WO1999050825A1 - Dispositif et procede de reduction de bruits - Google Patents

Dispositif et procede de reduction de bruits Download PDF

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Publication number
WO1999050825A1
WO1999050825A1 PCT/JP1998/005512 JP9805512W WO9950825A1 WO 1999050825 A1 WO1999050825 A1 WO 1999050825A1 JP 9805512 W JP9805512 W JP 9805512W WO 9950825 A1 WO9950825 A1 WO 9950825A1
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WIPO (PCT)
Prior art keywords
noise
amplitude
amplitude spectrum
output
power
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PCT/JP1998/005512
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English (en)
Japanese (ja)
Inventor
Kazutaka Tomita
Original Assignee
Mitsubishi Denki Kabushiki Kaisha
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Mitsubishi Denki Kabushiki Kaisha filed Critical Mitsubishi Denki Kabushiki Kaisha
Priority to EP98957196A priority Critical patent/EP0992978A4/fr
Priority to AU13525/99A priority patent/AU721270B2/en
Priority to CA002291826A priority patent/CA2291826A1/fr
Publication of WO1999050825A1 publication Critical patent/WO1999050825A1/fr

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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
    • 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
    • G10L21/0232—Processing in the frequency domain
    • 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
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/78—Detection of presence or absence of voice signals
    • G10L25/84—Detection of presence or absence of voice signals for discriminating voice from noise

