EP0948237B1 - Method for noise suppression in a microphone signal - Google Patents
Method for noise suppression in a microphone signal Download PDFInfo
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- EP0948237B1 EP0948237B1 EP99106123A EP99106123A EP0948237B1 EP 0948237 B1 EP0948237 B1 EP 0948237B1 EP 99106123 A EP99106123 A EP 99106123A EP 99106123 A EP99106123 A EP 99106123A EP 0948237 B1 EP0948237 B1 EP 0948237B1
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Classifications
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
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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
- H04R3/007—Protection circuits for transducers
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
- G10L21/0216—Noise filtering characterised by the method used for estimating noise
- G10L2021/02168—Noise filtering characterised by the method used for estimating noise the estimation exclusively taking place during speech pauses
Definitions
- the invention relates to a method for noise immunity of a microphone signal.
- a particular situation is often given in vehicles in that a playback device such as a radio, a cassette or CD player via a loudspeaker Sound environment generates, which superimposed as an interference signal recorded by a microphone voice signal, for example, for speech recognition or telephone transmission.
- a microphone voice signal for example, for speech recognition or telephone transmission.
- the microphone signal must be freed as much as possible of interference signal components.
- the interference signal emanating from a source of interference not only reaches the microphone on the shortest direct path, but also occurs via numerous reflections as a superposition of a plurality of echoes with different transit times in the microphone signal.
- the entire effect of the interference signal from the source of interference on the microphone signal can be described by an a priori unknown transfer function of the room, such as the passenger compartment of a motor vehicle.
- the transfer function changes depending on the occupation of the vehicle and the position of the individual persons.
- a compensation signal can be generated which, by subtraction from the microphone signal, delivers a signal freed from the interference signal, for example a pure speech signal.
- said replica represents a more or less good approximation to the unknown transfer function and the disturbance can not be completely eliminated.
- EP 0 250 048 A1 discloses a digital block adaptable filter which is adapted in the frequency domain.
- Object of the present invention is to provide a method for noise immunity of a microphone signal that has good characteristics hinsichltich the suppression with reasonable signal processing overhead.
- the compensation of the Störsignalanteils in the microphone signal is made by means of a generated from the reference signal on the replica of the transfer function compensation signal in the frequency domain, so that the microphone signal, compensation signal and output signal in the frequency range, i. in the form of spectra.
- the signal processing in this process step in the frequency domain requires a spectral transformation of the microphone signal, but takes into account that the reproduction of the transfer function in the frequency range is more advantageous and provides for a beneficial subsequent additional noise reduction of the output signal, which is typically also made in the frequency domain, already a particularly suitable Signal form ready.
- an advantageous development of the invention provides for a division of the replica filter into a plurality of sub-filters at time-shifted segments of the segmented reference signal whose coefficient update can be staggered over time, whereby the signal processing effort can be minimized.
- the division of the replica filter into a plurality of sub-filters and the noise removal on the basis of a filter setting obtained in a speech break are independent of the Störsignalkompensation in the frequency domain independently for the noise immunity of a microphone signal feasible and advantageous.
- Fig. 1 represents the principle of a device for (single-channel) radio signal compensation.
- the acoustic signal emitted by the loudspeaker reaches the microphone of the speech input system directly, but also via numerous reflections in the vehicle interior.
- the transmission path G thus represents a transversal filter with a weighted sum of time-delayed echoes
- the loudspeaker signal x is filtered by the a priori unknown transfer function G of the vehicle interior.
- the result is the noise component r, which adds to the speech signal s to the microphone signal y.
- an estimate r ⁇ is generated from the loudspeaker signal x by means of the filter simulation H.
- the speech signal may still contain disturbances in the form of, for example, engine noise or external noise, but which are not explicitly dealt with in this context.
- the H is an adaptive filter and works according to a standard method known in the literature, the LMS algorithm (Least Mean Squares).
- the error signal E is still required in order to accomplish the coefficient adaptation in the filter H.
- the output signal s ⁇ is fed to the determination of the filter coefficients.
- Fig. 2a shows in another representation again the arrangement of Fig. 1 as a radio signal compensation.
- the adaptive system H can be realized, for example, in the time domain as an FIR filter (finite-impulse-response filter). For large impulse response lengths, as they often occur in practice, however, this requires a very high computational effort.
- FIR filter finite-impulse-response filter
- FLMS frequency domain
- Fig. 2b shows a block diagram of the FLMS algorithm.
- F is a spectral transformation FFT of a time signal into the frequency domain and F -1 is the inverse IFFT.
- the processing steps referred to as projections P1, P2 and P3 are used for the correct segmentation of the data by the block use with the FFT or IFFT and will be explained in more detail later.
- the operation of the filter is to multiply the reference spectrum X by the filter coefficient vector H.
- the spectrum of the filter output R ⁇ is transformed back into the time domain via F -1 .
- the signal r ⁇ is available.
- the projection P1 which is particularly complicated here with two spectral transformations, calculates from H 'the coefficient vector H required for the filtering.
