may be inserted (as indicated by the dashed outline of the Enhancement unit in the input path for the Algorithm part).
  • the output from the (optional) additional Enhancement unit provides an estimate es(n) of the noise-like parts in the feedback corrected input signal e(n), which is connected to the Algorithm part of the adaptive FBC-filter and used in the calculation of update filter coefficients of the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • the optional Enhancement unit on the input side is absent, in which case the input to the Algorithm part is the feedback corrected input signal e(n).
  • the notation (e.g. u(n) , e(n)) for signals of the an audio processing system, e.g. a listening device, indicates a digital representation, which is preferred.
  • the system or device comprises analogue to digital (A/D) and digital to analogue (D/A) conversion units, where appropriate (e.g. in the forward paths as part of or subsequent to the microphone and prior to the receiver units, respectively).
  • preferred embodiments comprise processing of signals in a time-frequency framework.
  • the an audio processing system e.g. a listening device, comprises time to time-frequency conversion units and time-frequency to time conversion units, where appropriate (e.g. filter banks and synthesizer units, respectively, or Fourier transform and inverse Fourier transform units/algorithms, respectively, e.g.
  • a directional microphone system (e.g. providing directionally preferred directions of the microphone sensitivity) may form part of the processing of the input signal, before or after the estimate of the feedback path is subtracted.
  • other functional blocks of an audio processing system e.g. a listening device, may be integrated with those described in connection with the present invention, e.g. systems or components for noise reduction, compression, warping, etc.
  • the notation e.g. G(z,n) and Fh(z,n) in connection with transfer functions, e.g.
  • FIG. 1c illustrates the general concept of the use of noise retrieval AND a probe signal.
  • FIG. 1c is described in the Disclosure of invention section above.
  • the probe signal may be generated in any appropriate way fulfilling the requirements of non-correlation indicated in the following.
  • various implementations of a Probe signal unit for generating a probe signal are discussed below (noise generation methods A, B).
  • FIG. 1d shows a general block diagram of an embodiment of the proposed audio processing system, e.g. a listening or communication system.
  • An output signal, u(n) is connected to a receiver for converting an electric input to an acoustic output.
  • the acoustic output leaks back to the microphone through some (unknown) feedback channel F(z,n).
  • the microphone picks up the (desired) target signal x(n), e.g. a speech signal.
  • This signal is connected to a forward path unit G(z,n), which represents noise suppression, amplification, compression, etc., to form the processed signal y(n).
  • G(z,n) represents noise suppression, amplification, compression, etc.
  • Probe signals block represented by the block Probe signals Addition and / or substitution of noisy and / or tonal signals, termed Probe signals block in the following).
  • an estimate Fh(z,n) of the feedback channel F(z,n) is computed.
  • the Fh filter estimation block updates the filter estimate Fh(z,n) across time using any of the well-known adaptive filtering approaches such as (normalized) Least-Mean Square ((N)LMS), recursive least squares (RLS), methods based on affine projections (AP), Kalman filtering, etc.
  • NLMS Least-Mean Square
  • RLS recursive least squares
  • AP affine projections
  • Kalman filtering etc.
  • the feedback signal v(n) will largely be eliminated from the feedback compensated signal e(n) by the feedback estimate signal vh(n).
  • the output y(n) of the forward path unit or as in FIG. 1d , the output u(n) of the Probe signals block
  • the Fh filter estimation block cf. Retrieval of intrinsic noise block in FIG. 1d providing an estimate of output noise us(n).
  • the feedback compensated signal e(n) is processed before it enters the Fh filter estimation block, cf.
  • Retrieval of feedback noise block in FIG. 1d providing an estimate of input noise es(n). Consequently, we propose in some embodiments of the invention to introduce some or all of the blocks denoted in FIG. 1d as Probe signals, Retrieval of intrinsic noise, and Retrieval of feedback noise, accompanied by an appropriate Control block.
  • Probe signals and/or Retrieval of intrinsic noise is to ensure that the signal us(n) is substantially uncorrelated with the (target) input signal x(n) .
  • This may be achieved by e.g. generating and adding to the output y(n) of the forward path unit an inaudible noise sequence, which by construction is uncorrelated with x(n) (Probe signals block in FIG. 1d ), and/or replacing time-frequency regions in y(n) with filtered noise whenever this does not lead to audible artefacts ( Probe signals block in FIG. 1d ), and/or filtering out signal components from the receiver signal u(n) , which are uncorrelated with x(n) (Retrieval of intrinsic noise block in FIG. 1d ).
  • the general purpose of the Retrieval of feedback noise block is to filter out/retrieve signal components of the feedback corrected input signal e(n) originating from noise (e.g. from us(n) ) .
  • Signal components in e(n) which do not originate from us(n) are, seen from the Fh filter estimation block, interference, and should ideally be rejected by the Retrieval of feedback noise block.
  • the blocks Retrieval of intrinsic noise and Retrieval of feedback noise providing the estimates us(n) and es(n), respectively, of noise-like signals may receive other inputs than the output u(n) and the feedback corrected input signal e(n).
  • one or both (as in FIG. 1d ) of these noise retrieval blocks receive one or more External signals as inputs.
  • Such signals can e.g. be an acoustic signal picked up by another microphone, either in the same hearing aid or elsewhere, e.g. from a contra-lateral hearing aid, an external device, or other external sensors.
  • FIG. 1d Such signals can e.g. be an acoustic signal picked up by another microphone, either in the same hearing aid or elsewhere, e.g. from a contra-lateral hearing aid, an external device, or other external sensors.
  • the Retrieval of intrinsic noise block may receive - in addition to (or instead of) the output signal u(n) - an input from the Probe signals block.
  • This input can be the noise sequence inserted by the Probe signals block or information describing in which signal regions the noise is inserted.
  • the Retrieval of intrinsic noise block might then operate primarily in signal regions where noise is NOT inserted by the Probe signals generator.
  • the Control block is e.g. adapted to monitor and adjust the operation of the adaptive filter in the Fh filter estimation block in order to ensure that the loop gain of the system is appropriate.
  • the feedback path may change quickly (e.g. when a telephone is placed by the ear), and the loop gain will become momentarily high leading to poor signal quality or even howls.
  • a purpose of the Control block is to adjust the operation of the blocks G(z,n), Probe signals Addition and / or substitution of noisysy and / or tonal signals, Retrieval of intrinsic noise, Fh filter estimation and Retrieval of feedback noise, in order to extinguish the howl quickly and bring the system loop gain down. More specifically, based on the amount of inserted/intrinsic and/or retrieved noise in a given signal region, the Control block adjusts the adaptation speed of the adaptive filter. If e.g. a signal region has been substituted by filtered noise, the convergence rate (represented by a step length parameter ⁇ ) can be increased.
  • the Control block may also base its decisions on results from external detector algorithms, e.g.
  • this procedure can also easily be reversed, such that the Control block informs the Probe signals Addition and / or substitution of noisysy and / or tonal signal block to insert an appropriate amount of noise in the receiver signal for a given loop gain (as estimated by a loop gain estimator). Furthermore, in high loop gain situations (as estimated by a loop gain estimator), the Control block may inform the G(z,n) block to reduce the gain applied in the forward path, and in this way reduce the total loop gain.
  • a loop gain estimator the Control block may inform the G(z,n) block to reduce the gain applied in the forward path, and in this way reduce the total loop gain.
  • FIG. 1e shows an application scenario for an audio processing system according to an embodiment of the present invention.
  • FIG. 1e illustrates an entertainment system comprising microphone M, base station BS and a number of speaker units (here three) SP1, SP2, SP3.
  • a speaker S (or singer) speaks (or sings) into microphone M, which is electrically connected to base station BS via a wired connection Wi (which could be wireless).
  • the utterance (indicated as 'myyyyy waaaayy' in FIG. 1e ) of speaker (or singer) S is processed in base station BS and the processed signal is forwarded or transmitted to speakers SP1, SP2, SP3 via a wired or wireless connection.
  • speaker SP1 is directly connected (e.g.
  • embodiments of the base station BS comprise the rest of the components of the systems as shown in FIG. 1b-1d . Alternatively, a part of the remaining components are included in the microphone unit or the speaker unit(s). The acoustic feedback may arise from the pickup by the microphone of the sound presented by the speakers. In the example of FIG.
  • FIG. 1e may illustrate a karaoke system, where the person S sings in microphone M and his or her voice is processed in base station BS and transmitted to the speakers SP1-SP3 possibly together with accompanying music.
  • FIG. 1e may represent a combination of a car stereo system and a telephone system, where the microphone part is used during a telephone conversation (preferably in a handsfree mode). The same acoustic feedback issues as discussed above may be relevant in such situation.
  • Another application which may be symbolized by FIG.
  • PA 1e is a so-called public address (PA) system, where one or more (typically wireless) microphones are worn by one or more persons (speakers, actors, singers, musicians), processed in a base station and relayed to one or more loud speakers.