Definitions

  • the present invention is applied to a voice communication system or a voice recognition system used in an environment having background noise, and a noise reduction method for a voice signal that performs noise suppression by removing noise from an input voice signal and a noise section. It relates to a noise reduction method using amplitude suppression. Background art
  • a method shown in FIG. 15 below is known as a means for reducing background noise. That is, the input signal in which the background noise is superimposed on the voice is converted into an AZD (analog Z-digital) signal and divided into a fixed section (frame). (Hereinafter referred to as a frame signal) is converted to a frequency spectrum by a discrete Fourier transform, and then divided into an amplitude spectrum and a phase spectrum.
  • AZD analog Z-digital
  • the audio amplitude spectrum with reduced background noise Is estimated as the frequency spectrum of the voice with the background noise reduced along with the previous phase spectrum, and the frequency spectrum of this voice is inversely dispersive Fourier transformed and the output signal is obtained.
  • a scan Bae click Tsentralnyi sub tiger click Chillon becomes how obtained. This is S TEVEN F. BAL L "S upprssionofacusticnoi salspeechusingspectr alsubtraction," I EEE T rans. A coust., Speeshand Signal Proc., vol. AS SP-29, pp. 113-120, Apr. 1979.
  • FIG. 15 is a block diagram showing the configuration of this noise reduction method. First, the overall operation will be described with reference to FIG.
  • the input signal 107 cut out to a predetermined frame length is converted into the frequency domain by the Fourier transform unit 101, and the input phase spectrum 108 and the input amplitude spectrum 109 are output. You.
  • the input signal is determined by the noise section determination unit 102 to be a speech frame (section) if it is equal to or more than the threshold value TH, and a noise frame (section) otherwise.
  • the estimated noise amplitude spectrum calculation unit 103 weights and adds the input amplitude spectrum 109 at that time to the previous estimated noise amplitude spectrum. And outputs the estimated noise amplitude spectrum 110 updated.
  • the subtraction 'filter section 104 has a characteristic whose representative transfer function is represented by the following equation (1).
  • Equation (1) S ( ⁇ ) is the amplitude spectrum term of the input signal, ⁇ ( ⁇ ( ⁇ )) is the estimated noise amplitude spectrum term, and r is a constant representing the removal rate of the estimated noise amplitude spectrum. Increasing r increases the amount of noise suppression; conversely, decreasing r decreases the amount of noise suppression.
  • the subtraction 'filter section 104 calculates the removal rate r based on a predetermined equation.
  • the input amplitude spectrum and the estimated noise amplitude spectrum are subtracted in the same manner as in equation (1), and the difference output amplitude spectrum 111 is obtained. Output.
  • the subtraction / filter unit 104 reduces the removal rate for noise frames and low power frames such as consonants to reduce noise suppression.
  • a method in order to enhance the noise reduction effect, a method is used in which a function called a window function is defined on the time axis of the signal to be subjected to Fourier transform and multiplied and weighted.
  • a frame signal and a continuous signal with a certain length are multiplied by a window function and subjected to Fourier transform.
  • the output frame signal of the inverse Fourier transform is added to the first weighted sample below 1
  • the method of adding the overlap signal of the output of the inverse Fourier transform of the frame and outputting it is: North America CDMA mobile phone system (TIA / EIA, IS-127, "Enhanced Variable Rate Code Service Option 3 for Wideband S pread Spectrum Digital Systems") I have.
  • Figure 16 shows the window function used here.
  • a window function is used so that the sum of the weights of the samples corresponding to the addition of the frame signal and the overlap signal becomes 1, and that both ends of the Fourier transform target signal smoothly approach 0.
  • a third conventional spectral subtraction method there is a method of performing a Fourier transform on a frame signal and a signal of a fixed length (overlap signal) following the frame signal without weighting by a window function.
  • it is used in the noise reduction device disclosed in Japanese Patent Application Laid-Open No. Hei 9-134449.
  • a waveform shaping process is performed in which the overlap signal of the inverse Fourier transform output of the immediately preceding frame is superimposed on the triangular window with the frame signal of the inverse Fourier transform output. And outputs the same, and saves the inverse Fourier transform output overlap signal for overlap processing of the next frame. Equation (2) shows the waveform shaping process at this time.
  • fixed-point DSP 16-bit fixed-point digital signal processor
  • the operation precision of the fixed-point decimal point D SP can be increased by double-precision arithmetic operation or carry by shift.
  • the amount of calculation for this increases.
  • the Fourier transform and the inverse Fourier transform basically require a large amount of computation, and there are many cases where it is desired to realize the computation with a small amount of computation at the expense of a little computation accuracy.
  • this method the frame range to be Fourier-transformed is not weighted by the window function, so the dynamic range is not widened, and the accuracy of the output frame signal that has undergone limited Fourier transform and inverse Fourier transform is degraded. Less is. For this reason, a fixed-point DSP that requires a small amount of computation is used.
  • the fourth conventional noise reduction method using spectral subtraction is
  • the estimated noise amplitude spectrum is generally calculated by averaging the input signals of a plurality of frames in the section determined to be noise, that is, the average of the amplitude spectrum of the noise signal. For example, the spectral sub in Japanese Patent Application Laid-Open No. This method is used in fractionation.
  • a method of determining the state of the current frame from a predetermined finite state representing the state of the signal and determining the state of the current frame when the state corresponds to the state of a noise frame is disclosed in Japanese Unexamined Patent Publication No. — Indicated by 3 8 4 5 4.
