EP0992978A1 - Dispositif et procede de reduction de bruits - Google Patents

Dispositif et procede de reduction de bruits Download PDF

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Publication number
EP0992978A1
EP0992978A1 EP98957196A EP98957196A EP0992978A1 EP 0992978 A1 EP0992978 A1 EP 0992978A1 EP 98957196 A EP98957196 A EP 98957196A EP 98957196 A EP98957196 A EP 98957196A EP 0992978 A1 EP0992978 A1 EP 0992978A1
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Prior art keywords
noise
amplitude
spectrum
output
amplitude spectrum
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EP98957196A
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German (de)
English (en)
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EP0992978A4 (fr
Inventor
Kazutaka Mitsubishi Denki Kabushiki Kaisha TOMITA
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Mitsubishi Electric Corp
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Mitsubishi Electric Corp
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Publication of EP0992978A1 publication Critical patent/EP0992978A1/fr
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    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00Speech 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
    • G10L21/02Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208Noise filtering
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00Speech 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
    • G10L21/02Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208Noise filtering
    • G10L21/0216Noise filtering characterised by the method used for estimating noise
    • G10L21/0232Processing in the frequency domain
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/78Detection of presence or absence of voice signals
    • G10L25/84Detection of presence or absence of voice signals for discriminating voice from noise

Definitions

  • the present invention relates to a noise reduction method of a speech signal adopted in a speech communication system or a speech recognition system used under an environment with background noises.
  • the noise reduction method suppresses a noise of the speech signal input to these systems by eliminating the noise.
  • the present invention also relates to a noise reduction method of a noise frame of the speech signal by suppressing its amplitude.
  • a conventional method to reduce the background noises is illustrated in the drawing of Fig.15.
  • the method will be described below.
  • This method converts an input signal of speech having background noises from analogue to digital.
  • An A/D converted input signal is divided into fixed periods (frames). Then, the followings are performed in order to obtain an output signal with reduced noises for every one of the divided frames.
  • a discrete Fourier transformation is applied to a series of input signals including a fixed period signal (hereinafter referred to as a frame signal).
  • the frame signal is transformed to a frequency spectrum by applying the discrete Fourier transformation to the series of input signals.
  • the frequency spectrum is divided into an amplitude spectrum and a phase spectrum.
  • An estimated noise amplitude spectrum has been estimated from a non speech frame.
  • the estimated noise amplitude spectrum is subtracted from the amplitude spectrum of the input signal using a subtraction filter. By doing so, a speech amplitude spectrum with reduced background noises (output amplitude spectrum) is estimated. Then, the speech amplitude spectrum is added to the phase spectrum to get a frequency spectrum of the speech with reduced background noises. By applying an inverse discrete Fourier transformation to the frequency spectrum of this speech, the output signal with reduced noises is obtained.
  • This method is being proposed in a paper by Steven F. Ball, entitled “Supprssion of acustic noise in speech using spectral subtraction", IEEE Trans. Acoust., Speesh and Signal Proc., vol. ASSP-29, pp.113-120, Apr. 1979.
  • Fig.15 illustrates a block chart of the conventional noise reduction method.
  • An input signal 107 cut into a fixed frame length is transformed to a frequency domain at a Fourier transformation unit 101.
  • An input phase spectrum 108 and an input amplitude spectrum 109 are output from the Fourier transformation unit 101.
  • a noise period deciding unit 102 decides that the input signal is in a speech frame (period) if greater than a threshold value TH, and the input signal is in a noise frame (period) if less than the threshold value TH.
  • an estimated noise amplitude spectrum calculating unit 103 performs a weighted addition of the input amplitude spectrum 109 of that time and an estimated noise amplitude spectrum up to that time and outputs an updated estimated noise amplitude spectrum 110.
  • a typical transmission function of the subtraction filter unit 104 is expressed by an equation (1).
  • F( ⁇ ) S( ⁇ ) 2 -r ⁇ E(N( ⁇ )) 2 S( ⁇ ) 2 whereas
  • S ( ⁇ ) denotes to an amplitude spectrum of the input signal
  • E (N ( ⁇ )) denotes to an estimated noise amplitude spectrum
  • r is a constant expressing the reduction rate of the estimated noise amplitude spectrum.