  • PA public address
  • One such application is for amplifying a voice of a teacher in a classroom amplification system to enable the pupils to better hear the teacher's voice independently of their relative position to the teacher.
  • both microphone and speaker(s) are shown as physically separate units from the base station. In other embodiments, the microphone or the speaker(s) may be integrated with the base station.
  • a telephone e.g. a mobile telephone
  • its loudspeaker on, e.g. lying on a table to provide a handsfree operation to a user.
  • acoustic feedback between the loudspeaker and the microphones may well occur.
  • Another application is active noise cancelling, where a noise signal arriving at a user's eardrum is counteracted by a signal generated by the audio processing device and attempting to estimate the noise and where the estimate is presented to the user as an anti-noise acoustic signal adapted in phase and amplitude to cancel the noise signal.
  • active noise cancelling can e.g.
  • the signal from the loudspeaker of the device comprising the target signal (and the noise cancelling signal) may be acoustically fed back to the microphone(s) of the device being used for picking up sounds from the environment as illustrated in FIG. 1f .
  • FIG. 1f shows a listening device in the form of an active ear protection device EPD comprising an active noise cancellation system.
  • the ear protection device comprises an ear cup (EC) adapted for being placed over an ear of a user.
  • the ear protection device comprises an audio processing device (APD) comprising an input transducer (e.g. a microphone) M1 for picking up a signal from the environment, e.g. noise, and providing an electric input signal, a signal processing unit (SP) for processing the electric input signal and providing a processed output signal, and an output transducer for converting the processed output signal to an output sound for being presented to a user.
  • APD audio processing device
  • SP signal processing unit
  • the audio processing device is adapted to provide an acoustic cancellation (or anti-noise) signal N adapted in amplitude and phase to minimize or preferably cancel the acoustic signal N from the environment present at the ear of the user, thereby providing an active noise cancelling system.
  • a second input transducer e.g. a microphone
  • M2 picks up the acoustic signal (ANC-error signal) present at the ear (within the ear cup (EC) of the ear protection device EPD ) .
  • This (ANC-error) signal is preferably used to adaptively determine the anti-noise signal (by minimizing the ANC-error signal).
  • a part of the acoustic cancellation signal N may leak out of the ear protection device EPD, e.g. in case of insufficient contact between the ear cup EC and the head of the user, and reach the input transducer, thereby possibly leading to a feedback problem (howl).
  • Such feedback scenario may benefit from the teaching of the present application providing an improved estimate of the feedback cancellation path, thereby improving feedback cancellation.
  • This may be utilized to provide a more open ear piece (as an alternative to the closed ear cup shown in FIG. 1f ), which is more convenient for the user.
  • the ear protection device further comprises a direct electric input for enabling a user to receive an audio signal e.g.
  • an audio processing system as taught by the present disclosure may be in connection with communication devices (e.g. headsets, mobile telephones, etc.), the creation of acoustically quiet zones (e.g. in teleconferencing systems or call centre applications), active cancellation of machine noise, etc.
  • communication devices e.g. headsets, mobile telephones, etc.
  • the creation of acoustically quiet zones e.g. in teleconferencing systems or call centre applications
  • active cancellation of machine noise etc.
  • FIG 1i A more general sketch of an active noise control system employing an audio processing system as taught by the present application is shown in FIG 1i .
  • FIG. 1i shows a general model of active noise control ANC in the framework of an audio processing system APS as described in the present application.
  • the system shown in FIG. 1i is adapted to actively (and here adaptively) cancel noise from a source N by providing an anti-noise acoustic signal that minimizes or cancels the noise signal at the speaker unit AND minimizes the acoustic feedback from the speaker unit to the 1 st microphone M1 located to pick up sound from the noise source (as indicated by dashed line representing acoustic feedback path F).
  • the audio processing system APS can comprise any of the described embodiments.
  • the embodiment of the audio processing system APS shown in FIG. 1i is similar to the embodiment shown in FIG. 1g .
  • the probe signal generator is based on masked noise, see e.g. FIG. 3 .
  • the system of FIG. 1i comprises an ANC-reference microphone ( M1 , e.g. forming part of the audio processing system APS, as indicated by the dotted enclosure APS, or being separate there from) for picking of a noise reference signal and for being processed by an adaptive control unit (here adaptive filter ANC-filter Ph(z,n) ) to generate an anti-noise signal to be fed to the loudspeaker and intended to minimize the acoustic noise.
  • the system of FIG. 1i further comprises an ANC-error microphone ( M2 ) for monitoring the effect of the noise cancellation.
  • the signal picked up by the ANC-error microphone M2 is minimized by the adaptive filter ANC-filter Ph(z,n) to provide an estimate of acoustic path P from ANC-reference microphone M1 to ANC-error microphone M2 .
  • the system may be adapted to single channel (wideband) or multi channel operation.
  • the system further comprises an (optional) direct electric input (e.g. a direct (electric) audio input DAI ) for enabling a user to receive an audio signal e.g.
  • the device being adapted for presenting the received audio signal to the user via the output transducer (here by adding the DAI input signal to the anti-noise signal from the adaptive ANC-filter ( ANC-filter Ph(z,n) ) .
  • FIG. 1g shows an embodiment of an audio processing system with a probe signal generator ( Probe signal ) similar to that of FIG. 1c , but where in addition to the enhancement unit on the input side (in FIG. 1f denoted Eh _e) an enhancement unit (denoted Eh_u in FIG. 1g ) is inserted on the output side as well.
  • the two enhancement units are in communication with each other as indicated by control signal(s) ehc.
  • the enhancement unit Eh _ e on the input side is further in communication with the probe signal generator ( Probe signal ) via signal psc, e.g. regarding information of the characteristics of the probe signal.
  • the enhancement unit on the output side ( Eh_u ) is controlled by (matched to) the enhancement unit on the input side (Eh_e).
  • the characteristics of the filter e.g. its filter coefficients
  • the characteristics of the filter are mirrored in (e.g. copied to) the enhancement unit on the output side Eh_u (via signal(s) ehc) to provide an identical filtering function to that of the enhancement unit on the input side Eh_e .
  • the signal us'(n) resulting from the filtering of the probe signal us(n) by the enhancement unit on the output side Eh_u is fed to the algorithm part ( Algorithm ) of the adaptive FBC-filter and used to estimate the transfer function of the feedback path together with the signal es (n) generated by the enhancement unit on the input side Eh_e.
  • the use of a 'mirror enhancement unit' Eh_u in the input path of the algorithm part ( Algorithm ) of the adaptive FBC-filter has the advantage of providing an improved feedback path estimate, especially for small filter delays (cf. e.g. DE(z) of the LTP filter in section 2.2. below).
  • the probe signal us(n) generated by the probe signal generator can in general be of any appropriate kind (generating predefined characteristics), as long as the enhancement unit Eh _ e on the input side is matched to the probe signal in question (cf. e.g. control signal psc).
  • the probe signal is based on masked noise.
  • FIG. 1h shows an embodiment of an audio processing system similar to that of FIG. 1g , but where a enhancement control unit ( Enh-control ) determines the optimal settings of parameters (e.g. filter coefficients) of the two enhancement units (here termed Eh _ e and Eh_u indicating the location of the units on the input and output side, respectively, of the forward gain unit G(z,n) ) .
  • a enhancement control unit Enh-control
  • parameters e.g. filter coefficients
  • the enhancement control unit determines the settings of the two enhancement units based on information of the probe signal and on the signals us(n) (probe signal), us'(n) (output of enhancement unit Eh_u based on probe signal input us(n)), e(n) (the feedback corrected input signal), and es(n) (representing an estimate of characteristics in the feedback corrected input signal e(n) provided by enhancement unit Eh_e ).
  • the purpose of the enhancement control unit ( Enh-control ) is to improve, e.g. optimize, the working conditions of the feedback estimation unit, e.g. by maximizing the ratio between the probe signal and the interfering signal (the interfering signal being all other signal components (including a target speech signal) which are NOT associated with the probe signal).
  • Methods A and B modify the signal y(n) by adding/substituting filtered noise whereas Method C does not modify the signal but simply aims at extracting (retrieving) the signal components which are uncorrelated with the (target) input signal x(n), and which are intrinsically present in the signal y(n) (the 'noise-like part of the signal').
  • This method is illustrated by the embodiments of a listening device in FIG. 2a (embodiments ⁇ and ⁇ ).
  • the method aims at adding to the signal y(n) on the output side of the forward path a noise sequence us(n) (a sequence with low correlation time), which is uncorrelated with the input signal x(n), to form the receiver signal u(n).
  • the noise sequence us(n) may be generated by filtering a white noise sequence w(n) through an appropriately shaped, time-varying shaping filter M(z,n) in order to achieve a desired noise spectral shape and level.
  • the filter M(z,n) is estimated in block Noise shape and level, based on the signal y(n), cf. embodiment ⁇ in FIG. 2a as described below.