- the spectrum S 1 of the output signal evaluated with P 3 is calculated to calculate the correction vector ⁇ H' s + r - r ⁇ needed.
- FIG. 3 A detailed block diagram of the in Fig. 2b shown FLMS algorithm Fig. 3 ,
- the samples of a signal and the nodes of the FFT are commonly referred to as samples. All spectral transforms and their inverses are to be segmented as 256-point FFTs, each overlapping 128 samples.
- the output signal s ⁇ in the time domain consists of 128 sample blocks. It arises from the difference of the second block halves (thus in each case the samples 129 to 256) of microphone signal and filtered compensation signal r ⁇ .
- the projection P1 which requires 2 FFTs and converts the vector H 'into the vector H, is elaborate.
- the first half (samples 1 to 128) is cut out of the complex 256-point result vector of the inverse transformation from the frequency to the time domain (IFFT) and the second half (samples 129 to 256) is set to zero.
- the transformation into the frequency domain takes place again by means of FFT.
- Simple is the projection P2. It consists of the above-described fragmentation of the last 128 samples, resulting in overlapping 256-sample blocks again resulting in non-overlapping 128-sample blocks.
- the projection P3 is also very simple, which, in turn, provides overlapping 256-sample blocks from non-overlapping 128-sample blocks of the output signal by preprogramming 128 null values.
- the adaptation of the filter coefficients H ' L + 1 for a cycle L + 1 consists of the addition of a renewal vector ⁇ H' L to the old coefficient vector H ' L.
- the operation of the LMS algorithm is significantly influenced by the adaptation constant ⁇ and the smoothing constant ⁇ . Latches in recursion loops are labeled Sp.
- the previously described arrangement of the FLMS algorithm allows filter emulations with a maximum impulse response length of half an FFT length, in the example case 128 samples. If longer impulse responses are to be compensated, the already known FLMS algorithm for a sub-filter ( Fig. 4a ) to n subfilters.
- the im Fig. 4a Block B with the input signals X and S ⁇ and the compensation spectrum R ⁇ as the output is denoted by the Fig. 4b to replace the extension shown.
- the spectrum X of the reference signal is delayed by latches D by 1 or 2 block lengths, and the instantaneous X1 and the two delayed spectra X2, X3 are separately multiplied by coefficient vectors H1, H2, H3 determined separately in an extended projection P1.
- the formation of the coefficient vectors is analogous to the case of only a sub-filter, wherein in K1, K2, K3 respectively the associated reference spectrum is linked to the spectrum S ⁇ of the output signal.
- the effort is considerably increased mainly by the tripling of the projection P1. Additional storage space is required to provide the spectra of the reference signal X which is older by 1 or 2 block lengths.
- Fig. 6 provides a more detailed block diagram of the frequency domain output FLMS algorithm and again allows comparison with Fig. 3 (Time domain output).
- the filter adaptation consisting of smoothing of the spectral power, power normalization and coefficient renewal has remained unchanged. What is new are the FFT in the microphone channel, the difference formation YR ⁇ in the frequency domain instead of in the time domain for output formation, and finally the newly defined projection P4, which differs from the projection P1 only by the complementary time domain window.
- Fig. 7 Shown is the FLMS algorithm with 3 sub-filters (384 sample impulse response), which provides sufficient suppression of the radio signal in the microphone channel of the speech input system.
- the projections P1 and P4 are shown simplified. It's already out Fig. 4b known additional effort in the form of the memory D and the tripling of the projection P1 visible.
- the filter output is now practically 3 times the smoothed spectral power is taken into account after the inverse by multiplying by the constant 6 ⁇ .
- the filter adaptation is now carried out separately for the 3 coefficient vectors of the 3 sub-filters.
- FIG. 9 An example Z0 for the operation of the invention according to Fig. 7 shows Fig. 9 ,
- Microphone signal Y resulted from convolution of this noise signal with a likewise constructed 384 sample impulse response and the addition of an extremely weak speech signal. While listening to this in Fig. 9 recorded above signal y, the 10 spoken numbers are barely visible in the colored (because filtered) noise.
- the output signal of the estimator which was transformed back into the time domain, is freed after a transient of about 1 second (12,000 samples) very effective the speech input from noise and provides an undistorted but slightly reverberated speech signal S ⁇ ( Fig. 9 below).
- the resulting 3 * 128 sample impulse response or the associated filter transfer function can be calculated at any time. So shows Fig. 10 above is the 384 sample impulse response as it appears at the very end of the scene, that is, after the digit "0" was spoken. It is a very accurate image of the impulse response that was used to convolve with white Gaussian noise and thus to synthetically generate the signal micro.
- White noise as the reference input signal and filtered "colored" noise as the microphone input signal are the simplest case in terms of the task of finding a replica of this filter. Since the reference signal contains all frequency components by definition, the filter adaptation succeeds fastest here.