  • the reduction rate r is calculated based on a pre-determined equation at the subtraction filter unit 104.
  • an output amplitude spectrum 111 is output from the subtraction filter unit 104 by subtracting the estimated noise amplitude spectrum from the input amplitude spectrum, in a same manner as the equation (1).
  • the noise suppression is weakened by decreasing the reduction rate for a frame with small power such as noise frame or consonant sounds.
  • An inverse Fourier transformation unit 105 outputs an output signal in a time domain.
  • the first conventional spectrum subtraction method has a disadvantage of deteriorated speech quality due to cutoff of a speech such as onset of speech, ending part of speech, or frame with small power such as consonant sounds. Such cutoff of the speech will further increase by increasing the reduction rate r.
  • a function called window function is determined for a period in time axis, and the signals for applying the Fourier transformation is weighted by multiplying of the window function. For example, a frame signal and a fixed length signal which is continuous to the frame signal (overlap signal) are multiplied by the window function and then the Fourier transformation is applied. For a frame signal output from the inverse Fourier transformation, an overlap signal output from the inverse Fourier transformation of the previous frame is added to a beginning of the sample weighted by less than 1 in the frame.
  • the window function is used so that addition of weights of the samples corresponding to an addition of the frame signal and the overlap signal becomes 1.
  • the window function is used to get smooth edges of the signals for applying the Fourier transformation.
  • a third conventional spectrum subtraction method there is a method of applying Fourier transformation to a frame signal and a fixed length signal (overlap signal) continuous to the frame signal without weighting by the window function.
  • This method is being used in the noise reduction apparatus disclosed in Japanese unexamined patent publication HEI 9-34497.
  • This method implements a waveform reforming process which overlaps an overlap signal output from the inverse Fourier transformation of the previous frame with a frame signal output from the inverse Fourier transformation at a triangle window and outputs the result.
  • the waveform reforming process is implemented to achieve smooth outputs between frames.
  • the overlap signal output from the inverse Fourier transformation is stored for overlapping to a next frame.
  • the waveform reforming process is expressed by an equation (2).
  • fixed decimal point DSP 16-bits fixed decimal point calculation digital signal processor
  • the Fourier transformation and inverse Fourier transformation involve a large amount of calculation.
  • the spectrum subtraction method there are many cases of wanting to implement the spectrum subtraction method by involving a small amount of calculation, although this may sacrifice the precision calculation.
  • the third conventional spectrum subtraction method since the frame signal for applying Fourier transformation is not weighted by the window function, a dynamic range of the frame signal does not spread. And an accuracy deterioration of the frame signal is small if being applied the Fourier transformation and inverse Fourier transformation with the limited precision calculation. This is the reason for using the fixed decimal point DSP involving the small amount of calculation.
  • the fourth conventional noise reduction method using a spectrum subtraction at first, estimates a noise power for calculating the estimated noise amplitude spectrum, and a calculated noise power is taken as a noise frame deciding threshold value. Then, if an input power is smaller than this threshold value, the input frame is decided as a noise frame. It is common that the estimated noise amplitude spectrum is calculated as an average of noise signals, that is, an average of input signals of a plurality of frames which are decided as noises.
  • This spectrum subtraction method is disclosed in Japanese unexamined patent publication HEI8-221092 as an example.
  • a method which is disclosed in Japanese unexamined patent publication HEI7-38454 decides a state of current frame from a predetermined finite state which expresses a signal mode, and suppresses the amplitude by a certain intensity if the state of current frame is indicating a noise frame state.
  • the first conventional spectrum subtraction method has the disadvantage where a noise period is distorted and become an unpleasant residual noise called musical noise, which is a major practical problem.
  • This problem occurs in the noise period when an output amplitude spectrum shows a form in which a power of the output amplitude spectrum is sparsely concentrated to some of frequencies by subtracting estimated noise amplitude spectrum.
  • the problem occurs when the power concentrated frequencies varies irregularly among frames.
  • the noise reduction efficiency will improve by applying the Fourier transformation to a signal weighted by the window function so that both edges of the signal approaches 0.
  • an accuracy of the signal at both edges declines when this method is performed by the fixed decimal point DSP, therefore, there is a problem of discontinuous feeling sound occurring at the frame boundaries when both edges of the signal output from the inverse Fourier transformation deteriorates.
