WO2012098579A1 - 雑音抑圧装置 - Google Patents
雑音抑圧装置 Download PDFInfo
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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
- H04R3/002—Damping circuit arrangements for transducers, e.g. motional feedback circuits
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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
- G10L21/0232—Processing in the frequency domain
Definitions
- the present invention relates to a noise suppression device that suppresses background noise superimposed on an input signal.
- a time domain input signal is converted into a power spectrum which is a frequency domain signal, and noise suppression is performed using the power spectrum of the input signal and an estimated noise spectrum separately estimated from the input signal.
- the amount of suppression for the input signal is calculated, the amplitude of the power spectrum of the input signal is suppressed using the obtained amount of suppression, and the noise-suppressed signal is converted by converting the amplitude-suppressed power spectrum and the phase spectrum of the input signal into the time domain (For example, refer nonpatent literature 1).
- the suppression amount is calculated based on the ratio (SN ratio) of the power spectrum of speech to the estimated noise power spectrum, but the noise superimposed on the input signal is somewhat steady in the time and frequency directions. It is effective under certain conditions, and when non-stationary noise is input in the time and frequency directions, the amount of suppression cannot be calculated correctly, and there is a problem that annoying artificial residual noise called a musical tone is generated. .
- musical noise can be generated even for non-stationary noise by setting a predetermined target spectrum in advance for stable noise suppression and controlling the amount of noise suppression so that the residual noise spectrum approaches it.
- a method for suppressing noise and performing natural and stable noise suppression is disclosed (for example, see Patent Document 2).
- FIG. 6 is a diagram schematically illustrating the conventional technique described in Patent Document 2.
- the vertical axis represents amplitude and the horizontal axis represents frequency (0 to 4000 Hz).
- the dotted line is an estimated noise spectrum
- the alternate long and short dash line is a predetermined target spectrum
- the solid line is a spectrum of residual noise that is an output signal after noise suppression is performed by the method of Patent Document 2
- the broken line is Patent Document 2 This is a spectrum of residual noise when the method is not introduced, that is, when suppression is performed with a constant suppression amount in the entire band.
- the maximum suppression amount for noise suppression is controlled so that the level of the residual noise spectrum matches the amplitude level of the target spectrum, the shape and power of the target spectrum are the same as the estimated noise spectrum of the input signal. If it is significantly different from the above, a band that is extremely over-suppressed and a band that is extremely under-suppressed are generated. As a result, there has been a problem that the sound is distorted and noisy.
- the present invention has been made to solve the above-described problems, and an object thereof is to provide a high-quality noise suppression device.
- the noise suppression device of the present invention calculates a suppression coefficient for noise suppression using a spectral component obtained by converting an input signal from the time domain to the frequency domain and an estimated noise spectrum estimated from the input signal, and the suppression coefficient Is used to suppress the amplitude of the spectral component of the input signal and generate a noise-suppressed signal converted to the time domain, obtaining statistical information representing the characteristics of the estimated noise spectrum, and based on the statistical information
- a correction spectrum calculation unit that corrects the estimated noise spectrum to generate a correction spectrum
- a suppression amount limitation coefficient that generates a suppression amount limitation coefficient that defines the upper and lower limits of noise suppression based on the correction spectrum generated by the correction spectrum calculation unit
- the noise spectrum estimated from the input signal is corrected to obtain a corrected spectrum, and the spectrum gain limiting process is performed using the suppression amount limiting coefficient obtained from the corrected spectrum. It is possible to provide a high-quality noise suppression device capable of performing excellent noise suppression without generating an excessively excessively suppressed or insufficiently suppressed band while suppressing generation.
- FIG. 3 is a block diagram illustrating an internal configuration of a correction spectrum calculation unit according to Embodiment 1.
- FIG. 3A is a graph schematically showing a state of smoothing processing in the correction spectrum calculation unit in the first embodiment
- FIG. 3A is an estimated noise spectrum before smoothing
- FIG. An estimated noise spectrum is shown.
- 3 is a block diagram illustrating an internal configuration of a suppression amount limiting coefficient calculation unit according to Embodiment 1.
- FIG. 6 is a graph schematically showing a state of a residual noise spectrum in which noise is suppressed by the noise suppression device according to the first embodiment.
- 10 is a graph schematically showing a state of a residual noise spectrum in which noise is suppressed by a noise suppression method according to Patent Document 2.