  • the first conventional spectral subtraction method has a drawback that a noise section is deformed and becomes unpleasant residual noise called musical noise, which is the biggest practical problem.
  • the output amplitude spectrum from which the estimated noise amplitude spectrum has been subtracted has a shape in which power is concentrated in a part of the frequency, and the frequency in which the power is concentrated is not per frame. It changes by changing the rules.
  • a method of solving musical noise a method of varying the removal rate of the estimated noise amplitude spectrum is used, and the removal amount may be reduced in a noise frame, but the noise suppression amount is insufficient in a noise section. There is.
  • the noise reduction ability is improved by performing a Fourier transform on a weighted signal whose both ends approach 0 using a window function.
  • the accuracy of the signals at both ends is reduced when realizing with fixed-point DSP, so that both ends of the output signal of the inverse Fourier transform are degraded and abnormal noise occurs at frame boundaries.
  • the unweighted signal is Fourier-transformed as in the third conventional example, accuracy can be easily achieved when implementing it with a fixed-point DSP, but the noise amplitude spectrum included in the input amplitude spectrum can be improved. Since the variation of the torque component between frames becomes larger than when weighted, the noise reduction ability is inferior to that when weighted.
  • the noise section determination threshold is set high so that the noise frame can be correctly determined when the power fluctuation of the noise is large, some of the speech frames may also be noise frames. There is a problem in that the speech noise leaks into the estimated noise amplitude spectrum, causing the speech to be cut off.
  • the noise interval determination threshold is set low so that the audio frame is not determined to be a noise frame, the noise frame is determined to be a voice frame, and the estimated noise amplitude spectrum is updated.
  • the noise reduction is not performed correctly, and as a result, the noise reduction ability is deteriorated.
  • the frame state of the current frame is determined from a predetermined finite state representing the state of the signal, and this frame state is a noise frame state.
  • this frame state is a noise frame state.
  • the present invention has been made in order to solve the above-mentioned problem, and unpleasant residuals are obtained even when noise frames frequently move to or from noise frames and the spectrum of each frame is biased to some frequencies.
  • the aim is to obtain a noise reduction method with less noise. Disclosure of the invention
  • the noise reduction apparatus subtracts an estimated noise amplitude spectrum from an amplitude spectrum obtained by orthogonally transforming an input signal cut out to a predetermined frame length by a spectral subtraction filter.
  • Noise reduction device to obtain output
  • the required power is calculated by multiplying the reduced power by the spectral subtraction filter by an amplitude adjustment coefficient determined by the power of the amplitude spectrum and the power of the estimated noise amplitude spectrum.
  • An amplitude adjustment filter unit for obtaining an output is provided.
  • the spectral subtraction 'filter makes the subtraction rate of the subtraction of the estimated noise amplitude spectrum variable according to the estimated noise amplitude spectrum.
  • the amplitude adjustment filter unit is characterized in that the amplitude adjustment coefficient is made variable in accordance with the withdrawal rate.
  • the amplitude adjustment filter unit When the subtraction rate is high, the amplitude adjustment filter unit increases the amplitude adjustment coefficient to enhance noise suppression in the voice section and increases the output value of the output signal. When the rate is small, the amplitude adjustment coefficient is reduced, thereby reducing noise suppression in a noise section and reducing the output value of the output signal. It is characterized by multiplying the subtraction output by the central subtraction filter with the time-domain amplitude spectrum subjected to the inverse orthogonal transform.
  • the amplitude adjustment filter section is characterized in that the amplitude spectrum is multiplied by the amplitude adjustment coefficient in the frequency domain for each frame, and an inverse orthogonal transform is performed to obtain an output.
  • the amplitude adjustment coefficient is obtained by adding the amplitude adjustment coefficient of the current frame obtained based on the difference between the power of the amplitude spectrum of the input signal of the current frame and the power of the estimated noise amplitude spectrum of the current frame to the previous frame. It is characterized in that the value of the amplitude adjustment coefficient obtained in (1) is weighted and added.
  • a noise reduction apparatus provides an estimated noise amplitude spectrum from an amplitude spectrum obtained by orthogonally transforming an input signal cut out to a predetermined frame length.
  • a noise reduction device that obtains an output by subtracting with a spectral subtraction 'filter
  • An input signal generation unit that cuts out a set section before and after the current frame and multiplies by a weighting function of 1 or less and adds the input signal before and after the current frame so that the end is close to 0, and outputs the output of the input signal generation unit Is used as an input signal to obtain an amplitude spectrum.
  • a noise reduction apparatus includes a waveform shaping processing unit that shapes a waveform of a current frame using a set section after a previous frame multiplied by one weighting function.
  • the noise reduction apparatus subtracts an estimated noise amplitude spectrum from an amplitude spectrum obtained by orthogonally transforming an input signal cut out to a predetermined frame length by a spectral subtraction filter.
  • a noise reduction device that obtains output
  • a subtraction rate calculation unit that obtains an average noise power from a plurality of frames of the estimated noise amplitude spectrum and compares the average noise power with a determination threshold of the noise frame to obtain a removal rate
  • the subtraction rate used for the subtraction of the spectral subtraction filter is set to the above-described subtraction rate.