  • the noise period deciding threshold value is set higher for the cases of a large power variation of noise so that the noise frame can be decided correctly. In doing so, the speech frame is also wrongly decided as a noise frame to a certain extent, and a speech spectrum will be involved to the estimated noise amplitude spectrum, resulting in the speech cutoff. On contrary, to prevent this from happening, the noise period deciding threshold value can be set lower so as not to decide the speech frame as the noise frame. But by doing so the noise frame is misjudged as a speech frame, therefore, the updating of estimated noise amplitude spectrum is not performed correctly, and as a result, the noise reduction efficiency is reduced.
  • the fifth conventional method declines the noise perception by suppressing the amplitude of noise period, and a current frame state is decided from a pre-determined finite states expressing the signal mode.
  • a problem with the fifth conventional method is that if the frame state indicates a noise frame state, if this method adopts a method suppressing the amplitude of noise frame by a certain intensity, there is a case that the frame state transition happens frequently between the speech frame state and the noise frame state in a short period of time depending on a type of input noise. In addition to that, the intensity of suppressing amplitude changes frequently.
  • the present invention attempts to solve the problems mentioned above by aiming for a noise reduction method which can lessen unpleasant residual noise, even if the spectrum of each frame is sparsely concentrated to some of the frequencies or even if the frame state transition are happening frequently from or to the noise frame.
  • the noise reduction apparatus includes the spectrum subtraction filter which varies a reduction rate of a subtraction of estimated noise amplitude spectrum based on the estimated noise amplitude spectrum; and includes the amplitude adjusting filter unit which varies the amplitude adjusting coefficient based on the reduction rate.
  • the noise reduction apparatus includes the amplitude adjusting filter unit which increases the amplitude adjusting coefficient if the reduction rate is large, so as to intensify a noise suppression of speech period and to increase an output value of output signal; and includes the amplitude adjusting filter unit which decreases the amplitude adjusting coefficient if the reduction rate is small, so as to weaken a noise suppression of noise period and to decrease an output value of output signal.
  • the noise reduction apparatus includes the amplitude adjusting filter unit which multiplies the amplitude adjusting coefficient to an amplitude spectrum is a time domain, which has applied an inverse orthogonal transformation to the subtraction output by the spectrum subtraction filter.
  • the noise reduction apparatus includes the amplitude adjusting filter unit which multiplies the amplitude adjusting coefficient to the amplitude spectrum in a frequency domain for each frame, and obtains an output by applying an inverse orthogonal transformation.
  • the noise reduction apparatus inlcudes the amplitude adjusting coefficient which is a value obtained by an addition of a weighted amplitude adjusting coefficient obtained at a previous frame and an amplitude adjusting coefficient of a current frame which is obtained based on a difference of the power of amplitude spectrum of input signal of the current frame and the power of estimated noise amplitude spectrum of the current frame.
  • the noise reduction apparatus further inlcudes a waveform reforming unit for reforming the current frame by using a period after the previous frame, which is multiplied by the weighted function of 1.
  • the noise reduction apparatus further comprises an average noise power calculating unit for calculating an average noise power from a plurality of frames of the estimated noise amplitude spectrum; and includes the amplitude adjusting filter unit which multiplies the subtraction output which is output from the spectrum subtraction filter for each frame to an amplitude adjusting coefficient determined from the average noise amplitude power and the amplitude spectrum power, and obtains a desired output.
  • a noise reduction method for obtaining an output from a spectrum subtraction filter by subtracting an estimated noise amplitude spectrum from an amplitude spectrum which is obtained by orthogonally transforming an input signal cut into a fixed frame length comprises the steps of: varying a reduction rate of the spectrum subtraction filter based on the estimated noise amplitude spectrum; and multiplying a subtraction output which is output from the spectrum subtraction filter for each frame to the amplitude adjusting coefficient determined from a power of amplitude spectrum and a power of estimated noise amplitude spectrum, and obtaining a desired output.
  • a noise reduction method for obtaining an output from a spectrum subtraction filter by subtracting an estimated noise amplitude spectrum from an amplitude spectrum which is obtained by orthogonally transforming an input signal cut into a fixed frame length comprises the steps of calculating a reduction rate including a step of calculating an average noise power from a plurality of frames of the estimated noise amplitude spectrum and a step of comparing the calculated average noise power with a noise period deciding threshold value; and setting the calculated reduction rate as a reduction rate of the spectrum subtraction filter.