- FIG. 1 includes an input terminal 1, a Fourier transform unit 2, a power spectrum calculation unit 3, a voice / noise section determination unit 4, a noise spectrum estimation unit 5, a correction spectrum calculation unit 6, A suppression amount limiting coefficient calculation unit 7, an SN ratio calculation unit 8, a suppression amount calculation unit 9, a spectrum suppression unit 10, an inverse Fourier transform unit 11, and an output terminal 12 are provided.
- voice and music taken through a microphone are A / D (analog / digital) converted and then sampled at a predetermined sampling frequency (for example, 8 kHz). And a signal divided into frame units (for example, 10 ms) is used.
- the input terminal 1 receives the above signal and outputs it as an input signal to the Fourier transform unit 2.
- the Fourier transform unit 2 performs, for example, Hanning windowing on the input signal, and then performs a fast Fourier transform of 256 points as in the following equation (1), and from the time domain signal x (t), the spectral component X ( ⁇ , k).
- the obtained spectrum component X ( ⁇ , k) is output to the power spectrum calculation unit 3 and the spectrum suppression unit 10, respectively.
- ⁇ is a frame number when the input signal is divided into frames
- k is a number designating a frequency component in the frequency band of the power spectrum (hereinafter referred to as a spectrum number)
- FT [ ⁇ ] represents a Fourier transform process.
- T represents a discrete time number.
- the power spectrum calculation unit 3 calculates the power spectrum Y ( ⁇ , k) from the spectrum component X ( ⁇ , k) of the input signal using the following equation (2).
- the obtained power spectrum Y ( ⁇ , k) is output to the speech / noise section determination unit 4, the noise spectrum estimation unit 5, the suppression amount limiting coefficient calculation unit 7, and the SN ratio calculation unit 8, respectively.
- Re ⁇ X ( ⁇ , k) ⁇ and Im ⁇ X ( ⁇ , k) ⁇ represent a real part and an imaginary part of the input signal spectrum after Fourier transform, respectively.
- the voice / noise section determination unit 4 includes a power spectrum Y ( ⁇ , k) output from the power spectrum calculation unit 3 and an estimated noise spectrum N ( ⁇ estimated one frame before output from a noise spectrum estimation unit 5 described later. ⁇ 1, k) is used as an input to determine whether the input signal of the current frame ⁇ is speech or noise, and the result is output as a determination flag. The determination flag is output to the noise spectrum estimation unit 5 and the corrected spectrum calculation unit 6, respectively.
- the determination flag Vflag is determined to be a voice. Is set to “1 (speech)”, and in other cases, the determination flag Vflag is set to “0 (noise)” as noise.
- N ( ⁇ 1, k) is the estimated noise spectrum of the previous frame
- S pow and N pow are the sum of the power spectrum of the input signal and the sum of the estimated noise spectrum, respectively.
- ⁇ max ( ⁇ ) is the maximum value of the normalized autocorrelation function.
- Equation (5) is a Wiener-Khintchin theorem, and will not be described.
- the maximum value ⁇ max ( ⁇ ) of the normalized autocorrelation function can be obtained using the following equation (6).
- a known method such as cepstrum analysis can be used in addition to the method shown in the above equation (3).
- the noise spectrum estimation unit 5 uses the power spectrum Y ( ⁇ , k) output from the power spectrum calculation unit 3 and the determination flag Vflag output from the speech / noise section determination unit 4 as inputs, and the following equation (7)
- the noise spectrum is estimated and updated according to the determination flag Vflag, and the estimated noise spectrum N ( ⁇ , k) of the current frame is output.
- the estimated noise spectrum N ( ⁇ , k) is output to the corrected spectrum calculation unit 6, the suppression amount limit coefficient calculation unit 7 and the SN ratio calculation unit 8, respectively, and also to the voice / noise section determination unit 4 as described above. It is output as the estimated noise spectrum N ( ⁇ -1, k) of the previous frame.
- N ( ⁇ -1, k) is an estimated noise spectrum in the previous frame, and is held in storage means (not shown) such as a RAM (Random Access Memory) in the noise spectrum estimation unit 5.
- ⁇ is an update coefficient, and is a predetermined constant in the range of 0 ⁇ ⁇ 1.
- the correction spectrum calculation unit 6 uses the determination flag Vflag output from the speech / noise section determination unit 4 and the estimated noise spectrum N ( ⁇ , k) output from the noise spectrum estimation unit 5 as inputs, and controls the amount of suppression described later.