  • the shaping filter M(z,n) may be found through the use of models of the (possibly impaired) human auditory system, more specifically, using any of the many existing masking models, cf. e.g. [ISO/MPEG, 1993], [Johnston, 1988], [Van de Par et al., 2008].
  • the introduced noise sequence us(n) has the following properties:
  • the following additional noise property is preferably obeyed by the noise sequence us(n): P4):
  • the correlation time N 0 of the noise sequence us(n) obeys N 0 ⁇ dG + dF, i.e. a slight strengthening of requirement P3.
  • the level of the probe noise should preferably be low, e.g. at least 15 dB below u(n) ( y(n) ) on average, for requirement P1 to be approximately valid (for normally hearing persons), but probably quite a bit more for requirements P3 and P4 to be valid in a low-delay setup, like e.g. a hearing aid.
  • the processed output signal y(n) from the forward path unit G(z,n) (e.g. providing signal processing to compensate for a hearing loss) is connected to the block Masked probe noise for generating a masked noise based on a model of the human auditory system (which is fully or partially implemented in this block or more specifically in block Noise shape and le vel in embodiment ⁇ of FIG. 2a ).
  • the masked noise output us(n) of the block Masked probe noise is connected to the Fh filter Estimation unit for estimating the feedback path F .
  • the masked noise output us(n) is further added to the processed output signal y(n) from the forward path unit G(z,n) in SUM-unit '+' providing output signal u(n) , which is connected to the output transducer (receiver) and to the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • the output of the variable filter part Fh(z,n) providing an estimate vh(n) of the feedback signal v(n) is subtracted from the input signal from the microphone in SUM-unit '+', whose output e(n) is connected to the input of the forward path unit G(z,n) and to the Fh filter estimation unit.
  • the Control unit is in one- or two-way communication with the forward path unit G(z,n), the Masked probe noise unit and the Fh filter estimation unit, e.g. to monitor and adjust the operation of the adaptive filter in the Fh filter estimation block (e.g. including an adaptation rate).
  • the embodiment in FIG. 2a denoted ⁇ is identical to the embodiment denoted ⁇ as described above, except - as indicated by the dotted rectangle - that the Masked probe noise unit is implemented by shaping filter unit M(z,n), which is estimated by Noise shape and level unit based on input y(n) from the forward path unit G(z,n).
  • the masked noise us(n) is provided by the shaping filter unit M(z,n) based on a white noise sequence input w(n) and filter coefficients as determined by the Noise shape and level unit based on a model of the human auditory system (which is fully or partially implemented in this block).
  • White noise is in the present context taken to mean a random signal with a substantially flat power spectral density (in the meaning that the signal contains substantially equal power within a fixed bandwidth when said fixed bandwidth is moved over the frequency range of interest, e.g. a part of the human audible frequency range).
  • the white noise sequence may e.g. be generated using pseudo random techniques, e.g. using a pseudo-random binary sequence generator (with a large repetition number N psr , e.g. N psr ⁇ 1000 or ⁇ 10000).
  • the Control unit is in one- or two-way communication with the forward path unit G(z,n), the Noise shape and level unit and the Fh filter Estimation unit (as in embodiment ⁇ ).
  • PPS Perceptual Noise Substitution
  • the algorithm is embodied in block Probe signals in FIG. 1d .
  • the algorithm may be seen as a complement (or an alternative) to the added masked noise solution described above.
  • the method is illustrated by the embodiments of a listening device shown in FIG. 2b (embodiments ⁇ and ⁇ ).
  • the general goal is to process the signal y(n) so as to ensure that the receiver signal u(n) is uncorrelated to the (target) input signal x(n), at least in certain frequency regions.
  • the idea is to substitute selected spectral regions of the output signal y(n) of the forward path unit G(z,n) (cf. signal y(n) in FIG. 1d and 2b ) with filtered noise sequences and thereby ensure a degree of (un-) correlation in the frequency regions in question.
  • the advantage of the proposed procedure is that the desired noise-to-signal ratio in the substituted signal regions is high, much higher than what can typically be achieved with other probe noise solutions.
  • the modified receiver input signal u(n) ideally should be perceptually indistinguishable (for a particular user) from the original signal y(n)
  • not all time-frequency ranges or tiles can be substituted at all times.
  • the processed output signal y(n) from the forward path unit G(z,n) (e.g. providing signal processing to compensate for a hearing loss) is connected to the block PNS for providing Perceptual Noise Substitution, including substituting selected bands of the signal y(n) with filtered noise, to form the output signal u(n).
  • the selection of appropriate bands for substitution is controlled by the Control unit as indicated above (e.g. based on a perceptual model, masking model, etc.).
  • the Control unit is further in communication with the forward path unit G(z,n) and also controls the generation of filter coefficients for the variable filter part Fh(z,n) by the Fh filter Estimation unit.
  • the Fh filter estimation unit receives its inputs from the output signal u(n) (receiver input signal containing imperceptible noise in selected bands) and from the feedback corrected input signal e(n), respectively.
  • the embodiment ⁇ of FIG. 2b comprises the same functional units connected in the same way as in the embodiment ⁇ of FIG. 2a .
  • FIG. 2b denoted ⁇ is largely identical to the embodiment denoted ⁇ as described above.
  • two outputs of the PNS unit are shown, a first PNS-output upl(n) denoted No substituted frequency regions and comprising frequency bands that have been left unaltered and a second PNS-output ups(n) denoted Substituted frequency regions and comprising frequency bands comprising substituted frequency regions that are ideally substantially uncorrelated to the (target) input signal x(n).
  • the two output signals upl(n) and ups(n) from the PNS unit are combined in SUM unit '+' to provide the output signal u(n) , which is connected to the receiver and to the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • Both output signals upl(n) and ups(n) from the PNS unit are connected to the Fh filter estimation unit for - together with the feedback corrected input signal e(n) - generating filter coefficients for the variable filter part Fh(z,n) (possibly influenced by the Control unit) providing feedback estimate signal vh(n).
  • This method is illustrated by the embodiments of a listening device according to the example shown in FIG. 2c (embodiments ⁇ and ⁇ ).
  • the correlation time N 1 of the extracted sequence us(n) obeys N 1 ⁇ dG .
  • the signal components with low correlation time i.e. noise or noise-like signal parts, which are intrinsically present in y(n) are extracted and the corresponding signal connected to the Fh filter estimation block (cf. FIG. 2c ).
  • the extraction is performed in the Retrieval of intrinsic noise block of FIG. 2c .
  • the intrinsic noise components are understood to be parts of the signal y(n) which are noisy in character (although, the signal y(n) is not noisy in traditional sense). More specifically, the noise-like signal parts comprising components with low correlation time in (otherwise noise-free) speech signals could be speech sounds like /s/ and /f/. In the case where the signal y(n) is noisy in a traditional sense, e.g.
  • the Retrieval of intrinsic noise block can be implemented using an adaptive filter, e.g. an adaptively updated FIR filter with the following z-transform (cf. e.g. FIG.
  • the filter coefficients c p are updated across time in order to minimize the variance of the output, us(n), i.e. adapted to minimize ⁇ [
  • the updating of the filter coefficients c p may e.g. be performed using any of the well-known adaptive filtering algorithms, including (normalized) LMS, RLS, etc., cf. LR filter estimation unit in FIG. 2c ( ⁇ ).
  • the processed output signal y(n) from the forward path unit G(z,n) is connected to the enhancement unit Retrieval of intrinsic noise as well as to the receiver (thereby constituting the output (receiver input) signal).
  • the Retrieval of intrinsic noise unit extracts the noise-like part us(n) of the output signal y(n), e.g. as indicated above.
  • the noise-like signal us(n) is connected to the Fh filter estimation unit, which provides filter coefficients for the variable filter part Fh(z,n) estimating the feedback signal v(n).
  • the Control unit is in one-or two-way communication with the forward path unit G(z,n), the Retrieval of (intrinsic) noise unit and the Fh filter estimation unit.
  • the embodiment ⁇ of FIG. 2c comprises the same functional units ( G(z,n), Fh(z,n), F(z,n), microphone and receiver units) connected in the same way as the embodiment a of FIG. 2a .
  • the embodiment in FIG. 2c denoted ⁇ is identical to the embodiment denoted ⁇ as described above, except that the enhancement unit Retrieval of intrinsic noise is implemented by a Delay DR(z) unit, an LR filter estimation unit, an LR(z,n) variable filter unit and a SUM unit '+' (as indicated by the dotted rectangle enclosing these units).
  • the filter C(z,n) described above is implemented by the components Delay DR(z), LR(z,n) and SUM unit '+' enclosed by the dashed rectangle and denoted C(z,n).