- the additional additive speech input in the microphone input signal - ie the actual useful signal of the speech input system - represents a disturbance for the (F) LMS algorithm, which hinders the correct adaptation of the filter coefficients. In other words, the system is only able to correctly reproduce the room acoustics of the vehicle interior (distance between radio loudspeaker and microphone) during pauses in speech thereby causing a compensation of the radio playback.
- Fig. 9 This works very well, since the microphone input consists essentially of noise and only a very small part of speech input.
- the reference signal radio picked up from the radio speaker terminals and the signal micro recorded from the microphone of the voice input system came from the scene Z1.
- This microphone signal is in Fig. 11 shown above, consists of 100000 samples and thus has a sampling time of 12 kHz a time duration of about 8.3 seconds. It is fluent and relatively fast spoken language of a vehicle occupant seated in the rear right of the car while at the same time sounding at normal volume from the car radio speaker.
- the hearing test results in a clear elaboration of the language portion or a notable especially in the short language breaks music suppression.
- a suitable feature is used together with a threshold as an indicator for a voice input. If the characteristic falls below the threshold, this is an indication of missing speech input. In this case, as already stated above, a largely undisturbed filter adaptation can take place.
- the filter coefficient set is used, which was stored immediately before the threshold was exceeded, ie at the end of the preceding speech break.
- these stored coefficients H10, H20, H30 provide significantly better radio signal compensation than the current coefficients H, H2, H3, which constantly change under the disturbing influence of the voice input.
- Fig. 8 represents an embodiment with a further improved FLMS processing with 3 sub-filters.
- Fig. 7 existing current filter coefficient vectors H1, H2, H3, which were needed to form the continuously adopted output signal yR, there now exists an additional output signal (y-Ro) formed using stored coefficients H10, H20, H30.
- the current coefficient sets H1, H2, H3 represent a useful compensation filter in the frequency domain only in the absence of speech input in the steady state, however, provide insufficient filter characteristics in voice input, because the adaptation process in the control loop is constantly disturbed.
- the outputs (y-Ro) and (y-Ra) are identical. Inserting voice inputs cause the 3 switches, whereby the last located in the memories M1, M2, M3 coefficients H10, H20, H30 are no longer overwritten and remain unchanged. This state, in which the outputs (Y-Ro) and (Y-Ra) differ, is maintained until a speech break is detected again and the switches are closed.
- a smoothing filter for example a 1st order recursive low-pass filter with the input feat, provides at its output the smoothed speech pause feature fea which, after comparison with a threshold value th, controls the coefficients transfer switches.
- the measured 384-sample impulse response with associated magnitude transfer function is in Fig. 15 represented as current impulse response (a) or current transfer function (b).
- an impulse response (c) and a high-quality transfer function (d) can be calculated from the stored coefficients H10, H20, H30.
- the impulse response from the stored coefficients has the typical zero samples at the beginning, which are caused by the transit time of the direct sound from the radio loudspeaker to the speech input microphone. From the dead time of about 40 samples to be read in the example, the distance between loudspeaker and microphone can be determined.
- the complex projection P4 (IFFT, window on the right in the time domain, FFT) can be replaced without noticeable loss of quality by a relatively simple convolution in the frequency domain, thus saving 2 FFTs.
- IFFT IFFT, window on the right in the time domain, FFT
- the "right-sided" 128-sample rectangle window in the time domain ( Fig. 16a ) in the ideal projection replaced by a 128 sample Hamming window ( Fig. 16b ).
- Fig. 16b the "right-sided" 128-sample rectangle window in the time domain in the ideal projection replaced by a 128 sample Hamming window ( Fig. 16b ).
- Fig. 17 In the case of the rectangular window, the real part of the spectrum consists of a single line (DC component), whereas the antisymmetrical part of the imaginary spectrum consists of many slowly decreasing lines with alternating lines Zeroing exists.
- the projection P1 (IFFT - left-sided rectangular window - FFT) can be replaced by a corresponding convolution operation in the frequency domain with the conjugate complex 7-line spectrum.
- IFFT - left-sided rectangular window - FFT IFFT - left-sided rectangular window - FFT
- Fig. 8 cost-effective solutions can be achieved by following the LMS algorithm Fig. 8 the 3 projections P1 need not be processed simultaneously in a 256 sample input data block.
- the 128-sample overlapping input data blocks of length 256 are numbered beginning with "1" at random Fig. 19a outlined. For example, if the input data blocks are modulo-3, the 3 sub-filter projections are not possible in parallel ( Fig.
- the first of these scenes Z2 involves voice input of digits, with the radio loudspeaker emitting near-white noise at a relatively high volume.
- the corresponding 100000 sample microphone signal is in Fig. 20 above, the extracted output signal in Fig. 20 shown below.
- a clear noise exemption of the output signal compared to the microphone input is found by interception comparison.
- the time course of the speech pause feature is together with the constant threshold th Fig. 21 pictured above and derived therefrom language pauses or the associated switch positions in Fig. 21 below.
- Fig. 22 in to Fig.
- the first 100000 samples of a measurement scene Z3 with POP music on the radio and fluent to fast spoken language of the person sitting on the right back are in the form of the microphone signal y in Fig. 23 recorded above.