- a correction spectrum R ( ⁇ , k) necessary for calculating the coefficient is calculated.
- the obtained correction spectrum R ( ⁇ , k) is output to the suppression amount limiting coefficient calculation unit 7.
- This correction spectrum R ( ⁇ , k) is used for determining the frequency characteristic of the suppression amount limiting coefficient in the suppression amount limiting coefficient calculating unit 7 described later.
- the correction spectrum calculation unit 6 illustrated in FIG. 2 includes a noise spectrum analysis unit 61, a noise spectrum correction unit 62, and a correction spectrum update unit 63.
- the noise spectrum analysis unit 61 calculates the variance V ( ⁇ ) of the current frame and outputs it to the noise spectrum correction unit 62 as an analysis result.
- the noise spectrum correction unit 62 uses the variance V ( ⁇ ) output from the noise spectrum analysis unit 61 and the determination flag Vflag output from the speech / noise section determination unit 4 as statistical information, and uses the estimated noise spectrum N ( ⁇ , k) is corrected (smoothed), and the corrected estimated noise spectrum N ⁇ ( ⁇ , k) is output.
- a median filter such as the following equation (9) is used, and the filter is switched according to the magnitude of the variance V ( ⁇ ).
- the median filter is a process of performing smoothing by rearranging signals in a predetermined area in order of power and taking the median value.
- ⁇ (overline) in the following formula (9) is expressed as “ ⁇ ” in the relationship with the electronic application, and “ ⁇ ” is also expressed in the explanation of formulas shown below.
- F sm [N ( ⁇ , k), L] represents a median filter. L indicates the size of the region. The larger the region L, the stronger the degree of smoothing by the median filter.
- V H and V L are predetermined thresholds for switching filters having a relationship of V H > V L , and V H means a case where dispersion is large, that is, a variation in spectrum is extremely large, VL means a case where the spectral variation is recognized although the spectral variation is not larger than that of V H , and can be appropriately changed according to the type of noise input and its level.
- Vflag 1 since the current frame is speech, the smoothed estimated noise spectrum N ⁇ ( ⁇ 1, k) of the previous frame is output. By doing so, excessive smoothing can be stopped and the influence on the correction spectrum can be prevented when an audio signal is erroneously mixed in the estimated noise spectrum, so that good noise suppression is possible.
- the smoothed estimated noise spectrum N ⁇ ( ⁇ -1, k) of the previous frame is stored in storage means (not shown) such as a RAM in the correction spectrum calculation unit 6, for example.
- FIG. 3 schematically shows the processing of the noise spectrum correction unit 62.
- FIG. 3A shows an input estimated noise spectrum N ( ⁇ , k)
- FIG. 3B shows an output.
- This is an estimated noise spectrum N ⁇ ( ⁇ , k) smoothed by a median filter.
- FIG. 3 in the smoothed estimated noise spectrum N ⁇ ( ⁇ , k), fine irregularities that cause annoying musical tone of residual noise are reduced, and sharp peaks and valleys disappear. I understand.
- the median filter is switched by classifying into two levels of V H and V L using spectral dispersion.
- the present invention is not limited to this method.
- a moving average filter and other known smoothing filters may be used as the filter, and the filter switching conditions may be further subdivided or continuously changed.
- all the elements of the filter processing of the above formula (9) have uniform weights, but non-uniform weighting may be performed. For example, it is conceivable that the spectral components are heavily weighted.
- the variance of the estimated noise spectrum by the noise spectrum analysis unit 61 is used as a means for analyzing the variance of the spectrum.
- known analysis means such as spectrum entropy is used. May be used, or a plurality of methods may be used in combination.
- the filter switching threshold in this case may be adjusted as appropriate according to the analysis means to be used and the analysis means to be combined.
- spectrum dispersion that is, variability in the frequency direction is detected and spectrum smoothing control is performed.
- variability in the time direction can be taken into account. If the difference in power between the frame and the current frame is calculated and exceeds the predetermined threshold value, smoothing may be considered.
- the corrected spectrum updating unit 63 outputs the analysis result (spectrum variance V ( ⁇ )) output by the noise spectrum analyzing unit 61 and the smoothed estimated noise spectrum N ⁇ ( ⁇ , k) output by the noise spectrum correcting unit 62.
- the minimum gain amount (maximum suppression amount in noise suppression) GMIN is used as an input to generate and output a correction spectrum R ( ⁇ , k).