  • a noise reduction method of the embodiment 1 is described.
  • a reduction rate of the spectrum subtraction filter is variable.
  • the noise reduction method of the present invention comprises an amplitude adjusting filter unit which subtracts an amplitude from a normal output.
  • the amplitude subtraction relies on the reduction rate of the spectrum subtraction filter.
  • the drawing of Fig.1 illustrates a block chart of the noise reduction method of the embodiment 1.
  • the drawing of Fig.2 illustrates a flow chart of the amplitude adjusting filter unit of Fig.1.
  • FIG.17 illustrates a comparison of operations for the speech period and the noise period .
  • An input signal 7 having a fixed frame length is orthogonally transformed at the Fourier transformation unit 1, transformed to a frequency domain, and an input phase spectrum 8 and an input amplitude spectrum 9 are output.
  • a noise period deciding unit 2 decides that the input signal is in a speech frame (period) if it exceeded a threshold value TH, and decides that the input signal is in a noise frame (period) if below the threshold value. If an equation (3) is satisfied, the threshold TH is replaced by a new threshold TH new .
  • P in ⁇ 2.0 TH TH new 0.9 TH+0.1 P in
  • TH is a noise period deciding threshold value before updating
  • TH new is a noise period deciding threshold value after updating
  • an estimated noise amplitude spectrum calculation unit 3 performs a weighted addition of an input amplitude spectrum 9 of the time and an estimated noise amplitude spectrum up to that time and outputs an estimated noise amplitude spectrum 10.
  • the estimated noise amplitude spectrum 10 is updated by an equation (5).
  • the reduction rate r is calculated based on a next equation (6), and an obtained reduction rate r is output as a noise reduction intensity 13.
  • r min ⁇ 1.0, r TH ⁇ POWs/POW N ⁇
  • an input amplitude spectrum is subtracted by an estimated noise amplitude spectrum in a same manner as the equation (1), to give a subtracted output amplitude spectrum 11.
  • the subtraction filter unit 4 weakens a noise suppression by making the reduction rate small for a noise frame or a frame having small power such as consonant sounds.
  • the amplitude suppression of an output amplitude 12 which is returned to a time domain at an inverse Fourier transformation unit 5 is intensified since an amplitude adjusting coefficient gets small at a next amplitude adjusting filter unit 6 for those frames with small powers.
  • the amplitude adjusting filter unit 6 performs the following three operations from steps S1 to S3 of Fig.2.
  • the noise reduction intensity 13 (the reduction rate r) is input at step S1.
  • a power of estimated noise amplitude spectrum of a current frame is subtracted from a power of amplitude spectrum of input signal of the current frame.
  • an amplitude suppressing coefficient G is calculated using an equation (7) for each frame.
  • G POW S -POW N POW S -r ⁇ POW N (POW S -POW N ⁇ 0,and,POW S -r ⁇ POW N >0)
  • G 0 (POW S -POW N ⁇ 0,or,POW S -r ⁇ POW N ⁇ 0)
  • POW S denotes a power of amplitude spectrum of all frequencies of input signal of a current frame
  • POW N denotes a power of estimated noise amplitude spectrum of all frequencies of the current frame
  • G denotes an amplitude suppressing coefficient of the current frame
  • r denotes the reduction rate.
  • the amplitude suppressing coefficient G gets large if the reduction rate r is large. If the reduction rate r gets small, the amplitude suppressing coefficient G is also small.
  • amplitude adjusting coefficients g(n) for each of samples are calculated in step S2 using an equation (8).
  • g (n) g (n-1) AR+G (1-AR)
  • g(n) denotes an amplitude adjusting coefficient of nth sample of a current frame
  • n-1 expresses a previous sample.
  • the reduction rate r when the reduction rate r is large, the amplitude suppressing coefficient G becomes large, and the amplitude adjusting coefficient g(n) gets large.
  • the reduction rate r is small, the amplitude suppressing coefficient G becomes small, and the amplitude adjusting coefficient g(n) gets small.