- the radio signal is usefully suppressed ( Fig. 23 below).
- the POP music suppression is effectively maintained, whereby the speech intelligibility here is markedly improved over the microphone signal.
- Fig. 24 After a long linguistic break, there is no longer a threshold underrun because of the subsequent pause-free speech input ( Fig. 24 ). For this reason, the in Fig.
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Abstract
Description
Die Erfindung betrifft ein Verfahren zur Störbefreiung eines Mikrophonsignals.The invention relates to a method for noise immunity of a microphone signal.
Derartige Verfahren gewinnen insbesondere für die Spracheingabe von Kommandos und/oder für Freisprechtelefone zunehmend an Bedeutung, wobei insbesondere die Situation in einem Fahrzeug ein wichtiger Anwendungsfall ist.Such methods are becoming increasingly important, in particular for the voice input of commands and / or for hands-free telephones, with the situation in a vehicle in particular being an important application.
Eine besondere Situation ist in Fahrzeugen häufig dadurch gegeben, daß ein Wiedergabegerät wie z.B. ein Radio, ein Kassetten- oder CD-Abspieler über einen Lautsprecher eine Geräuschumgebung erzeugt, die als Störsignal ein von einem Mikrophon aufgenommenes Sprachsignal, beispielsweise für die Spracherkennung oder Telefonübertragung überlagert. Zur Erkennung von Spracheingaben in einem Spracherkenner oder zur verständlichen Sprachübertragung über Telefon ist das Mikrophonsignal soweit wie möglich von Störsignalanteilen zu befreien.A particular situation is often given in vehicles in that a playback device such as a radio, a cassette or CD player via a loudspeaker Sound environment generates, which superimposed as an interference signal recorded by a microphone voice signal, for example, for speech recognition or telephone transmission. To detect voice input in a voice recognition device or for intelligible voice transmission over the telephone, the microphone signal must be freed as much as possible of interference signal components.
Das von einer Störquelle, insbesondere einem Lautsprecher ausgehende Störsignal gelangt nicht nur auf direktem kürzestem Weg zum Mikrophon, sondern tritt auch noch über zahlreiche Reflexionen als eine Überlagerung einer Mehrzahl von Echos mit verschiedenen Laufzeiten im Mikrophonsignal in Erscheinung. Die gesamte Einwirkung des Störsignals von der Störquelle auf das Mikrophonsignal kann durch eine a priori unbekannte Übertragungsfunktion des Raumes, beispielsweise des Fahrgastraumes eines Kraftfahrzeugs beschrieben werden. Die Übertragungsfunktion ändert sich je nach Besetzung des Fahrzeugs und nach Position der einzelnen Personen. Durch Nachbildung dieser Übertragungsfunktion und Filterung eines Referenzsignals von der Störquelle mit dieser Nachbildung kann ein Kompensationssignal erzeugt werden, welches durch Subtraktion vom Mikrophonsignal ein vom Störsignal befreites Signal, beispielsweise ein reines Sprachsignal liefert. Im Realfall stellt die genannte Nachbildung eine mehr oder minder gute Annäherung an die unbekannte Übertragungsfunktion dar und die Störung kann nicht vollständig beseitigt werden.The interference signal emanating from a source of interference, in particular a loudspeaker, not only reaches the microphone on the shortest direct path, but also occurs via numerous reflections as a superposition of a plurality of echoes with different transit times in the microphone signal. The entire effect of the interference signal from the source of interference on the microphone signal can be described by an a priori unknown transfer function of the room, such as the passenger compartment of a motor vehicle. The transfer function changes depending on the occupation of the vehicle and the position of the individual persons. By replicating this transfer function and filtering a reference signal from the source of interference with this replica, a compensation signal can be generated which, by subtraction from the microphone signal, delivers a signal freed from the interference signal, for example a pure speech signal. In the real case, said replica represents a more or less good approximation to the unknown transfer function and the disturbance can not be completely eliminated.
Aufgabe der vorliegenden Erfindung ist es, ein Verfahren zur Störbefreiung eines Mikrophonsignals anzugeben, daß bei vertretbarem Signalverarbeitungsaufwand gute Eigenschaften hinsichltich der Entstörung aufweist.Object of the present invention is to provide a method for noise immunity of a microphone signal that has good characteristics hinsichltich the suppression with reasonable signal processing overhead.