  • the noise reduction apparatus includes an average noise power calculation unit that calculates an average noise power from a plurality of frames of the estimated noise amplitude spectrum, and the amplitude adjustment filter unit includes a spectral sub-frame for each frame.
  • the required output is obtained by multiplying the subtraction output by the task filter by an amplitude adjustment coefficient determined by the power of the amplitude spectrum and the average noise amplitude power obtained above.
  • an estimated noise amplitude spectrum is obtained from an amplitude spectrum obtained by orthogonally transforming an input signal cut out to a predetermined frame length.
  • the required power is calculated by multiplying the reduced power by the above-mentioned spectral subtraction filter for each frame by an amplitude adjustment coefficient determined by the power of the above-mentioned amplitude spectrum and the power of the above-mentioned estimated noise amplitude spectrum. It is characterized by a process for obtaining output.
  • the noise reduction method according to the present invention is characterized in that an estimated noise amplitude spectrum is subtracted from an amplitude spectrum obtained by orthogonally transforming an input signal cut out to a predetermined frame length by a spectral subtraction 'filter.
  • an estimated noise amplitude spectrum is subtracted from an amplitude spectrum obtained by orthogonally transforming an input signal cut out to a predetermined frame length by a spectral subtraction 'filter.
  • FIG. 1 is a block diagram showing a configuration of a spectral subtraction method according to Embodiment 1 of the present invention.
  • FIG. 2 is a flowchart showing the operation performed by the amplitude adjustment filter in the noise reduction method according to the first embodiment.
  • FIG. 3 is a diagram illustrating an operation performed by the noise section determination unit according to the first embodiment.
  • FIG. 4 is a diagram for explaining the operation performed by the amplitude adjustment filter according to the first embodiment. is there.
  • FIG. 5 is a diagram illustrating an output signal of the spectral subtraction method according to the first embodiment.
  • FIG. 6 is a block diagram showing a configuration of a spectral subtraction method according to Embodiment 2 of the present invention.
  • FIG. 7 is a diagram showing a configuration of a spectral subtraction method according to Embodiment 3 of the present invention.
  • FIG. 8 is a diagram illustrating an example of an input signal in the noise reduction method according to the third embodiment.
  • FIG. 9 is a diagram illustrating an example of a weighting function multiplied by the input signal generation unit in the noise reduction method according to the third embodiment.
  • FIG. 10 is a diagram illustrating an example of an output signal of the inverse Fourier transform unit in the noise reduction method according to the third embodiment.
  • FIG. 11 is a block diagram showing a configuration of a spectral subtraction method according to Embodiment 4 of the present invention.
  • FIG. 12 is a diagram illustrating an operation in the noise reduction method according to the fourth embodiment.
  • FIG. 13 is a diagram showing a configuration of a spectral subtraction method according to the fifth embodiment of the present invention.
  • FIG. 14 is a diagram illustrating an operation in the noise reduction method according to the fifth embodiment.
  • FIG. 15 is a diagram showing a configuration of a conventional noise reduction method.
  • FIG. 16 is a diagram showing a window function used in the conventional noise reduction method.
  • FIG. 17 is a comparison diagram of the operation of the first embodiment.
  • FIG. 18 is a diagram illustrating a waveform shaping process according to the third embodiment.
  • a noise reduction method in which the subtraction rate of the spectral subtraction filter is made variable and an amplitude adjustment filter section is provided to further subtract an amplitude from a normal output depending on the extraction rate will be described.
  • FIG. 1 is a block diagram illustrating a configuration of a noise reduction method according to the present embodiment.
  • FIG. 2 is a flowchart illustrating an operation of the amplitude adjustment filter unit in FIG.
  • FIG. 17 is a diagram showing a comparison of operations in a speech section and a noise section.
  • the input signal 7 cut out to a predetermined frame length is orthogonally transformed by the Fourier transform unit 1 and transformed into the frequency domain, and the input phase spectrum 8 and the input amplitude spectrum 9 are output.
  • the input signal is judged as a speech frame (segment) if it is equal to or greater than the threshold value TH, and a noise frame (segment) if not more than the threshold value TH.
  • P in is the input signal power
  • TH is before updating the noise section determination threshold value
  • TH new new is the noise section determination threshold updated.
  • the estimated noise amplitude spectrum calculation unit 3 replaces the input amplitude spectrum 9 at that time (with the estimated noise amplitude spectrum up to that point) by, for example, the following equation (5). Then, the estimated noise amplitude spectrum 10 updated by weighting and adding is output.
  • ⁇ ( ⁇ ( ⁇ )) is the updated estimated noise amplitude spectrum
  • E old (N ( ⁇ )) is the estimated noise amplitude spectrum before updating
  • the subtraction 'filter unit 4 calculates the removal rate r based on the following equation (6), and outputs it as the noise removal strength 13.
  • POWs is the percentage of the amplitude spectrum of the input signal at all frequencies in the current frame.
  • POW N is the power of the estimated noise amplitude spectrum for all frequencies of the current frame 0 ⁇ r TH ⁇ 1
  • the input amplitude spectrum and the estimated noise amplitude spectrum are subtracted in the same manner as in equation (1), and the difference output amplitude spectrum 11 is output. I do.
  • the noise suppression is reduced by reducing the extraction rate for noise frames and low power frames such as consonants.
  • the output amplitude 12 returned to the time domain by the inverse Fourier transform unit 5 has a smaller amplitude adjustment coefficient in the next amplitude adjustment filter unit 6 in a frame having a small power, so that the amplitude suppression is enhanced.
  • the amplitude adjustment filter unit 6 is configured to perform steps 3 to 3 in FIG. Perform two actions.
  • the noise removal strength 13 (removal rate r) is input.