  • step S3 the output amplitude 12 from the inverse Fourier transformation unit 5 is expressed in S in , and an output signal 14 is calculated by multiplying the amplitude adjusting coefficient g(n) to the output amplitude 12 by using an equation (9).
  • S out (n) S in (n) X g
  • FIG.4 illustrates input/output attributes of the amplitude adjusting filter unit 6. It is apparent from the drawing that, because the reduction rate r is small for the noise period, the amplitude adjusting coefficient g(n) is small. An output value for the noise period becomes small since a suppression gets large. On contrary, because the reduction rate r is larger for the speech period, the amplitude adjusting coefficient g(n) is large. An output value for the speech frame comparatively increases since a suppression gets small.
  • the amount of reduction rate of the noise in the frequency domain is reduced for the noise frame or the speech frame having small power such as consonant sounds, therefore, the occurrences of musical noise are suppressed at the noise frame, and the cutoff of speech period is prevented.
  • Fig.5 illustrates the amplitude spectrums of noise frame before reduction and after reduction.
  • the amplitude adjusting filter unit 6 of the present embodiment gradually changes the amplitude adjusting coefficients in a direction of time axis for every samples sequentially inside a frame by using the equation (8), therefore, a natural output is obtained in spite of a sudden adjusting of the amplitude such as onset of the speech period.
  • the amplitude adjustment can also be implemented to the frequency domain. That is, the amplitude adjusting filter unit is provided after the Fourier transformation unit so that the inverse Fourier transformation is applied to a signal after the amplitude is adjusted.
  • FIG.6 illustrates a block chart showing the configuration of spectrum subtraction method of the present embodiment.
  • Fig.6 illustrates a configuration for adjusting an amplitude in the frequency domain for which the amplitude adjusting filter of Fig.1 is relocated immediately after the subtraction filter 4. Operation of all other parts is same as the operation of embodiment 1.
  • the subtraction filter unit 4 calculates the reduction rate by using the equation (6), and based on a calculated reduction rate, the estimated noise amplitude spectrum 10 is subtracted from the input amplitude spectrum 9, and the subtraction filter unit 4 outputs an output amplitude spectrum.
  • the amplitude adjusting filter unit 15 outputs a final output amplitude spectrum by multiplying the amplitude adjusting coefficient calculated based on the reduction rate r to the output amplitude spectrum.
  • the intensity of reduction is small for the noise frame or the speech frame having small power such as consonant sounds, therefore, the musical noise occurrence at the noise frame is suppressed, which prevents diminishing or distorting of consonant sounds period.
  • the amplitude is suppressed depending on the amount of reduction, such that the insufficient amount of noise suppression is prevented.
  • the amplitude adjusting coefficient needs be calculated only once for each frame. In this embodiment, there is no need to calculate the amplitude adjusting coefficient for each of signal samples as in the step S3 of Fig.2 of the embodiment 1. Therefore, the present embodiment is implemented by small calculation amount.
  • the input signal is divided into fixed frames and speech is extracted for every frames.
  • the input signal becomes non-continuous at divided points of the frames, and this may result in the occurrence of discontinuous feeling sounds.
  • This embodiment attempts to improve from this by smoothening a change in the input signal at the divided points between the frames.
  • Fig.7 illustrates a block chart of the configuration of spectrum subtraction method for the embodiment 3. Most of the elements are same as those of Fig.1. New elements are: an input signal creating unit 19; and a waveform reforming unit 20.
  • the drawing of Fig.8 illustrates the example of input signal 7 for the noise reduction method of the embodiment 3.
  • the drawing of Fig.9 illustrates a weighting function for multiplying to the input signal at the input signal creating unit for the noise reduction method of the embodiment 3.
  • FIG.10 illustrates the example of output signal 5a of the inverse Fourier transformation unit 5 for the noise reduction method of the embodiment 3.
  • Fig.8 illustrates a time series amplitude of the input signal 7 after the A/D conversion, which is inputted to the input signal creating unit 19.
  • a of Fig.8 illustrates a period before the frame.
  • B and C of Fig.8 illustrate periods after the frame.
  • the Fig.10 illustrates u(i)
  • a frame signal is weighted so that its edges approach 0 and the weighted frame signal is applied the Fourier transformation, therefore, the noise reduction efficiency will improve.
  • edges A and C of Fig.18
  • edges A and C of Fig.18
  • an output accuracy is secured, at the same time, the discontinuous feeling sounds occurring at the frame boundaries is prevented.