Die Erfindung ist im Patentanspruch 1 beschrieben. Die Unteransprüche enthalten vorteilhafte Ausgestaltungen und Weiterbildungen der Erfindung.The invention is described in
Wesentlich an dem erfindungsgemäßen Verfahren ist, daß die Kompensation des Störsignalanteils im Mikrophonsignal mittels eines aus dem Referenzsignal über die Nachbildung der Übertragungsfunktion erzeugten Kompensationssignals im Frequenzbereich vorgenommen wird, so daß Mikrophonsignal, Kompensationssignal und Ausgangssignal im Frequenzbereich, d.h. in Form von Spektren vorliegen. Die Signalverarbeitung in diesem Verfahrensschritt im Frequenzbereich erfordert zwar eine spektrale Transformation des Mikrophonsignals, berücksichtigt aber, daß die Nachbildung der Übertragungsfunktion im Frequenzbereich vorteilhafter ist und stellt für eine vorteilhafte nachfolgende zusätzliche Geräuschreduktion des Ausgangssignals, die typischerweise gleichfalls im Frequenzbereich vorgenommen wird, bereits eine besonders geeignete Signalform bereit.It is essential to the inventive method that the compensation of the Störsignalanteils in the microphone signal is made by means of a generated from the reference signal on the replica of the transfer function compensation signal in the frequency domain, so that the microphone signal, compensation signal and output signal in the frequency range, i. in the form of spectra. Although the signal processing in this process step in the frequency domain requires a spectral transformation of the microphone signal, but takes into account that the reproduction of the transfer function in the frequency range is more advantageous and provides for a beneficial subsequent additional noise reduction of the output signal, which is typically also made in the frequency domain, already a particularly suitable Signal form ready.
Durch einfache Näherungen beim Ersatz eines Verarbeitungsschritts mit einem Zeitfenster kann durch Übergang zu einer Faltung im Frequenzbereich eine deutliche Reduzierung des Verarbeitungsaufwands reduziert werden.By simple approximations when replacing a processing step with a time window, a significant reduction in processing overhead can be reduced by transitioning to a convolution in the frequency domain.
Für lange Impulsantworten der Übertragungsfunktion bzw. deren Nachbildung sieht eine vorteilhafte Weiterbildung der Erfindung eine Aufteilung des Nachbildungsfilters in mehrere Teilfilter zu zeitversetzten Segmenten des segmentierten Referenzsignals vor, deren Koeffizienten-Aktualisierung zeitlich gestaffelt sein kann, wodurch der Signalverarbeitungsaufwand gering gehalten werden kann.For long impulse responses of the transfer function or their replica, an advantageous development of the invention provides for a division of the replica filter into a plurality of sub-filters at time-shifted segments of the segmented reference signal whose coefficient update can be staggered over time, whereby the signal processing effort can be minimized.
Als besonders vorteilhaft erweist es sich, die Entstörung eines Sprachsignals auf der Basis einer Einstellung des Nachbildungsfilters, die in einer vorhergehenden Sprachpause gewonnen und gespeichert wurde, vorzunehmen.It proves to be particularly advantageous to suppress the interference of a speech signal on the basis of a setting of the Replica filter that was obtained and stored in a previous speech break.
Die Aufteilung des Nachbildungsfilters in mehrere Teilfilter und die Störbefreiung auf der Basis einer in einer Sprachpause gewonnenen Filtereinstellung sind auch unabhängig von der Störsignalkompensation im Frequenzbereich eigenständig für die Störbefreiung eines Mikrophonsignals realisierbar und vorteilhaft.The division of the replica filter into a plurality of sub-filters and the noise removal on the basis of a filter setting obtained in a speech break are independent of the Störsignalkompensation in the frequency domain independently for the noise immunity of a microphone signal feasible and advantageous.
Die Erfindung ist nachfolgend anhand von bevorzugten Ausführungsbeispielen unter Bezugnahme auf die Abbildungen noch eingehend veranschaulicht. Dabei zeigt:
- Fig. 1
- ein Prinzip der Kompensation eines Radiosignals
- Fig. 2a
- ein Blockschaltbild zu
Fig. 1 - Fig. 2b
- ein Blockschaltbild zur Filternachbildung
- Fig. 3
- ein detailliertes Beispiel zu
Fig. 2b - Fig. 4
- eine Erweiterung auf mehrere Teilfilter
- Fig. 5
- einen Übergang zur Kompensation im Frequenzbereich
- Fig. 6
- ein detailliertes Beispiel zu
Fig. 5b - Fig. 7
- ein Ausführungsbeispiel mit mehreren Teilfiltern
- Fig. 8
- ein Ausführungsbeispiel mit Speicherung der Filtereinstellungen
- Fig. 9
- Signale einer synthetischen Beispielsszene
- Fig. 10
- Impulsantwort und Übertragungsfunktion zu
Fig. 9 - Fig. 11
- Signal einer ersten Meßszene
- Fig. 12
- Impulsantwort und Übertragungsfunktion zu
Fig. 11 - Fig. 13
- das Beispiel nach
Fig. 11 mit Speicherung der Filtereinstellungen - Fig. 14
- eine Sprachpausendetektion zu
Fig. 13 - Fig. 15
- Impulsantworten und Übertragungsfunktionen zu
Fig. 11 undFig. 13 - Fig. 16
- Übergang von einem Zeitfenster zu einer Faltung im Frequenzbereich
- Fig. 17
- ein Rechteck-Zeitfenster mit Linienspektrum
- Fig. 18
- ein Hamming-Zeitfenster mit Linienspektrum
- Fig. 19
- Staffelung von Signalblöcken bei der Filterberechnung
- Fig. 20
- Signale einer zweiten Meßszene
- Fig. 21
- eine Sprachpausendetektion zu
Fig. 20 - Fig. 22
- Impulsantworten und Übertragungsfunktionen zu
Fig. 20 undFig. 21 - Fig. 23
- Signale einer dritten Meßszene
- Fig. 24
- eine Sprachpausendetektion zu
Fig. 23 - Fig. 25
- Impulsantworten und Übertragungsfunktionen zu
Fig. 23 undFig. 24 - Fig. 26
- Signale einer vierten Meßszene
- Fig. 27
- eine Sprachpausendetektion zu
Fig. 26 - Fig. 28
- Impulsantworten und Übertragungsfunktionen zu
Fig. 26 undFig. 27 .