  • the difference between the power of the amplitude spectrum of the speech section of the input signal of the current frame and the power of the estimated noise amplitude spectrum of the current frame is obtained.
  • POWs is the power of the amplitude spectrum of all the frequencies of the input signal of the current frame
  • POWn is the power of the estimated noise amplitude spectrum of all the frequencies of the current frame
  • G is the amplitude suppression coefficient of the current frame.
  • R is the withdrawal rate. As shown in Fig. 17, when the withdrawal rate r is large, the amplitude suppression coefficient G increases. When the withdrawal rate r is small, the amplitude suppression coefficient G becomes small.
  • g (n) g (n-1) AR + G (1— AR) (8)
  • G (n) is the amplitude adjustment coefficient of the n-th sample of the current frame, and n-1 is the previous sample.
  • n-1 is the previous sample.
  • the amplitude suppression coefficient G increases, and the amplitude adjustment coefficient g (n) increases.
  • the removal ratio r is small, the amplitude suppression coefficient G becomes small, and the amplitude adjustment coefficient g (n) becomes small.
  • FIG. 4 is a diagram showing the input / output characteristics of the amplitude adjustment filter unit 6.
  • the extraction rate r is small, so that the amplitude adjustment coefficient g (n) is small, and the suppression on the output side is large, and the output value is large.
  • the amplitude adjustment coefficient g ( n ) is large because the withdrawal rate r is large in the voice section.
  • the suppression is small and the output value is relatively large.
  • the amount of noise removal in the frequency domain is reduced in a noise frame or a consonant voice frame having a small power, so that the generation of musical noise in the noise frame can be suppressed and the voice section can be prevented from being cut.
  • Figure 5 shows the amplitude spectrum of the noise frame before and after the subtraction.
  • the removal rate r When the removal rate r is set to 1.0 and the noise is largely removed, only the frequency component of the strong amplitude spectrum of the removed noise remains and becomes a source of musical noise.
  • the withdrawal rate r When the withdrawal rate r is set to 0.5 and the withdrawal is weakened, the deviation of the amplitude to a part of the frequency in the amplitude spectrum of the noise after the withdrawal is reduced, and no musical noise is generated.
  • the amplitude is suppressed accordingly, so that it is possible to prevent the noise suppression amount from becoming insufficient.
  • the amplitude adjustment coefficient is gradually changed in the time axis direction for each sample even in one frame by equation (8), so that Even if the amplitude is suddenly adjusted such as at the rising edge, a natural output can be obtained.
  • the amplitude adjustment may be performed in the frequency domain. That is, an amplitude adjustment filter section is provided after the Fourier transform, and the signal after the amplitude adjustment is subjected to the inverse Fourier transform. Configuration.
  • FIG. 6 is a block diagram showing a configuration of a spectral subtraction method according to the embodiment.
  • the configuration in FIG. 6 shows a configuration in which the amplitude adjustment filter in FIG. 1 is moved immediately after the subtraction filter 4 and the amplitude adjustment is performed in the frequency domain.
  • the operation is the same as that of mode 1.
  • the subtraction ′ filter unit 4 calculates the subtraction rate by the equation (6), and subtracts the estimated noise amplitude spectrum 10 from the input amplitude spectrum 9 based on the subtraction rate, Outputs the output amplitude spectrum.
  • the amplitude adjustment filter section 15 multiplies the amplitude adjustment coefficient calculated based on the withdrawal rate r by the output amplitude spectrum, and outputs a final output amplitude; spectrum.
  • the withdrawal strength is reduced in a noise frame or a voice frame having a low power such as a consonant
  • the generation of musical noise can be suppressed in the noise frame, and the deformation or disappearance of the consonant section can be prevented.
  • amplitude suppression is performed accordingly, so that it is possible to prevent shortage of noise suppression.
  • the amplitude adjustment coefficient need only be calculated once per frame, and it is not necessary to calculate the amplitude adjustment coefficient for each sample of the signal as in S3 of FIG. 2 of the first embodiment. .
  • the input signal since the input signal extracts the voice for each section divided by the predetermined frame, the input signal becomes discontinuous at the change point of the frame (section), which may cause abnormal noise. . In the present embodiment, this is Better to smooth signal changes between frames.
  • FIG. 7 is a block diagram showing a configuration of a spectral subtraction method according to Embodiment 3 of the present invention.
  • the input signal generation unit 19 and the waveform shaping processing unit 20 are new elements, and the other elements are the same as those in FIG. 1.
  • FIG. 8 shows an example of the input signal 7 in the noise reduction method according to the third embodiment.
  • FIG. 9 is a diagram illustrating a weighting function for multiplying the input signal performed by the input signal generation unit in the noise reduction method according to the third embodiment.
  • FIG. 10 is a diagram illustrating an example of an output signal 5 a of the inverse Fourier transform unit 5 in the noise reduction method according to the third embodiment.
  • FIG. 8 shows the time-series amplitude of the input signal 7 after the AD conversion, and this is input to the input signal generation unit 19.
  • a in Fig. 8 is the set section before the frame.
  • B and C in Fig. 8 are the set sections after the frame.
  • the weighted signal whose end approaches 0 is subjected to Fourier transform, so that the noise reduction capability is improved.
  • this system was implemented with a fixed-point arithmetic digital signal processor (fixed-point DSP (digital signal processor)), the signals at both ends (A and C in Fig. 18), whose accuracy deteriorates due to the weighting, are reduced. Since it is not used for waveform shaping, it is easy to ensure output accuracy and to prevent abnormal noise at frame boundaries.
  • fixed-point arithmetic digital signal processor fixed-point DSP (digital signal processor)