  • the present embodiment considers a method of reducing the speech cutoff caused by an excessive reduction and facilitates a method of distinguishing the noise period.
  • Fig.11 illustrates a block chart of configuration of the spectrum subtraction method of the embodiment 4 for the present invention.
  • a new element is a reduction rate calculating unit 16.
  • Other elements are identical to those of Fig.1.
  • Fig.12 describes the operation of the noise reduction method of the present embodiment.
  • a bold line indicates an input power of noise frame POW S
  • a dotted line indicates an average noise power POW AVE
  • a chained line indicates a noise period deciding threshold value POW TH .
  • the POW TH is a threshold value of previous noise frame as described in the equation (3).
  • the present configuration has added the reduction rate calculating unit 16 to the overall configuration of the conventional spectrum subtraction.
  • a filter of the subtraction filter unit 4 performs calculation of the equation (1).
  • the noise period deciding unit 2 calculates the noise period deciding threshold value POW TH . If an input power underlies this threshold value, it is decided as the noise frame.
  • the reduction rate calculating unit 16 calculates an average power from a plurality of noise frames close to a current frame based on this decision, and takes it as the average noise power.
  • the reduction rate calculating unit 16 calculates a ratio r1 of the noise period deciding threshold value 17 and the average noise power based on an equation (12), provided that the noise period deciding threshold value is POW TH and the average noise power is POW AVE .
  • a calculated ratio r1 is output as a noise variation level 18.
  • r 1 POW AVE POW TH
  • the noise variation level r1 is set as the reduction rate r of noise spectrum of the equation (1).
  • a higher value of the noise period deciding threshold value POW TH is used when the power variation of noise is large so that an input signal is correctly decided in the noise period.
  • Fig.12 illustrates the changes in the average noise power and the noise period deciding threshold value against the change in the input power of the noise period.
  • the reduction rate r1 when the change in the noise power is large, a value of the average noise power POW AVE of the noise frame is smaller than the noise period deciding threshold value POW TH , as illustrated in the drawing of Fig. 12. Therefore, the reduction rate r1 must be smaller than 1. As a result, the reduction by estimated noise amplitude spectrum is effectively suppressed, and the speech cutoff is reduced, and an estimated noise amplitude spectrum is updated correctly.
  • the present embodiment describes a method of reducing an unpleasant remaining noise, by suppressing the amplitude of input signal which was decided as a noise of the noise period.
  • FIG.13 illustrates a block chart of the main elements of the noise reduction method of the embodiment 5 of the present invention.
  • FIG.14 illustrates the operation of the noise reduction method of the present embodiment.
  • the configuration of the present embodiment reduces the noise by suppressing an amplitude of the noise period, and decides the amplitude adjusting coefficient for suppressing the amplitude depending on the current input power and the average noise power.
  • a noise period deciding unit 301 calculates an input power POW S 305 shown by the bold line of Fig.12 from the input signal 304, and decides a noise period by using the noise period deciding threshold value POW TH just as in the embodiment 1. Based on a decided noise period, an average noise power calculating unit 302 calculates an average power of plurality of past noise frames that are close to the current frame, and obtains an average noise power POW AVE 306 which is shown by the dotted line of Fig.12.
  • An amplitude adjusting filter unit 303 calculates the amplitude suppressing coefficient G from the input power POW S 305 and the average noise power POW AVE 306 of the input signal by using an equation (13).
  • the amplitude suppression coefficient G is used as an amplitude adjusting coefficient as it is.
  • the amplitude adjusting filter unit 303 multiplies the amplitude adjusting coefficient to the input signal 304 and obtains an output signal 307.
  • the final amplitude adjusting coefficient g(n) is calculated by an operation of smoothening the change in the amplitude suppressing coefficient G for each of samples as in the equation (8).
  • FIG.14 illustrates a relation of output power of the output signal 307 after adjusting the amplitude and the input power POW s 305 of the input signal 304.
  • the bold line illustrates a relation of the output power and the input power POW s in cases of using the amplitude adjusting filter.
  • the bold line shows a smaller output value than the output value shown by the dotted line due to the amplitude suppression.
  • the bold line also shows that the output signal power is zero when the input power is smaller than the average noise power POW AVE .