- Fig. 1
- a principle of compensation of a radio signal
- Fig. 2a
- a block diagram to
Fig. 1 - Fig. 2b
- a block diagram of the filter simulation
- Fig. 3
- a detailed example
Fig. 2b - Fig. 4
- an extension to several subfilters
- Fig. 5
- a transition to compensation in the frequency domain
- Fig. 6
- a detailed example
Fig. 5b - Fig. 7
- an embodiment with several sub-filters
- Fig. 8
- an embodiment with storage of the filter settings
- Fig. 9
- Signals of a synthetic example scene
- Fig. 10
- Impulse response and transfer function too
Fig. 9 - Fig. 11
- Signal of a first measurement scene
- Fig. 12
- Impulse response and transfer function too
Fig. 11 - Fig. 13
- the example after
Fig. 11 with storage of the filter settings - Fig. 14
- a speech pause detection too
Fig. 13 - Fig. 15
- Impulse responses and transfer functions too
Fig. 11 andFig. 13 - Fig. 16
- Transition from a time window to a convolution in the frequency domain
- Fig. 17
- a rectangle time window with line spectrum
- Fig. 18
- a Hamming time window with line spectrum
- Fig. 19
- Staggering of signal blocks during filter calculation
- Fig. 20
- Signals of a second measurement scene
- Fig. 21
- a speech pause detection too
Fig. 20 - Fig. 22
- Impulse responses and transfer functions too
Fig. 20 andFig. 21 - Fig. 23
- Signals of a third measurement scene
- Fig. 24
- a speech pause detection too
Fig. 23 - Fig. 25
- Impulse responses and transfer functions too
Fig. 23 andFig. 24 - Fig. 26
- Signals of a fourth measurement scene
- Fig. 27
- a speech pause detection too
Fig. 26 - Fig. 28
- Impulse responses and transfer functions too
Fig. 26 andFig. 27 ,
Das Lautsprechersignal x wird durch die a priori unbekannte Übertragungsfunktion G des Fahrzeuginnenraumes gefiltert. Es entsteht die Störkomponente r, die sich mit dem Sprachsignal s zu dem Mikrophonsignal y addiert. Um die Störkomponente r zu kompensieren, wird mittels der Filternachbildung H ein Schätzwert r^ aus dem Lautsprechersignal x erzeugt. Der Ausgang der Schaltung liefert den Schätzwert für das Sprachsignal:
Dem Sprachsignal s ist also am Ausgang der Schaltung noch das Fehlersignal
H ist ein adaptives Filter und arbeitet nach einem in der Literatur bekannten Standardverfahren, dem LMS-Algorithmus (least mean squares). Neben dem Eingangssignal x wird noch das Fehlersignal E benötigt, um die Koeffizientenadaption im Filter H zu bewerkstelligen. Hierfür ist das Ausgangssignal s^ der Bestimmung der Filterkoeffizienten zugeführt.H is an adaptive filter and works according to a standard method known in the literature, the LMS algorithm (Least Mean Squares). In addition to the input signal x, the error signal E is still required in order to accomplish the coefficient adaptation in the filter H. For this purpose, the output signal s ^ is fed to the determination of the filter coefficients.
Wesentlicher Bestandteil des adaptiven Filters ist die Koeffiiientenadaption im Block K, die im
Ein detailliertes Blockschaltbild des in
Die Arbeitsweise des LMS-Algorithmus wird erheblich von der Adaptionskonstante α und der Glättungskonstante β beeinflußt. Zwischenspeicher in Rekursionsschleifen sind mit Sp bezeichnet.The operation of the LMS algorithm is significantly influenced by the adaptation constant α and the smoothing constant β. Latches in recursion loops are labeled Sp.