  • the Delay DR(z) unit receives as an input the output signal y(n) from the forward path unit G(z,n) (which here is equal to the receiver input signal) and provides an output representing a delayed version of the input (e.g. with a delay corresponding to the delay of the forward path unit G(z,n)), which is connected to the LR filter estimation unit as well as to the variable filter unit LR(z,n).
  • the output of the variable filter unit LR(z,n) is subtracted from the output signal y(n) from the forward path unit G(z,n) in SUM unit '+', whose output represents the noise-like part us(n) of the output signal y(n) predicted based on previous samples of y(n).
  • the noise-like part us(n) of the output signal y(n) is connected to the LR filter estimation unit and used in the calculation of filter coefficients for the variable filter unit LR(z,n) as well as to the Fh filter estimation unit of the feedback cancellation system and used in the calculation of filter coefficients for the variable filter unit Fh(z,n).
  • the Control unit is in one- or two-way communication with the forward path unit G(z,n) and the two ( LR - and Fh-) filter estimation units.
  • noise generation or retrieval methods A, B and C may be mutually combined in any appropriate way (and with possible other schemes for generating appropriate noise sequences and possible other schemes for retrieving noise).
  • noise is typically added to the forward path on the output side (in the examples shown, after the forward path gain unit G(z,n) ). In practice, this need not be the case.
  • the noise generator(s) may insert noise-like signal parts at any appropriate location of the forward path, e.g. on the input side ( before the forward path gain unit G(z,n) ) or in the forward path gain unit G(z,n) or at several different locations of the forward path.
  • FIG. 2d illustrates a model of an embodiment of a listening device, wherein noise generation Method A (masked noise) and B (perceptual noise substitution) are used in combination.
  • the output signal y(n) of the forward path gain unit G(z,n) is connected to a PNS unit that (controlled by the Control unit) substitutes selected spectral regions of the output signal y(n) (e.g. with spectral content comprising noise-like signal components) and provides an output signal up(n) that is substantially uncorrelated to the (target) input signal x(n), at least in certain frequency regions.
  • the output up(n) from the PNS unit is represented by two outputs (as also in FIG.
  • a first PNS-output upl(n) denoted No substituted frequency regions and comprising frequency bands that have been left unaltered
  • a second PNS-output ups(n) denoted Substituted frequency regions and comprising frequency bands comprising substituted frequency regions that are ideally substantially uncorrelated to the (target) input signal x(n).
  • the two output signals upl(n) and ups(n) from the PNS unit are combined in SUM unit '+' to provide the output signal up(n).
  • the output signal up(n) is connected to a masked noise generator (indicated by dotted rectangle denoted Masked probe noise) comprising a Noise shape and level unit for estimating the time-varying shaping filter M(z,n), which filters a white noise sequence w(n) and provides as an output the masked noise signal ms(n).
  • Masked probe noise a Noise shape and level unit for estimating the time-varying shaping filter M(z,n)
  • the masked noise signal ms(n) is added to the second output ups(n) from the PNS unit in SUM unit '+' whose output us(n) is used together with the feedback corrected input signal e(n) as inputs to Fh filter estimation unit for generating filter coefficients for the variable filter part Fh(z,n) for estimating the feedback path.
  • the Fh filter estimation unit is in communication with the Control unit, which is also connected to the Noise shape and level unit, to the forward path gain unit G(z,n) and to the PNS -unit.
  • the masked noise signal ms(n) is further added to the (combined) output signal up(n) from the PNS unit in SUM unit '+' whose output signal u(n) is connected to the receiver and converted to an acoustic signal as well as to the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • the feedback corrected input signal e(n) is further, as in other embodiments, connected to the forward path gain unit G(z,n).
  • the output and input transducers, feedback F(z,n) and feedback estimation Fh(z,n) paths and signals v(n), vh(n) and x(n) have the same meaning as described in connection with other embodiments of the invention (e.g. FIG. 2a ).
  • the masked noise generation method (Method A, FIG. 2a ) and the perceptual noise substitution method (Method B, FIG. 2b ) and functional units for implementations thereof are further discussed above. Details of masking of noise and perceptual noise substitution are e.g. discussed by [Painter et al., 2000].
  • FIG. 2e illustrates block diagrams of two embodiments of a listening device according to the invention, wherein noise generation Method A (masked noise) and C (extraction of intrinsic noise-like parts) are used in combination.
  • Noise generation Method A mask noise
  • C extraction of intrinsic noise-like parts
  • the output signal y(n) of the forward path gain unit G(z,n) is connected to a masked noise generator (indicated by dotted rectangle denoted Masked probe noise, cf. also FIG. 2a and the discussion above) comprising Noise shape and level unit (controlled by a Control unit) for estimating time-varying shaping filter M(z,n), which filters white noise sequence w(n) and provides as an output the masked noise signal ms(n), which is added to the output signal y(n) of the forward path gain unit in SUM unit '+' to provide output signal u(n) , which is connected to the receiver.
  • Masked probe noise cf. also FIG. 2a and the discussion above
  • the output signal u(n) comprising masked noise is connected to an enhancement unit for retrieval of noise-like signal parts from the input signal (indicated by dotted rectangle denoted Retrieval of intrinsic noise, cf. also FIG. 2c and the discussion of Method C above).
  • the unit for retrieval of intrinsic noise-like signal parts comprises a Delay DR(z) unit, an LR Filter estimation unit, an LR(z,n) variable filter unit and a SUM unit '+'.
  • the Delay DR(z) unit receives as an input the output signal u(n) and provides an output representing a delayed version of u(n) , which is connected to the LR Filter estimation unit as well as to the variable filter unit LR(z,n).
  • the output of the variable filter unit LR(z,n) is subtracted from the output signal u(n) in SUM unit '+', whose output represents the noise-like parts us(n) (masked as well as intrinsic) of the output u(n).
  • the noise-like signal us(n) is connected to the LR Filter estimation unit as well as to the Fh filter estimation unit of the feedback cancellation system and used in the calculation of filter coefficients for the variable filter units LR(z,n) and Fh(z,n), respectively.
  • the Control unit is in one- or two-way communication with the two ( LR - and Fh-) Filter estimation units, with the Noise shape and level unit of the Masked probe noise generator and with the forward path gain unit G(z,n).
  • the feedback corrected input signal e(n) is used as a second input to the Fh filter estimation unit and is further, as in other embodiments, connected to the forward path gain unit G(z,n).
  • the output and input transducers, feedback F(z,n) and feedback estimation Fh(z,n) paths and signals v(n), vh(n) and x(n) have the same meaning as described in connection with other embodiments of the invention (e.g. FIG. 2a ).
  • Embodiment ⁇ of FIG. 2e is largely identical to embodiment ⁇ of FIG. 2e .
  • the two embodiments differ in that in embodiment ⁇ of FIG. 2e the input to the Retrieval of intrinsic noise unit is the output y(n) from the forward path gain unit G(z,n).
  • the noise retrieval unit extracts noise-like parts is(n) of the output signal ( y(n) ) before a (masked) probe signal (ms(n) ) has been added. Consequently, the masked noise signal ms(n) is added to the output is(n) of the Retrieval of intrinsic noise unit to provide the resulting noise estimate us(n), which is connected to the Fh filter estimation unit (as in embodiment ⁇ ).
  • This has the advantage that the Retrieval of intrinsic noise unit does not have to extract the noise-like parts of the signal that originated from the inserted probe noise.
  • the masked noise generation method (Method A, FIG. 2a ) and signal decomposition method comprising extraction of noise-like parts (Method C, FIG. 2c ) and functional units for implementations thereof are further discussed above.
  • FIG. 2f illustrates a model of an embodiment of a listening device according to the invention, wherein noise generation Method B (perceptual noise substitution) and C (extraction of (intrinsic) noise-like parts) are used in combination.
  • the output signal y(n) of the forward path gain unit G(z,n) is connected to a PNS unit that (controlled by the Control unit) substitutes selected spectral regions of the output signal y(n) and provides a first output signal upl(n) comprising frequency parts that have been left unaltered (output signal No substituted frequency regions in FIG.
  • the output signal is(n) of the Retrieval of intrinsic noise unit (the output of the SUM unit '+' in the dotted rectangle) is connected to a further SUM unit '+' together with the other output signal ups(n) of the PNS unit comprising the frequency parts that have been substituted with spectral content comprising noise-like signal components.
  • the output of this further SUM unit thus represents the estimate us(n) of the noise-like signal parts of the output signal u(n).
  • the estimate us(n) is connected to the Fh filter estimation unit together with the feedback corrected input signal e(n) and used to update the variable filter part Fh(z,n) of the adaptive FBC-filter for estimating the feedback signal v(n).
  • the LR- and Fh- filter estimation units can be influenced via the Control unit, which can also influence and/or receive information from forward path gain unit G(z,n) and the PNS unit.
  • the feedback corrected input signal e(n) is further, as in other embodiments, connected to the forward path gain unit G(z,n).