  • the reduction rate is made variable, and with the amplitude adjusting filter unit for changing a degree of the amplitude suppression based on the varying reduction rate is provided, therefore, the speech output is stabilized without having to change the amplitude suppression extensively and frequently as in the case of directly deciding the amplitude adjusting coefficient from a decided state of the speech.
  • the present invention not only the reduction rate is variable, it is provided with the amplitude adjusting filter unit for changing the degree of suppressing the amplitude based on the variable reduction rate, therefore, even if the intensity of reduction at noise frame is reduced for a purpose of preventing the cutoff of noise frame, the noise is suppressed by suppressing the amplitude corresponding to the reduction rate.
  • the present invention is effective in obtaining a well-balanced and easy-to-hear output.
  • the amplitude adjustment is performed in the frequency domain, therefore, there is no need to calculate the amplitude adjusting coefficients for each of signal samples.
  • the present invention is effective in reducing the amount of calculation.
  • the amplitude adjusting coefficient gradually changes in the direction of time axis, therefore, a natural output is obtained even though there may be a sudden amplitude adjusting such as onset of the speech period.
  • the present invention since the present invention is provided with the input signal creating unit which multiplies a current frame signal and a signal in the periods before and after the current frame by the weighting function and performs addition of the weighted current frame signal, therefore, the noise reduction efficiency will be higher by improving an estimated accuracy of the noise spectrum by weighting the signals for applying to the Fourier transformation. Also, in case that non-weighted signal of the inverse Fourier transformation is output as the frame signal, this is effective in obtaining a highly accurate signal and is effective in performing a small calculation amount even by using the fixed decimal point calculation digital signal processor.
  • the present invention since the intensity of noise removal is adjusted depending on a variation characteristic of period which was decided as the noise period, the present invention is effective in pursuing and setting a correct noise deciding threshold value even for the cases of noise period having a large variation.
  • the invention is also effective in preventing the speech cutoff due to the added speech components getting mixed.
  • the present invention since a gradually changing average power of noise period is used in determining the amount of amplitude suppression instead of determining an amount of amplitude suppression directly from the noise period, the present invention is effective in avoiding a bad influence caused by frequent changes in the noise period deciding output.

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Quality & Reliability (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Noise Elimination (AREA)
EP98957196A 1998-03-30 1998-12-07 Dispositif et procede de reduction de bruits Withdrawn EP0992978A4 (fr)

Applications Claiming Priority (3)

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JP8417498 1998-03-30
JP8417498 1998-03-30
PCT/JP1998/005512 WO1999050825A1 (fr) 1998-03-30 1998-12-07 Dispositif et procede de reduction de bruits

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EP0992978A1 true EP0992978A1 (fr) 2000-04-12
EP0992978A4 EP0992978A4 (fr) 2002-01-16

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KR (1) KR100314332B1 (fr)
CN (1) CN1258368A (fr)
AU (1) AU721270B2 (fr)
CA (1) CA2291826A1 (fr)
WO (1) WO1999050825A1 (fr)

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GB2422237A (en) * 2004-12-21 2006-07-19 Fluency Voice Technology Ltd Dynamic coefficients determined from temporally adjacent speech frames
EP1914727A1 (fr) * 2005-05-17 2008-04-23 Yamaha Corporation Procede de suppression de bruit et dispositif correspondant
US20100207689A1 (en) * 2007-09-19 2010-08-19 Nec Corporation Noise suppression device, its method, and program
US9318122B2 (en) 2014-04-18 2016-04-19 Fujitsu Limited Audio signal processing apparatus and audio signal processing method
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EP3232589A3 (fr) * 2016-04-12 2018-01-17 Panasonic Intellectual Property Corporation of America Appareil de reproduction stéréo
EP3276621A1 (fr) * 2016-07-27 2018-01-31 Fujitsu Limited Dispositif de suppression du bruit et procédé de suppression du bruit
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KR100314332B1 (ko) 2001-11-16
CN1258368A (zh) 2000-06-28
KR20000076037A (ko) 2000-12-26
AU1352599A (en) 1999-10-18
WO1999050825A1 (fr) 1999-10-07
AU721270B2 (en) 2000-06-29
CA2291826A1 (fr) 1999-10-07

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