Die bisher beschriebene Anordnung des FLMS-Algorithmus erlaubt Filternachbildungen mit einer maximalen Impulsantwortlänge von einer halben FFT-Länge, im Beispielsfall also 128 samples. Sollen längere Impulsantworten kompensiert werden, ist der schon bekannte FLMS-Algorithmus für einen Teilfilter (
Bei der beispielhaft angegebenen Aufgabenstellung der Unterdrückung des Radiosignales bei Spracheingabe im Kfz ist es vorteilhaft die Ausgangsdaten nicht im Zeit- sondern im Frequenzbereich auszugeben, da dadurch eine verbesserte Anpassung an eine nachgeschaltete Geräuschunterdrückung erreicht werden kann. Der bereits vorgestellte FLMS-Algorithmus mit einem Teilfilter benötigt gemäß
- Bei der zeitgleichen Spektralanalyse der Signale x und y ist nur eine einzige 256-Punkte-FFT mit geringem Zusatzaufwand für eine spektrale Separation notwendig. Man erzielt
eine Einsparung von 1 FFT. - Die hier mit P4 gekennzeichnete und neu definierte Projektion ist bis auf das verwendete Zeitfenster formal identisch mit der Projektion P1. Wie später gezeigt wird, läßt sich P4 durch eine relativ einfache Faltungsoperation im Frequenzbereich ersetzten, ohne daß eine merkliche Einbuße an Qualität in Kauf genommen werden muß. Man erzielt
eine Einsparung von 2 FFT's.
- In the simultaneous spectral analysis of the signals x and y, only a single 256-point FFT with little additional effort for a spectral separation is necessary. One achieves a saving of 1 FFT.
- The newly defined projection with P4 is formally identical to the projection P1 except for the time window used. As will be seen later, P4 can be replaced by a relatively simple convolution operation in the frequency domain without the need to sacrifice any appreciable quality. One achieves a saving of 2 FFT's.
Als Vorstufe einer nachfolgend beschriebenen bevorzugten Ausführung betrachte man
Ein Beispiel Z0 für die Wirkungsweise der Erfindung nach
Aus den jeweils 129 samples langen Teilkoeffizientenvektoren H1, H2, H3 der 3 Teilfilter nach Bild7 läßt sich nun zu jedem Zeitpunkt die hieraus resultierende 3*128-sample-Impulsantwort bzw. die zugehörige Filterübertragungsfunktion berechnen. So zeigt
Weißes Rauschen als Referenzeingangssignal und gefiltertes "farbiges" Rauschen als Mikrophoneingangssignal stellen im Sinne der Aufgabenstellung, eine Nachbildung dieses Filters zu finden, den einfachsten Fall dar. Da das Referenzsignal per Definitionen alle Frequenzanteile enthält, gelingt die Filteradaption hier am schnellsten. Die zusätzliche additive Spracheingabe im Mikrophoneingangssignal - also das eigentliche Nutzsignal des Spracheingabesystems - stellt für den (F)LMS-Algorithmus eine Störung dar, welche die korrekte Adaption der Filterkoeffizienten behindert. Anders ausgedrückt: nur in Sprachpausen ist das System dazu in der Lage die Raumakustik des Fahrzeuginnenraums (Strecke Radiolautsprecher zum Mikrophon) richtig nachzubilden und dadurch eine Kompensation der Radiowiedergabe zu bewirken. Im oben demonstrierten Beispiel gemäß
Aus echten Messungen im Fahrzeug hingegen entstammten das an den Radiolautsprecherklemmen abgegriffene Referenzsignal radio und das vom Mikrophon des Spracheingabesystem aufgezeichnete Signal mikro der Szene Z1. Dieses Mikrophonsignal ist in
Die im folgenden anhand von
Als Sprachpausenmerkmal fea hat sich die geglättete Summe aller Absolutwerte der Koeffizientenkorrekturvektoren ΔH1', ΔH2', ΔH3' bewährt (
Die Wirkungsweise des verbesserten FLMS-Algorithmus nach
Wie vorstehend schon angedeutet läßt sich die aufwendige Projektion P4 (IFFT, Fenster rechts im Zeitbereich, FFT) ohne merkliche Einbuße an Qualität durch eine relativ einfache Faltung im Frequenzbereich ersetzten, wodurch 2 FFT's eingespart werden. Dazu betrachte man
Prinzipiell läßt sich natürlich auch die Projektion P1 (IFFT - linksseitiges Rechteckfenster - FFT) ersetzen durch eine entsprechende Faltungsoperation im Frequenzbereich mit dem konjugiert komplexen 7-Linien-Spektrum. Experimente haben jedoch gezeigt, daß Einsparungen an dieser Stelle erkauft werden mit einer deutlichen Verschlechterung des Einschwingverhaltens. Aufwandsgünstige Lösungen lassen sich trotzdem dadurch erzielen, daß in dem LMS-Algorithmus nach
Die Leistungsfähigkeit des FLMS-Algorithmus mit 3 Teilfiltern gemäß Blockschaltung
Die erste dieser Szenen Z2 beinhaltet Spracheingabe von Ziffern, wobei der Radiolautsprecher annähernd weißes Rauschen mit verhältnismäßig hoher Lautstärke abstrahlt. Das zugehörige 100000-sample-Mikrophonsignal ist in
Die ersten 100000 samples einer Meßszene Z3 mit POP-Musik im Radio und flüssig bis schnell gesprochener Sprache der rechts hinten sitzenden Person sind in Form des Mikrophonsignales y in
Die letzte Szene Z4 nach
Claims (10)
- Method of eliminating interference in a microphone signal due to components of a source signal which is present as a reference signal (x) and after passing through a transmission path with a priori unknown transmission function (G), is superimposed on a voice signal (s) as an interference signal (r) in the microphone signal, by adaptive simulation of the interference signal and compensation of the actual and the simulated interference signal in an output signal, wherein the microphone signal is likewise transformed into the frequency domain, the signal compensation occurs in the frequency domain and the output signal present in the frequency domain is linked with the reference signal present in the frequency domain for adaptation of the simulation, wherein for simulation of the interference signal an adaptive filtering function of a simulation filter is applied to the reference signal, characterised in that the occurrence of the voice signal in the microphone signal is detected and when a voice signal occurs the filtering function set before the occurrence of the voice signal is retained in order to form the output signal.