  • FIG. 11 is a block diagram showing a configuration of a spectral subtraction method according to Embodiment 4 of the present invention.
  • a withdrawal rate calculator 16 as a new element.
  • the other elements are the same as those with the same numbers in FIG.
  • FIG. 12 is a diagram illustrating an operation in the noise reduction method according to the present embodiment.
  • the solid line represents the input power P ⁇ Ws in the noise section
  • the dotted line represents the average noise power POW AVE
  • the chain line represents the noise section determination threshold POW TH .
  • POW TH is the threshold TH in the pre-noise frame described in equation (3).
  • This configuration has a configuration in which a removal rate calculation unit 16 is added to the overall configuration of the spectral subtraction of the conventional method.
  • the filter of the subtraction filter unit 4 performs the operation of equation (1).
  • the noise interval determination unit 2 calculates a noise interval determination threshold value POW TH , and determines that the noise frame is a noise frame when the input level falls below this threshold value.
  • the subtraction rate calculation unit 16 calculates the average power of a plurality of noise frames close to the current based on the determination result and sets the average power as the average noise power. Based on the following equation (12), the noise section determination threshold is determined. P ⁇ W TH , average noise power P
  • the magnitude r1 of this noise fluctuation is defined as the noise vector removal rate r in equation (1).
  • the noise section determination threshold POW TH value uses a high value that can be correctly determined as a noise section in the case of noise with large power fluctuations.
  • Figure 12 shows the changes in the average noise power and the noise section determination threshold with respect to the change in the input power in the noise section at this time.
  • the average noise power POW AVE of the noise frame takes a value smaller than the noise section determination threshold value POW TH . Therefore, the withdrawal rate r 1 is smaller than 1. As a result, the effect of suppressing the removal of the estimated noise amplitude spectrum can be obtained, the voice shaving can be reduced, and the estimated noise amplitude spectrum is updated normally.
  • FIG. 13 is a block diagram showing main components of a noise reduction method according to Embodiment 5 of the present invention.
  • FIG. 14 is a diagram illustrating an operation in the noise reduction method according to the present embodiment.
  • the noise is reduced by suppressing the amplitude in the noise section.
  • the amplitude adjustment coefficient for performing the amplitude suppression is determined depending on the current input power and the average noise power.
  • the noise interval determination unit 301 calculates the input power POWs 305 indicated by the solid line in FIG. 12 from the input signal 304, and performs the noise interval determination using the noise interval determination threshold POW TH similar to the first embodiment. Do.
  • the average noise power calculation section 302 calculates the average power of a plurality of past noise frames close to the current frame based on the result of the noise section determination, and calculates the average noise power P OW AVE 3 shown by the dotted line in FIG. 06.
  • the amplitude adjustment filter section 303 calculates the amplitude suppression coefficient G from the input power P ⁇ Ws 305 of the input signal and the average noise power P OW AVE 306 according to equation (13), and then directly adjusts the amplitude.
  • the output signal 307 is obtained by multiplying the input signal 304 by the obtained amplitude adjustment coefficient.
  • FIG. 14 shows the relationship between the input power P OWs 305 of the input signal 304 and the output power of the output signal 307 after the amplitude adjustment.
  • the dotted line in Fig. 14 shows the case where the input signal was output as it was without using the amplitude adjustment filter. That is, the dotted line indicates a case where the input power of the input signal is equal to the output power of the output signal.
  • the solid line shows the relationship between the input power POWs and the output power when the amplitude adjustment filter is used. This indicates that a value smaller than the dotted line is output by amplitude suppression. Also, when the input power is the average noise power P_ ⁇ _W AVE smaller than the output signal Pawa one indicates that zero.
  • the amplitude adjustment coefficient is determined from the result of the voice state determination. Frequently, as in the case of direct determination, the amplitude suppression does not change significantly, and the audio output stabilizes.
  • the withdrawal rate is made variable and the amplitude adjustment filter section that changes the degree of amplitude suppression based on this is provided, it is possible to prevent the voice section from being cut off.
  • the subtraction strength in a noise frame or the like is reduced, noise is suppressed by performing amplitude suppression corresponding to the strength, so that a balanced and easy-to-hear output can be obtained as a whole.
  • the amplitude adjustment coefficient gradually changes in the time axis direction even within a frame, a natural output can be obtained even when a sharp amplitude adjustment such as the rising of a voice section is performed.
  • the signals in the preceding and succeeding sections of the current frame are also multiplied by a weight function and added. Since the input signal generation unit includes the input signal generation unit, the target signal of the Fourier transform is weighted, the estimation accuracy of the noise spectrum is improved and the noise reduction effect is enhanced, and the unweighted signal of the inverse Fourier transform output is obtained. Is output as a frame signal, so that even with a fixed-point arithmetic digital signal processor, there is an effect that the arithmetic operation is small and high signal accuracy can be obtained.
  • the strength of noise removal is adjusted according to the variability of the section determined to be a noise section, so that even when the variability of noise is large, a correct noise determination threshold can be set. It also has the effect of preventing mixed speech components from squeezing the speech.
  • the output is caused by frequent changes in the noise section determination. This has the effect of avoiding adverse effects.