- This correction spectrum R ( ⁇ , k) is generated by the following equation (10).
- ⁇ is a predetermined inter-frame smoothing coefficient
- ⁇ 0.9 is a suitable value, but the value of ⁇ can also be changed according to the value of variance V ( ⁇ ).
- V ( ⁇ ) the value of variance
- the correction spectrum update is stopped by outputting the correction spectrum R ( ⁇ k, k) of the previous frame.
- the correction spectrum R ( ⁇ 1, k) of the previous frame is stored in a storage unit (not shown) such as a RAM in the suppression amount limit coefficient calculation unit 7.
- the inter-frame smoothing coefficient ⁇ can be set to a different value for each frequency. For example, by decreasing the value from the low range to the high range, the frequency / time variation can be reduced. The update speed of large high frequency components can be increased.
- the suppression amount limiting coefficient calculation unit 7 includes a correction spectrum R ( ⁇ 1, k) output from the correction spectrum calculation unit 6 and a power spectrum Y ( ⁇ , k) output from the power spectrum calculation unit 3.
- the minimum gain amount GMIN which is a predetermined value set by the user, is used as an input in the same manner as in the corrected spectrum updating unit 63 in FIG. 2, and correction is performed so as to match the estimated noise spectrum N ( ⁇ , k) in the current frame.
- the gain of the spectrum R ( ⁇ , k) is corrected, and the result is output as the suppression amount limiting coefficient G floor ( ⁇ , k).
- the obtained suppression amount limiting coefficient G floor ( ⁇ , k) is output to the suppression amount calculation unit 9.
- the power calculation unit 71 illustrated in FIG. 4 includes a power calculation unit 71 and a coefficient correction unit 72.
- the power calculation unit 71 calculates the power POW R ( ⁇ ) of the correction spectrum R ( ⁇ , k) output from the correction spectrum calculation unit 6 according to the following equation (11), and the noise spectrum estimation unit 5 outputs The power POW N ( ⁇ ) of the estimated noise spectrum N ( ⁇ , k) to be calculated is calculated. These powers POW R ( ⁇ ) and POW N ( ⁇ ) are output to the coefficient correction unit 72.
- POW R ( ⁇ ) is the power of the correction spectrum R ( ⁇ , k) of the current frame
- POW N ( ⁇ ) is the power of the estimated noise spectrum N ( ⁇ , k) of the current frame
- N 128.
- the coefficient correction unit 72 compares the power POW R ( ⁇ ) of the correction spectrum with a value obtained by multiplying the power POW N ( ⁇ ) of the estimated noise spectrum by the minimum gain amount GMIN in accordance with the following equation (12).
- the correction amount D ( ⁇ ) of the correction spectrum R ( ⁇ , k) is determined according to the result.
- D UP 1.2
- D DOWN 0.8
- the power of the entire band is obtained by the above equation (11).
- some band components for example, power of 200 Hz to 800 Hz are obtained. It is also possible to make a comparison using the above equation (12).
- the coefficient correction unit 72 corrects the gain of the correction spectrum R ( ⁇ , k) using the correction amount D ( ⁇ ) obtained by the following equation (13), and the correction spectrum whose gain has been corrected.
- R ⁇ ( ⁇ , k) is obtained.
- the correction spectrum R ⁇ ( ⁇ , k) whose gain has been corrected is output to the correction spectrum calculation unit 6 and is handled as the correction spectrum R ( ⁇ -1, k) of the previous frame.
- “ ⁇ ” (hat symbol) in the following formula (13) is expressed as “ ⁇ ”, and also in the explanation of the following formulas, “ ⁇ ”.
- the coefficient correction unit 72 uses the corrected spectrum R ⁇ ( ⁇ , k) whose gain has been corrected and the power spectrum Y ( ⁇ , k) of the input signal output from the power spectrum calculation unit 3 as inputs.
- the suppression amount limiting coefficient G floor ( ⁇ , k) is calculated by the equations (14) and (15).
- the following expression (14) is an expression that determines the upper limit and the lower limit of the suppression amount
- the following expression (15) is an expression that performs interframe smoothing of the suppression amount limiting coefficient.
- the obtained suppression amount limiting coefficient G floor ( ⁇ , k) is output to the suppression amount calculation unit 9.
- GMAX is a predetermined constant equal to or less than 1 which is the maximum gain amount, that is, the minimum suppression amount of the noise suppression device.