- Method as claimed in Claim 1, wherein the output signal spectrum is transformed into the time domain, the length of the time signal is doubled by placing zeros in front of it, back-transforming it into the frequency domain and is used for simulation of the transmission function.
- Method as claimed in Claim 1, wherein the output signal spectrum is convoluted with the spectrum of a Hamming time window and is used for simulation of the transmission function.
- Method as claimed in Claim 1, wherein the filtering function is predetermined by a coefficient vector with adaptively adjusted coefficients.
- Method as claimed in Claim 1, wherein when the voice signal is detected the adaptive readjustment of a current filtering function is continued in addition to the formation of the output signal.
- Method as claimed in Claim 5, wherein the occurrence of the voice signal is detected from a change in the current filtering function.
- Method as claimed in Claim 6, wherein the change in the current filtering function is smoothed over time for detection of the occurrence of a voice signal.
- Method as claimed in any one of the preceding claims, in which the filtering function is divided into several partial filtering functions for successive segments of a total pulse response from all partial filters and is applied to reference signal spectra during time segments of the segmented reference time signal which are offset in time.
- Method as claimed in Claim 8, wherein the adaptation of the filtering function is carried out in parallel for the partial filters.
- Method as claimed in Claim 9, wherein the adaptation of the filtering function for the individual partial filters is carried out sequentially in time.
Applications Claiming Priority (2)
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DE19814971 | 1998-04-03 | ||
DE19814971A DE19814971A1 (en) | 1998-04-03 | 1998-04-03 | Procedure for the elimination of interference from a microphone signal |
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EP0948237A3 EP0948237A3 (en) | 2006-02-08 |
EP0948237B1 true EP0948237B1 (en) | 2008-06-11 |
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EP99106123A Expired - Lifetime EP0948237B1 (en) | 1998-04-03 | 1999-04-01 | Method for noise suppression in a microphone signal |
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US (1) | US6895095B1 (en) |
EP (1) | EP0948237B1 (en) |
AT (1) | ATE398326T1 (en) |
DE (2) | DE19814971A1 (en) |
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DE19958836A1 (en) * | 1999-11-29 | 2001-05-31 | Deutsche Telekom Ag | In car communication system has individual microphones and loudspeakers allows easy conversation |
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DE10052991A1 (en) * | 2000-10-19 | 2002-05-02 | Deutsche Telekom Ag | Determining spatial acoustic and electroacoustic parameters, involves conducting signal conversion steps in room with sound source, electroacoustic converters in predefined arrangement |
DE10221990B4 (en) * | 2002-05-17 | 2006-10-12 | Audi Ag | Reduction of noise on car radios with bus connections |
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JP2005218010A (en) * | 2004-02-02 | 2005-08-11 | Matsushita Electric Ind Co Ltd | Intravehicle data transmission system |
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US7716046B2 (en) * | 2004-10-26 | 2010-05-11 | Qnx Software Systems (Wavemakers), Inc. | Advanced periodic signal enhancement |
US8170879B2 (en) | 2004-10-26 | 2012-05-01 | Qnx Software Systems Limited | Periodic signal enhancement system |
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US7525440B2 (en) * | 2005-06-01 | 2009-04-28 | Bose Corporation | Person monitoring |
ATE423433T1 (en) * | 2006-04-18 | 2009-03-15 | Harman Becker Automotive Sys | SYSTEM AND METHOD FOR MULTI-CHANNEL ECHO COMPENSATION |
DE602006009770D1 (en) * | 2006-05-08 | 2009-11-26 | Harman Becker Automotive Sys | Echo reduction for time variant systems |
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US7577257B2 (en) * | 2006-12-21 | 2009-08-18 | Verizon Services Operations, Inc. | Large scale quantum cryptographic key distribution network |
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US20180166073A1 (en) * | 2016-12-13 | 2018-06-14 | Ford Global Technologies, Llc | Speech Recognition Without Interrupting The Playback Audio |
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-
1998
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1999
- 1999-04-01 AT AT99106123T patent/ATE398326T1/en not_active IP Right Cessation
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ATE398326T1 (en) | 2008-07-15 |
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EP0948237A2 (en) | 1999-10-06 |
US6895095B1 (en) | 2005-05-17 |
DE59914782D1 (en) | 2008-07-24 |
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