  • the output and input transducers, feedback F(z,n) and feedback estimation Fh(z,n) paths and signals v(n), vh(n) and x(n) have the same meaning as described in connection with other embodiments of the invention (e.g. FIG. 2a ).
  • FIG. 2g illustrates a model of an embodiment of a listening device according to the invention, wherein noise generation Method A (masked noise), Method B (perceptual noise substitution) and noise retrieval Method C (extraction of (intrinsic) noise-like parts) are used in combination.
  • the output signal y(n) of the forward path gain unit G(z,n) is connected to a PNS unit that (controlled by the Control unit) substitutes selected spectral regions of the output signal y(n) and provides a first output signal upl(n) comprising frequency parts that have been left unaltered (output signal No substituted frequency regions in FIG.
  • Noise shape and level unit (controlled by a Control unit) for estimating time-varying shaping filter M(z,n), which filters white noise sequence w(n) and provides as an output the masked noise signal ms(n), which is added to the combined output signal upx(n) from the PNS unit in further SUM unit '+' to provide output signal u(n) , which is connected to the receiver.
  • the Noise shape and level unit further receives input signal y(n) from the forward path gain unit G(z,n).
  • the Noise shape and level unit may further receive information from the Control unit regarding which bands have been subject to perceptual noise substitution in the PNS unit, which may advantageously influence the generation of masking noise.
  • the masked noise signal output ms(n) of shaping filter M(z,n) is further connected to a gain factor unit ' x ' for applying gain factor ⁇ to the masked noise signal ms(n).
  • the gain factor ⁇ can in general take on any value between 0 and 1.
  • ⁇ is equal to 1 or 0, controlled by the Control unit (cf. output ⁇ ).
  • the listening device further comprises an enhancement unit for retrieval of noise-like signal parts from an input signal (enclosed by dotted rectangle denoted Retrieval of intrinsic noise in FIG. 2g , cf. also FIG. 2c and the discussion of Method C above).
  • the embodiment of a unit for retrieval of noise-like signal parts comprises a Delay DR(z) unit, an LR filter estimation unit, an LR(z,n) variable filter unit and a SUM unit '+'.
  • the Retrieval of intrinsic noise block receives as an input the output ux(n) from SUM unit '+' providing signal (1- ⁇ ) ⁇ u(n) + ⁇ upl(n) via two gain factor units 'x' applying gain (1- ⁇ ) and ⁇ to signals u(n) and upl(n), respectively, where the gain factor ⁇ is controlled by the Control unit.
  • the gain factor ⁇ can in general take on any value between 0 and 1. In a preferred embodiment, ⁇ is equal to 1 or 0, controlled by the Control unit (cf. output ⁇ ) .
  • the Delay DR(z) unit provides an output representing a delayed version of the input ux(n).
  • the delayed output is connected to the LR filter estimation unit as well as to the variable filter unit LR(z,n) .
  • the output upm(n) ⁇ ms(n) + ups(n) from SUM unit '+' is added to the estimate is(n) of noise-like parts of the signal ux(n) in SUM unit '+', whose output represents the resulting noise-like signal us(n).
  • the noise-like signal us(n) is connected to the Fh filter estimation unit of the feedback cancellation system and used in the calculation of filter coefficients for the variable filter unit Fh(z,n) .
  • the Control unit is further in one- or two-way communication with forward path gain unit G(z,n) and the two ( LR- and Fh-) Filter Estimation units.
  • the electrical equivalent of the leakage feedback from output to input transducer F(z,n) resulting in input signal v(n) is added to a target signal x(n) in SUM unit '+' representing the microphone.
  • the feedback estimation Fh(z,n) resulting in feedback signal vh(n) is subtracted from the combined input x(n) + v(n) in SUM unit '+' whose output, the feedback corrected input signal e(n), is, as in other embodiments (cf. e.g. FIG. 2a ), connected to the forward path gain unit G(z,n) and to the Fh filter estimation unit.
  • the masked noise generation method (Method A, FIG. 2a ), the perceptual noise substitution method (B) and the signal decomposition method comprising extraction of noise-like parts (Method C, FIG. 2c ) and functional units for implementations thereof are further discussed above.
  • the algorithms for noise enhancement/retrieval include, but are not limited to:
  • any method (or combination of methods) of generating noise including the methods outlined above (methods A, B) are intended to be combinable with any method (or combination of methods) for noise enhancement/retrieval including the methods outlined in the following (methods I, II and C).
  • FIG. 3 shows a combination of noise generation method A (masked noise) with a noise enhancement/retrieval algorithm (Retrieval of feedback noise unit in FIG. 3a (cf. e.g. Enhancement unit in FIG. 1c ), e.g. implementing Method I as outlined below) in a model of an audio processing system, e.g. a listening device or a communication device, according to the present invention.
  • the model embodiment of FIG. 3a comprises the same elements as the model embodiment ⁇ of FIG. 2a .
  • the model embodiment of FIG. 3a comprises enhancement unit Retrieval of feedback noise for estimating the signal components of the feedback corrected input signal e(n) which originate from the masked noise signal us(n).
  • the output es(n) of the Retrieval of feedback noise unit is connected to the Fh filter estimation unit for updating the variable filter part Fh(z,n) of the adaptive FBC-filter for estimating the feedback signal v(n).
  • the other input to the Fh filter estimation unit is the masked noise signal output us(n) from the filter M(z,n) of the Masked probe noise generator.
  • the Retrieval of feedback noise unit is in one or two-way communication with a Control unit.
  • FIG. 3b shows an embodiment of an audio processing system comprising an enhancement unit ( Enhancement_e ) on the input side and additionally a (matched) enhancement unit ( Enhancement_u ) on the output side.
  • the model embodiment of FIG. 3b comprises the same elements as the model embodiment of FIG. 3a , but comprises additionally an enhancement unit ( Enhancement_u ) on the output side of the of the forward gain unit G(z,n), cf. also the embodiment of FIG. 1g .
  • the two enhancement units are in communication with each other as indicated by control signal copy.
  • the enhancement unit on the output side ( Enhancement_u )) is controlled by (matched to) the enhancement unit on the input side ( Enhancement_e ) .
  • the enhancement unit on the input side Enhancement_e is represented by a filter (e.g. filter D(z,n) as shown in FIG. 4 and discussed below in connection therewith)
  • the characteristics of the filter e.g. its filter coefficients
  • FIG. 3b may alternatively be configured with a control unit as shown in and discussed in connection with FIG. 1h .
  • the correlation time of noise signal us(n) preferably does not exceed No, i.e., during synthesis of us(n), the signal requirements P1-P3(P4) as outlined in the section on generation of masked noise (Method A) above are preferably obeyed.
  • the components of e(n) which originate from us(n) may be retrieved from the signal e(n) using the observation that the introduced/intrinsic noise in Methods A, B, C has a limited and known, correlation time, say N 0 .
  • the feedback path F(z,n) is (equivalent to) a FIR filter of order N, it follows that the correlation time of the noise picked up at the microphone has a correlation time no longer than N + N 0 .
  • signal components in e (n) with longer correlation time than N+No do not originate from the introduced/intrinsic noise sequence us(n).
  • Such a filter can be realized using an adaptively updated FIR filter with the following z-transform (cf. e.g. FIG. 4 , dashed rectangle denoted D(z,n)), where noise retrieval method I (based on long term prediction) is illustrated in combination with noise generation method A (masked noise, see also the corresponding treatment of the output signal y(n) to generate masked noise signal us(n) as discussed above in connection with Method A, and as illustrated in FIG.
  • z-transform cf. e.g. FIG. 4 , dashed rectangle denoted D(z,n)
  • D(z,n) represents the resulting filter
  • LE(z,n) represents the variable filter part
  • N 2 is the maximum correlation time
  • d p are the filter coefficients adapted to minimize ⁇ [es(n) 2 ], where ⁇ is the expected value operator, and P 2 is the order of the filter LE(z,n).
  • N 2 and P 2 depend on the application in question (sampling rate, frequency range considered, hearing aid style, etc.).
  • N 2 ⁇ 32 such as ⁇ 64, such as ⁇ 128.
  • the updating of the filter coefficients d p is performed in LE filter estimation unit in FIG. 4 (a, b).
  • z(n) can be seen as a prediction of e(n), based on signal samples which are at least N 2 samples old.
  • the filter coefficients d l are estimated here to provide the MSE-optimal linear predictor, although other criteria than MSE (Mean Square Error) may be equally appropriate. By doing so, components of the signal e(n) having a correlation time longer than N 2 are reduced.
  • D(z,n) is called a long-term prediction (LTP) error filter, a term coined in the area of speech coding [Spanias, 1994].
  • LTP long-term prediction
  • N 2 >>0 is taken to mean N 2 ⁇ 32, such as ⁇ 64 or ⁇ 128.
  • the NIR may be significantly improved and the adaptation rate of the Fh filter estimation block can be increased beyond what is possible with traditional systems based on probe noise.