- ⁇ represents a predetermined smoothing coefficient
- ⁇ 0.1 is preferable.
- the SN ratio calculation unit 8 includes a power spectrum Y ( ⁇ , k) output from the power spectrum calculation unit 3, an estimated noise spectrum N ( ⁇ , k) output from the noise spectrum estimation unit 5, and will be described later. Calculates the a posteriori SNR (a postoriori SNR) and a priori SNR (a priori SNR) for each spectral component using the spectrum suppression amount G ( ⁇ -1, k) of the previous frame output from the suppression amount calculation unit 9 as an input. To do.
- the a posteriori SNR ⁇ ( ⁇ , k) can be obtained from the following equation (16) using the power spectrum Y ( ⁇ , k) and the estimated noise spectrum N ( ⁇ , k).
- the prior SNR ⁇ ( ⁇ , k) is calculated using the following expression (17) using the spectral suppression amount G ( ⁇ 1, k) of the previous frame and the a posteriori SNR ⁇ ( ⁇ 1, k) of the previous frame. It can be obtained more.
- F [ ⁇ ] means half-wave rectification, and when the posterior SNR ⁇ ( ⁇ , k) is negative in decibels, the value is floored to zero.
- the obtained posterior SNR ⁇ ( ⁇ , k) and prior SNR ⁇ ( ⁇ , k) are each output to the suppression amount calculation unit 9.
- the suppression amount calculation unit 9 includes a prior SNR ⁇ ( ⁇ , k) and a posteriori SNR ⁇ ( ⁇ , k) output from the SN ratio calculation unit 8, and a suppression amount restriction coefficient G floor ( ⁇ ) output from the suppression amount restriction coefficient calculation unit 7. , K) as an input, a spectrum suppression amount G ( ⁇ , k), which is a noise suppression amount for each spectrum, is obtained. The obtained spectrum suppression amount G ( ⁇ , k) is output to the spectrum suppression unit 10.
- the Joint MAP method is a method for estimating a spectrum suppression amount G ( ⁇ , k) on the assumption that a noise signal and a speech signal are Gaussian distributions.
- the spectrum suppression amount G ( ⁇ , k) can be expressed by the following equation (18) using ⁇ and ⁇ that determine the shape of the probability density function as parameters.
- the suppression amount calculation unit 9 obtains the temporary spectrum suppression amount G ⁇ ( ⁇ , k) by the above equation (18), and then calculates the suppression amount limiting coefficient G floor ( ⁇ , k) and the following equation (19). Using this, the minimum value of the spectrum gain is restricted (flooring process), and the spectrum suppression amount G ( ⁇ , k) is obtained.
- the spectrum suppression unit 10 uses the spectrum suppression amount G ( ⁇ , k) output from the suppression amount calculation unit 9 as an input, and uses the spectrum component X ( ⁇ , k) of the input signal as its spectrum according to the following equation (20).
- the speech signal spectrum S ( ⁇ , k) with noise suppression is obtained by suppressing each time.
- the obtained audio signal spectrum S ( ⁇ , k) is output to the inverse Fourier transform unit 11.
- the inverse Fourier transform unit 11 performs inverse Fourier transform using the audio signal spectrum S ( ⁇ , k) output from the spectrum suppression unit 10 and the phase spectrum of the audio signal, and after superimposing the output signal on the previous frame.
- the noise-suppressed audio signal s (t) is output to the output terminal 12.
- the output terminal 12 outputs the audio signal s (t) whose noise is suppressed to the outside.
- FIG. 5 is a diagram schematically illustrating an example of a residual noise spectrum (that is, a voice signal spectrum S ( ⁇ , k)) that is an output signal of the noise suppression device according to the first embodiment. Similar to FIG. 6 described earlier, the dotted line is the estimated noise spectrum, and the broken line is the residual noise spectrum when the entire band is suppressed with a constant suppression amount. On the other hand, the solid line is a residual noise spectrum in which noise suppression is performed by the noise suppression apparatus according to the first embodiment.
- a residual noise spectrum that is, a voice signal spectrum S ( ⁇ , k)
- the actual noise environment for example, the running noise observed in the passenger compartment when the car is running, has a complex peak due to wind noise and engine acceleration noise, and often does not have a simple downward-sloping shape.
- the conventional method determines the overall suppression amount so that the residual noise after noise suppression processing matches the shape of a predetermined target spectrum. In some cases, an extremely excessively suppressed band or an insufficiently suppressed band appears.