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  • Noise Elimination (AREA)

Abstract

L'invention concerne un procédé de réduction de bruits destiné à réduire des bruits résiduels déplaisants, même lorsqu'un mouvement vers des trames de bruit ou à partir de celles-ci est fréquent et que le spectre de chaque trame contient de manière inégale certaines fréquences. Ce procédé de réduction de bruits par soustraction spectrale consiste à produire une valeur de sortie, par soustraction au moyen d'un filtre de soustraction spectrale, d'un spectre d'amplitude de bruit estimé, à partir d'un spectre d'amplitude créé par transformation orthogonale d'un signal d'entrée segmenté pour présenter une longueur de trame déterminée. Dans ce procédé, le taux de soustraction du filtre de soustraction spectrale est variable en fonction du spectre d'amplitude de bruit estimé et on utilise un circuit (6) de filtrage et de réglage d'amplitude. Ce circuit (6) multiplie, pour chaque trame, la valeur de sortie produite par soustraction par le filtre de soustraction spectrale, par un coefficient de réglage d'amplitude, afin de produire une valeur de sortie voulue. Le coefficient de réglage d'amplitude est déterminé par la puissance du spectre d'amplitude (9) et par la puissance du spectre d'amplitude (10) de bruit estimé.
PCT/JP1998/005512 1998-03-30 1998-12-07 Dispositif et procede de reduction de bruits WO1999050825A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
EP98957196A EP0992978A4 (fr) 1998-03-30 1998-12-07 Dispositif et procede de reduction de bruits
AU13525/99A AU721270B2 (en) 1998-03-30 1998-12-07 Noise reduction apparatus and noise reduction method
CA002291826A CA2291826A1 (fr) 1998-03-30 1998-12-07 Dispositif et procede de reduction de bruits

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP10/84174 1998-03-30
JP8417498 1998-03-30

Publications (1)

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WO1999050825A1 true WO1999050825A1 (fr) 1999-10-07

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Application Number Title Priority Date Filing Date
PCT/JP1998/005512 WO1999050825A1 (fr) 1998-03-30 1998-12-07 Dispositif et procede de reduction de bruits

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Country Link
EP (1) EP0992978A4 (fr)
KR (1) KR100314332B1 (fr)
CN (1) CN1258368A (fr)
AU (1) AU721270B2 (fr)
CA (1) CA2291826A1 (fr)
WO (1) WO1999050825A1 (fr)