  • the (probe) noise properties and the LTP error filter D(z,n) are chosen such that their characteristics match:
  • the introduced/intrinsic noise has a correlation time shorter than N 0
  • N 0 is in the range from 32 to 128 samples (assuming a sampling rate of 20 kHz).
  • D(z,n) can be seen as a matched filter.
  • N is e.g. equal to 64, this leads to N 2 in the range from 96 to 192.
  • the idea of introducing (probe) noise with certain characteristics is easy to generalize: Alternatively, for example, certain probe signal characteristics in the modulation domain can be introduced and a corresponding matched filter in this domain designed.
  • the adaptive filter D(z,n) is correspondingly implemented in Retrieval of feedback noise block by units Delay DE(z), LE(z,n), and SUM '+' (as indicated by the corresponding dashed enclosing rectangle denoted D(z,n)) providing output es(n) .
  • the Delay DE(z) unit receives feedback corrected input signal e(n) as an input and provides a delayed output which is connected to the algorithm and variable filter parts LE filter estimation and LE(z,n), respectively. The output of the variable filter part LE(z,n) is subtracted from the input signal e(n) in SUM unit '+'.
  • the output of the adaptive filter D(z,n) (i.e. output of Retrieval of feedback noise block, i.e. output of SUM-unit '+' in FIG. 4 ) is the signal es(n) representing the noise-like part of the (feedback corrected) input signal e(n).
  • the signal es(n) is connected to the variable filter part LE filter estimation of the adaptive filter D(z,n) as well as to the Fh filter estimation part of the FBC-filter and used in the latter to estimate of filter coefficients for estimating the feedback signal v(n).
  • the other input to the Fh filter estimation unit is the signal us(n) providing a masked noise signal generated by Masked probe noise unit (cf. FIG.
  • shaping filter unit M ( z,n ) which is estimated by Noise shape and level unit based on input y(n) from the forward path unit G(z,n) .
  • the masked noise us(n) is provided by the shaping filter unit M(z,n) based on a white noise sequence input w(n) and filter coefficients as determined by the Noise shape and level unit based on a model of the human auditory system.
  • the masked noise us(n) is added to the output y(n) from the forward path unit G(z,n) in SUM unit '+' to provide output signal u(n) connected to the receiver and to the variable filter part Fh(z,n) of the adaptive FBC filter.
  • a Control unit is in one- or two-way communication with the forward path gain unit G(z,n) , the Noise shape and level unit and the LE- and Fh- filter estimation units.
  • the electrical equivalent F(z,n) of the leakage feedback from output to input transducer resulting in input signal v(n) is added to a target signal x(n) in SUM unit '+' representing the microphone.
  • the feedback estimation Fh(z,n) (variable filter part of an adaptive FBC filter) resulting in feedback signal estimate vh(n) is subtracted from the combined input x(n) + v(n) in SUM unit '+' whose output, the feedback corrected input signal e(n), is connected to the forward path gain unit G(z,n) and (in the embodiment in FIG. 4a ) to the Retrieval of feedback noise unit (here to the Delay DE(z) unit).
  • FIG. 4b The embodiment of a listening device according to the invention shown in FIG. 4b is largely identical to the one shown in FIG. 4a .
  • the embodiment of FIG. 4b comprises an Inv-sensitivity function estimation block comprising an adaptive filter with an algorithm part S filter estimation and a variable filter part S(z,n) getting its filter coefficient updates from the S filter estimation part.
  • This filter update may be achieved through classical methods such as NLMS.
  • the FIR filter S(z,n) is an estimate of the so-called inverse sensitivity function.
  • the sensitivity function concept in closed-loop identification (see e.g.
  • FIG. 4 illustrates as described above a combination of noise retrieval based on long term prediction (Method I) with noise generation based on the generation of masked noise (Method A).
  • Noise retrieval method I may, however, be combined with any other noise generation method, alone or in combination with other noise generation methods.
  • Method I proposed above uses far-past samples of the error signal e(n) to predict the current sample of e(n), and in this way reduce signal components in the error signal estimate es(n) which are not due to the introduced/intrinsic noise.
  • this framework is not dependent of which signal samples are used to predict the current error signal sample e(n), as long as the signal samples used are uncorrelated with the introduced/intrinsic noise and do correlate to some extent with the current error signal sample.
  • signal samples from another microphone e.g. from a contra-lateral microphone to predict the components of the error signal e(n), which do not originate from the introduced/intrinsic noise us(n). The setup is shown in FIG.
  • FIG. 5 shows a noise based DFC system using a signal y c (n) from another microphone (i.e. e.g. a signal from an external sensor, e.g. a contra-lateral listening device located at another ear than the current one) for retrieving the signal components in e(n) originating from us(n).
  • the signal y c (n) is a processed version of an additional microphone signal (cf. block Y), e.g.
  • a feedback corrected microphone signal as received via a connection to another device (cf. indication Wired or wireless transmission).
  • the LTP error filter D(z) of Method I (cf. FIG. 4 ) has been replaced by another FIR filter structure (implemented in Binaural retrieval of feedback noise block in FIG.
  • this filter is identical to that of the predictor of D(z,n) of method I, namely to predict samples of the error signal e(n) in order to eliminate signal components NOT related to the probe signal. Specifically, the filter coefficients e p are found so as to minimize E[es(n) 2 ]. However, in contrast to the predictor of D(z,n), the predictor LB(z,n) bases the prediction, not on e(n), but on samples from a signal y c (n) from another (e.g. a contra-lateral) microphone.
  • the introduced/intrinsic noise should preferably have properties P1-P3 (as outlined in the section on generation of masked noise (Method A) above), and in addition preferably: P6)
  • the introduced/intrinsic noise us(n) is uncorrelated with the contra-lateral microphone signal y c (n) , i.e., Eus(n) ⁇ y c (n+k) ⁇ 0 for all k .
  • the proposed filter structure is implemented in Binaural retrieval of feedback noise block by units Delay DB(z), LB Filter Estimation, LB(z,n), and SUM '+'.
  • the Delay DB(z) unit receives (feedback corrected) input signal e(n) as an input and provides a delayed output ed(n) which is connected to SUM unit '+'.
  • the output of the variable filter part LB(z,n) is subtracted from the output signal ed(n) of the Delay DB(z) unit in SUM unit '+'.
  • the output of the filter structure of the Binaural retrieval of feedback noise block is the signal es(n) representing the noise-like part of the (feedback corrected) input signal e(n).
  • This signal (es(n)) is connected to the variable filter part LB filter estimation of the filter structure as well as to the Fh filter estimation part of the FBC-filter and in the latter used in the estimate of filter coefficients for estimating the feedback signal v(n) provided as vh(n) by variable FBC-filter part Fh(z,n) .
  • the LB filter estimation part of the filter structure is electrically connected to a Control unit.
  • the other input to the Fh filter estimation unit is the signal usd(n) (an appropriately delayed version of us(n) delayed in Delay DB(z) unit, equal to the other delay unit of the Binaural retrieval of feedback noise block).
  • Signal us(n) is a masked noise signal generated by Masked probe noise unit (cf. FIG.
  • shaping filter unit M(z,n) which is estimated by Noise shape and level unit based on input y(n) from the forward path unit G(z,n) .
  • the masked noise us(n) is provided by the shaping filter unit M(z,n) based on a white noise sequence input w(n) and filter coefficients as determined by the Noise shape and level unit based on a model of the human auditory system.
  • a Control unit is in one- or two-way communication with the Noise shape and level unit and the LB- and Fh- filter estimation units and the forward path gain unit G(z,n) .
  • the masked noise us(n) is added to the output y(n) from the forward path unit G(z,n) in SUM unit '+', the sum providing output signal u(n) to the receiver.
  • the output signal u(n) is connected to the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • the electrical equivalent F(z,n) of the leakage feedback from output to input transducer resulting in input signal v(n) is added to a target signal x(n) in SUM unit '+' representing the microphone.
  • the feedback estimation Fh(z,n) (variable filter part of an adaptive FBC filter) resulting in feedback signal estimate vh(n) is subtracted from the combined input signal x(n) + v(n) in SUM unit '+' whose output, the feedback corrected input signal e(n), is connected to the forward path gain unit G(z,n) and to the Binaural retrieval of feedback noise unit, here specifically to the Delay DB(z) unit.
  • the Binaural retrieval of feedback noise unit is in FIG. 5 represented by units enclosed by the dotted polygon, i.e.
  • Delay DB(z) for delaying masked noise signal us(n) to adapt it to the delay of es(n) before entering the Fh filter estimation unit.
  • the goal of the proposed filter structure is similar to that of D(z,n) of method I and the coefficients of the proposed filter structure can be estimated and updated in a similar fashion, using e.g. NLMS.
  • D(z,n) is dependent on samples of the microphone signal only (in fact, in the embodiment of FIG. 4a , D(z,n) is derived from the feedback compensated signal, e(n))
  • the proposed filter structure is dependent on the spatial configuration of sound sources.
  • LB(z,n) aims at representing the transfer function from one ear to the other (in case of using a signal originating from a microphone of a contra-lateral device), which is related to head related transfer functions HRTF (in the case of a single point source in the free field, this relation is particularly simple), which in turn are functions of the direction-of-arrival of the sound source.
  • HRTF head related transfer functions
  • D(z,n) is dependent on far-past samples of the error signal
  • FIG. 5 illustrates as described above a combination of noise retrieval method II based on binaural prediction with noise generation method A based on masked noise generation.
  • Noise retrieval method II may, however, be combined with any other noise generation methods, alone or in combination.
  • the method requires dual, e.g. contra-lateral, listening devices or another microphone signal from the same listening device or from another device, e.g. from a communication device, e.g. from an audio selection device.
  • combinations of one or more of the noise generation methods A, and B with one or more of the noise retrieval methods I, II and C can advantageously be implemented using at least one algorithm from each class.
  • FIG. 6a shows a model for an embodiment of a listening device according to the invention, wherein noise generation method A based on masked noise is combined with noise retrieval method I based on long term prediction filtering as well as with noise retrieval method II based on binaural prediction filtering.
  • masked noise us(n) (Method A, cf. above) is inserted in the output part of the forward path by block Masked probe noise and used as a first input to the algorithm part (Fh filter estimation) of the adaptive FBC-filter for estimating the feedback path.
  • the noise in the feedback corrected input signal e(n) originating from the inserted masked noise is retrieved in enhancement unit Retrieval of feedback noise using long term prediction filtering (Method I, filter D(z,n), cf. above) and noise from an alternative (possibly processed) microphone signal yc(n) (e.g. from a contra lateral device) is retrieved in enhancement unit Binaural retrieval of feedback noise using binaural prediction filtering (Method II, cf. above).
  • the combined noise signal es(n) is used as a second input to the algorithm part of the adaptive FBC-filter. Appropriate delays are inserted to 'align' the samples of the different signals.
  • Appropriate delays are inserted to 'align' the samples of the different signals.
  • the output signal y(n) of the forward path gain unit G(z,n) is connected to a masked noise generator (cf. FIG. 2a and the discussion above) comprising Noise shape and level unit (controlled by a Control unit) for estimating time-varying shaping filter M(z,n), which filters white noise sequence w(n) and provides as an output the masked noise signal us(n), which is added to the output signal y(n) of the forward path gain unit in SUM unit '+' to provide output signal u(n) , which is connected to the receiver.
  • the masked noise signal us(n) is delayed in delay unit Delay DB(z) providing output usd(n) which is connected to the Fh filter estimation unit.
  • the purpose of the delay of us(n) is to align the noise-signal samples of the two input signals (usd(n) and es(n)) to the Fh filter estimation unit for generating update filter coefficients to the variable filter part Fh(z,n) of the FBC-filter for estimating the feedback signal v(n).
  • the other input es(n) of the Fh filter estimation unit is generated by an enhancement unit implementing a combination of noise retrieval based on long term prediction filtering (Method I) and binaural prediction filtering (Method II).
  • the processing of the signal on the input side in FIG. 6a is a combination of the two retrieval techniques considered separately above: long term prediction (LTP) filtering (cf. block Retrieval of feedback noise) and binaural prediction filtering (cf. block Binaural retrieval of feedback noise).
  • LTP long term prediction
  • LE1 filter estimation and LE1(z,n) form the LTP filter considered above.
  • the blocks have been described in section Noise retrieval based on long term prediction (method I above).
  • the output of this filter, ex(n) consists ideally of signal components with a correlation time no longer than N 2 .
  • ex(n) consists of "noise-like" components, some originating from the inserted noise (these are the components of interest in this context) and some intrinsically present in the input signal (these are interference components in the given context).
  • the purpose of the binaural retrieval filter is to reject these interference components, such that, ideally, the signal es(n) contains the noise-like components originating from the introduced noise.
  • the outputs of the Retrieval of feedback noise block are a first signal ex(n) comprising the noise-like parts of the feedback corrected input signal e(n) and a second signal ycx(n) comprising the alternative microphone signal, which has been filtered in a copy of the LTP filter ( DE1(z), LE1(z,n))
  • These signals are connected to the Binaural retrieval of feedback noise block, the second signal ycx(n) to the algorithm and variable filter parts of the adaptive filter ( LB filter estimation and LB(z,n), respectively) and the first signal ex(n) to delay unit Delay DB(z).
  • the output of the variable filter part LB(z,n) is subtracted from the output of Delay DB(z) in SUM unit '+'.
  • This output es(n) of the Binaural retrieval of feedback noise block represents the combined retrieved noise and is connected to the (internal) LB filter estimation unit (and used in the estimate of the variable filter part LB(z,n)) as well as to the Fh filter estimation unit and used for updating the variable filter part Fh(z,n) of the adaptive feedback cancellation filter.
  • a Control unit is in one- or two-way communication with the Noise shape and level unit and the LB-, LE- and Fh- Filter Estimation units and the forward path gain unit G(z,n).
  • the output signal u(n) is connected to the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • the electrical equivalent F(z,n) of the leakage feedback from output to input transducer resulting in input signal v(n) is added to a target signal x(n) in SUM unit '+' representing the microphone.
  • the feedback signal estimate vh(n) resulting from the feedback estimation Fh(z,n) is subtracted from the combined input x(n) + v(n) in SUM unit '+' whose output, the feedback corrected input signal e(n), is connected to the forward path gain unit G(z,n) and to the Retrieval of feedback noise block (here specifically to the Delay DE1(z) unit).
  • the Retrieval of feedback noise block is in FIG. 6a represented by units enclosed by the dotted rectangle, i.e. including units implementing filter D(z,n) and the update LE1 filter estimation unit as outlined above AND delay unit DE2(z) and variable filter part LE2(z,n) for delaying and filtering alternative microphone signal yc(n) before it enters the Binaural retrieval of feedback noise block.
  • processing on the input side includes that the noise in the feedback corrected input signal e(n) originating from the inserted noise on the output side is retrieved in enhancement unit Retrieval of feedback noise using long term prediction filtering (Method I, filter D(z,n), cf. above) and noise from an alternative microphone signal (e.g. from a contra lateral device, e.g. processed in processing unit Y) is retrieved in enhancement unit Binaural retrieval of feedback noise using binaural prediction filtering (Method II, cf. above). The resulting noise signal es(n) is used as a second input to the algorithm part of the adaptive FBC-filter. Appropriate delays are inserted to 'align' the samples of the different signals. This is largely as shown and described in connection with FIG. 6a above.
  • the output signal u(n) is connected to the variable filter part Fh(z,n) of the adaptive FBC-filter.
  • the electrical equivalent F(z,n) of the leakage feedback from output to input transducer resulting in input signal v(n) is added to a target signal x(n) in SUM unit '+' representing the microphone.
  • the feedback signal estimate vh(n) resulting from the feedback estimation Fh(z,n) is subtracted from the combined input x(n) + v(n) in SUM unit '+' whose output, the feedback corrected input signal e(n), is connected to the forward path gain unit G(z,n) and to the Retrieval of feedback noise block.
  • the term listening device has been used to exemplify embodiments of the present invention.
  • the term audio processing system or audio processing device may likewise be used.

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Claims (15)

  1. Système de traitement audio pour traiter un son d'entrée comprenant un signal cible (x(n)) en un son de sortie, le système de traitement audio comprenant
    • un transducteur d'entrée comprenant un microphone pour convertir un son d'entrée en un signal d'entrée électrique et définir un côté d'entrée,
    • un transducteur de sortie pour convertir un signal de sortie électrique traité en un son de sortie et défini un côté sortie,
    • un chemin aller étant défini entre le transducteur d'entrée et le transducteur de sortie, et comprenant une unité de traitement de signal (G(z,n)) adaptée pour traiter un signal d'entrée (e(n)) provenant du signal d'entrée électrique et pour fournir un signal de sortie traité (u(n), y(n)), le signal de sortie électrique traité étant dérivé du signal de sortie traité,
    • une boucle de rétroaction électrique allant du côté sortie vers le côté entrée comprenant o une unité d'estimation de chemin de rétroaction (Algorithme, Fh(z,n)) pour estimer une fonction de transfert de rétroaction acoustique (F(z,n)) du transducteur de sortie au transducteur d'entrée, ladite unité d'estimation de chemin de rétroaction comprenant un filtre adaptatif comprenant une partie filtre variable (Fh(z,n)) et une partie algorithme (Algorithme) pour mettre à jour les coefficients de filtre de la partie filtre variable, et
    ∘ une unité d'amélioration (Amélioration ; Eh_e, Eh_u ; Enh_e, Enh_u) pour extraire les caractéristiques d'un signal électrique du chemin aller et fournir une sortie d'estimation de signal de bruit (es(n)), ladite unité d'amélioration comprenant un deuxième filtre adaptatif (C(z,n)) ; et
    • un générateur de signal de sonde (Signal de sonde) pour générer un signal de sonde (us(n)) contribuant à l'estimation de la fonction de transfert de rétroaction (F(z,n)), le générateur de signal de sonde étant adapté pour assurer que le signal de sonde possède des caractéristiques prédéfinies,
    ladite unité d'amélioration (Amélioration ; Eh_e, Eh_u ; Enh_e, Enh_u) étant adaptée pour fournir ladite sortie d'estimation de signal de bruit (es(n)) sur la base desdites caractéristiques prédéfinies du signal de sonde (us(n)) ; et
    ladite partie d'algorithme (Algorithme) du filtre adaptatif de l'unité d'estimation de chemin de rétroaction étant adaptée pour baser la mise à jour au moins en partie sur ladite sortie d'estimation de signal de bruit (es(n)) de l'unité d'amélioration dans l'estimation de la fonction de transfert de rétroaction acoustique,
    CARACTERISÉ EN CE QUE la partie algorithme du filtre adaptatif de l'unité d'estimation de chemin de rétroaction comprend un bloc de commande de longueur de pas pour commander une longueur de pas de la partie algorithme dans une zone de fréquence donnée et ledit bloc de commande de longueur de pas recevant une entrée de commande en provenance du générateur de signal de sonde.