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WO2006064699A1 (fr) * 2004-12-17 2006-06-22 Waseda University Système de séparation de source sonore, méthode de séparation de source sonore et dispositif d’acquisition de signal acoustique
WO2006123721A1 (fr) * 2005-05-17 2006-11-23 Yamaha Corporation Procede de suppression de bruit et dispositif correspondant
US7706550B2 (en) 2004-01-08 2010-04-27 Kabushiki Kaisha Toshiba Noise suppression apparatus and method
JP2015002505A (ja) * 2013-06-18 2015-01-05 パイオニア株式会社 ノイズ低減装置、放送受信装置及びノイズ低減方法
US9318122B2 (en) 2014-04-18 2016-04-19 Fujitsu Limited Audio signal processing apparatus and audio signal processing method
US9754606B2 (en) 2012-05-01 2017-09-05 Ricoh Company, Ltd. Processing apparatus, processing method, program, computer readable information recording medium and processing system

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KR100686382B1 (ko) 2005-07-08 2007-02-22 엔에이치엔(주) 싱크 서버를 이용한 메신저 알림 시스템 및 방법
CN1822092B (zh) * 2006-03-28 2010-05-26 北京中星微电子有限公司 一种消除语音输入中背景噪声的方法及其装置
CN101166232B (zh) * 2006-10-19 2010-05-12 华晶科技股份有限公司 消除马达声音的方法及其数字影像撷取装置
WO2009038136A1 (fr) * 2007-09-19 2009-03-26 Nec Corporation Dispositif de suppression de bruit, son procédé et programme
US20120143604A1 (en) * 2010-12-07 2012-06-07 Rita Singh Method for Restoring Spectral Components in Denoised Speech Signals
JP6687453B2 (ja) * 2016-04-12 2020-04-22 パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカＰａｎａｓｏｎｉｃ Ｉｎｔｅｌｌｅｃｔｕａｌ Ｐｒｏｐｅｒｔｙ Ｃｏｒｐｏｒａｔｉｏｎ ｏｆ Ａｍｅｒｉｃａ ステレオ再生装置
JP6668995B2 (ja) 2016-07-27 2020-03-18 富士通株式会社 雑音抑圧装置、雑音抑圧方法及び雑音抑圧用コンピュータプログラム
CN108831500B (zh) * 2018-05-29 2023-04-28 平安科技（深圳）有限公司 语音增强方法、装置、计算机设备及存储介质

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7706550B2 (en) 2004-01-08 2010-04-27 Kabushiki Kaisha Toshiba Noise suppression apparatus and method
WO2006064699A1 (fr) * 2004-12-17 2006-06-22 Waseda University Système de séparation de source sonore, méthode de séparation de source sonore et dispositif d’acquisition de signal acoustique
JP2006197552A (ja) * 2004-12-17 2006-07-27 Univ Waseda 音源分離システムおよび音源分離方法、並びに音響信号取得装置
US8213633B2 (en) 2004-12-17 2012-07-03 Waseda University Sound source separation system, sound source separation method, and acoustic signal acquisition device
WO2006123721A1 (fr) * 2005-05-17 2006-11-23 Yamaha Corporation Procede de suppression de bruit et dispositif correspondant
US8160732B2 (en) 2005-05-17 2012-04-17 Yamaha Corporation Noise suppressing method and noise suppressing apparatus
JP4958303B2 (ja) * 2005-05-17 2012-06-20 ヤマハ株式会社 雑音抑圧方法およびその装置
US9754606B2 (en) 2012-05-01 2017-09-05 Ricoh Company, Ltd. Processing apparatus, processing method, program, computer readable information recording medium and processing system
JP2015002505A (ja) * 2013-06-18 2015-01-05 パイオニア株式会社 ノイズ低減装置、放送受信装置及びノイズ低減方法
US9318122B2 (en) 2014-04-18 2016-04-19 Fujitsu Limited Audio signal processing apparatus and audio signal processing method

Also Published As

Publication number Publication date
CA2291826A1 (fr) 1999-10-07
KR20000076037A (ko) 2000-12-26
AU1352599A (en) 1999-10-18
EP0992978A1 (fr) 2000-04-12
AU721270B2 (en) 2000-06-29
KR100314332B1 (ko) 2001-11-16
EP0992978A4 (fr) 2002-01-16
CN1258368A (zh) 2000-06-28

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