  2. Système de traitement audio selon la revendication 1, lesdites caractéristiques du signal électrique du chemin aller étant sélectionnées dans le groupe comprenant les caractéristiques de modulation, la périodicité, les parties de type bruit et les combinaisons de celles-ci.
  3. Système de traitement audio selon la revendication 1 ou 2, ladite unité d'amélioration étant adaptée pour récupérer des composantes de signal de type bruit intrinsèques dans le signal électrique du chemin aller, lesdites composantes de signal de type bruit intrinsèques formant une partie du signal cible (x(n)).
  4. Système de traitement audio selon l'une quelconque des revendications 1 à 3, ledit générateur de signal de sonde étant adapté pour fournir un signal de sonde sur la base d'un bruit ajouté masqué.
  5. Système de traitement audio selon la revendication 4, ledit générateur de signal de sonde comprenant un troisième filtre adaptatif pour filtrer une séquence d'entrée de bruit blanc w, la sortie d'une partie variable (M) du troisième filtre adaptatif formant le signal de sonde, et la partie variable (M) du troisième filtre adaptatif étant mis à jour sur la base d'un signal provenant du chemin aller par une partie algorithme comprenant un modèle du système auditif humain.
  6. Système de traitement audio selon l'une quelconque des revendications 1 à 5, ledit générateur de signal de sonde étant adapté pour fournir un signal de sonde sur la base de la substitution de bruit perceptif (PNS).
  7. Système de traitement audio selon l'une quelconque des revendications 1 à 6, ladite unité d'amélioration étant adaptée pour baser la sortie d'estimation de signal de bruit sur ledit deuxième filtre adaptatif, par exemple un filtre de prédiction à long terme (LTP) D(z,n) adapté pour filtrer un signal d'entrée corrigé par rétroaction sur le côté d'entrée du chemin aller pour fournir la sortie d'estimation de signal de bruit comprenant des composantes de signal de type bruit dudit signal d'entrée corrigé par rétroaction.
  8. Système de traitement audio selon l'une quelconque des revendications 1 à 7, ladite unité d'amélioration étant adaptée pour fournir la sortie d'estimation de signal de bruit sur la base d'un filtrage de prédiction binaural, un filtre de récupération de bruit adaptatif (E) étant adapté pour filtrer un signal (yc ) provenant d'un autre microphone, par exemple provenant du côté d'entrée du chemin avant d'un dispositif d'écoute contra-latéral.
  9. Système de traitement audio selon la revendication 8, ledit filtre adaptatif de récupération de bruit (E) possédant une caractéristique de filtre variant dans le temps décrite par l'équation aux différences e s n = e n − N 3 − ∑ p = 0 P 3 e p y c n − p ,
    Figure imgb0016
     où e(n) est un signal d'entrée corrigé par rétroaction du côté d'entrée à l'instant n, p représente un indice de coefficient de filtre, et où yc(n) représente des échantillons provenant de l'autre microphone, par exemple un capteur externe, et LB z n = ∑ p = 0 P 3 e p z − p
    Figure imgb0017
     représente une partie de filtre variable, où e p sont les coefficients de filtre adaptés pour minimiser une mesure d'écart statistique de es(n) et où N3 est un retard d'échantillons, et P3 est l'ordre du filtre LB(z,n).
  10. Système de traitement audio selon l'une quelconque des revendications 1 à 9, comprenant ladite unité d'amélioration comprenant une première unité d'amélioration du côté d'entrée et une deuxième unité d'amélioration du côté sortie, et ladite première unité d'amélioration située du côté d'entrée étant un unité d'amélioration maître et ladite deuxième unité d'amélioration située du côté sortie étant une unité d'amélioration esclave, chaque unité d'amélioration étant électriquement raccordée à l'unité d'estimation de rétroaction, ladite unité d'amélioration esclave étant adaptée pour fournir la même fonction de transfert que l'unité d'amélioration maître.
  11. Système de traitement audio selon la revendication 10, ladite unité d'amélioration du côté d'entrée étant en communication avec le générateur de signal de sonde concernant les informations des caractéristiques du signal de sonde.
  12. Système de traitement audio selon l'une quelconque des revendications 1 à 11, comprenant une prothèse auditive.
  13. Procédé d'estimation d'une fonction de transfert de rétroaction (F(z,n)) dans un système de traitement audio comprenant un système d'estimation de rétroaction pour estimer la rétroaction acoustique, le système de traitement audio comprenant
    • un chemin aller entre un transducteur d'entrée comprenant un microphone pour convertir un son d'entrée comprenant un signal cible (x(n)) en un signal d'entrée électrique et définissant un côté d'entrée et un transducteur de sortie pour convertir un signal de sortie électrique traité en une sortie son et définissant un côté de sortie, et comprenant une unité de traitement de signal (G(z,n) adaptée pour traiter un signal d'entrée (e(n)) provenant du signal d'entrée électrique et pour fournir un signal de sortie traité (u(n), y(n), u) le signal de sortie électrique traité étant dérivé du signal de sortie traité,
    • une boucle de rétroaction électrique allant du côté sortie au côté entrée comprenant une unité d'estimation de chemin de rétroaction (Algorithme, Fh(z,n)) pour estimer la fonction de transfert de rétroaction (F(z,n)) du transducteur de sortie au transducteur d'entrée, ladite unité d'estimation de chemin de rétroaction comprenant un filtre adaptatif (Algorithme, Fh(z,n)) comprenant une partie filtre variable (Fh(z,n)) et une partie algorithme (Algorithme) pour mettre à jour les coefficients de filtre de la partie filtre variable,
    le procédé comprenant
    • la génération par un générateur de signal de sonde d'un signal de sonde (us(n)) contribuant à l'estimation de la fonction de transfert de rétroaction, le signal de sonde possédant des caractéristiques prédéfinies ;
    • l'extraction des caractéristiques d'un signal électrique du chemin aller et la fourniture d'une sortie d'estimation de signal de bruit ;
    • de manière adaptative (C(z,n)) la fourniture de ladite sortie d'estimation de signal de bruit (es(n)) sur la base desdites caractéristiques prédéfinies du signal de sonde (us(n)) ;
    • l'adaptation de la partie algorithme (Algorithme) de l'unité d'estimation de chemin de rétroaction pour baser la mise à jour au moins en partie sur ladite sortie d'estimation de signal de bruit (es(n)) dans l'estimation de la fonction de transfert de rétroaction (F(z,n)) ; et
    CARACTÉRISÉ EN CE QUE le procédé comprend en outre
    • la commande d'une longueur de pas de la partie algorithme du filtre adaptatif de l'unité d'estimation de rétroaction dans une zone de fréquence donnée et la réception d'une entrée de commande en provenance du générateur de signaux de sonde.
  14. Support tangible lisible par ordinateur stockant un programme informatique comprenant des moyens de code de programme pour amener un système de traitement de données à effectuer les étapes du procédé selon la revendication 13, lorsque ledit programme informatique est exécuté sur le système de traitement de données.
  15. Utilisation d'un système de traitement audio selon l'une quelconque des revendications 1 à 12 dans un dispositif de communication ou dans un dispositif d'écoute ou dans un système de distribution audio ou en relation avec une commande de bruit active.
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PCT/EP2009/053920 WO2010112073A1 (fr) 2009-04-02 2009-04-02 Annulation adaptative d'échos sur des caractéristiques introduites ou intrinsèques, et récupération correspondante
US24567909P 2009-09-25 2009-09-25
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