- the suppression amount limiting coefficient G floor ( ⁇ , k) is calculated from the noise spectrum N ( ⁇ , k) estimated from the input signal.
- the noise suppression apparatus includes the Fourier transform unit 2 that converts an input signal in the time domain into a spectrum component in the frequency domain, and the power spectrum calculation unit 3 that calculates a power spectrum from the spectrum component.
- a speech / noise interval determination unit 4 for determining a noise interval of the input signal, a noise spectrum estimation unit 5 for estimating a noise spectrum from the input signal in the noise interval, a variance value representing a degree of variation of the estimated noise spectrum, and a variance
- a correction spectrum calculation unit 6 that corrects the estimated noise spectrum based on the value and the determination result of the voice / noise interval to generate a correction spectrum, and a suppression amount limiting coefficient that defines the upper and lower limits of noise suppression based on the correction spectrum
- Suppression amount limiting coefficient calculation unit 7 for generating SNR
- SN ratio calculation unit 8 for calculating the S / N ratio of the estimated noise spectrum, S / N ratio and suppression
- a suppression amount calculation unit 9 that controls the suppression coefficient using the amount limiting coefficient, a spectrum suppression unit 10 that suppresse
- the correction spectrum calculation unit 6 is good by controlling the correction amount by changing the filter or changing the number of processes according to the variance value of the estimated noise spectrum. Noise suppression is possible.
- a correction process with respect to an estimated noise spectrum either or both of frequency direction smoothing and inter-frame smoothing can be performed. By correcting the frequency direction smoothing, the unevenness of each noise frequency can be reduced and the generation of musical tone can be suppressed.
- inter-frame smoothing correction it is possible to follow a sudden change in noise in the input signal. Therefore, better noise suppression is possible.
- the correction spectrum calculation unit 6 stops the correction of the estimated noise spectrum when the variance value of the estimated noise spectrum is equal to or smaller than a predetermined threshold, or the voice / noise section determination unit. Since the correction is stopped when it is determined that the voice section is determined by No. 4, excessive smoothing can be stopped, and the influence on the correction spectrum when the voice signal is erroneously mixed in the estimated noise spectrum. Can be prevented, and better noise suppression can be achieved.
- the correction spectrum calculation unit 6 performs correction that increases the smoothing as the frequency increases with respect to the estimated noise spectrum, so that the high-frequency component irregularities with large noise disturbances are obtained. Can be further mitigated, and better noise suppression can be achieved. Furthermore, by reducing the update rate of the correction spectrum as it goes from the low range to the high range, the update rate of the high frequency component having a large frequency / time change can be increased, and further noise suppression can be achieved.
- the correction spectrum calculation unit 6 generates a correction spectrum using the smoothed estimated noise spectrum according to the above equation (10). For example, a predetermined correction spectrum is learned in advance. If the initial state of operation and noise in the input signal change suddenly, a predetermined correction spectrum learned in advance may be used for input instead of the smoothed estimated noise spectrum. Good. With this configuration, when the initial state and the input signal change suddenly, the learning convergence speed of the correction spectrum can be increased, and the change in the sound quality of the output signal can be minimized. Also, a small amount of a predetermined correction spectrum that has been learned in advance may be mixed into the correction spectrum obtained by the above equation (10). By mixing a small amount of the predetermined correction spectrum, overlearning of the correction spectrum can be suppressed (the correction spectrum is forgotten gradually), and further excellent noise suppression can be performed.
- the case where the maximum posterior probability method (MAP method) is used as the noise suppression method by the suppression amount calculation unit 9 and the spectrum suppression unit 10 has been described as an example.
- the present invention is limited to this method.
- the present invention can be applied to other methods.
- the minimum mean square error short time spectral amplitude method detailed in Non-Patent Document 1, F. Boll, "Subpression of Acoustical Noise in Spectating Usage Subtraction” (IEEE Trans. On ASSP, Vol. 27, No. 2, pp. 113-120, Apr. 1979). .
- the suppression amount control is performed for the entire band of the input signal.
- the present invention is not limited to this.
- only the low band or the high band may be controlled as necessary.
- only a specific frequency band such as only in the vicinity of 500 to 800 Hz may be controlled.
- Such suppression amount control for a limited frequency band is effective for narrow band noise such as wind noise and automobile engine sound.
- the noise suppression target is not limited to the narrowband telephone voice.
- the broadband telephone voice and acoustic signal of 0 to 8000 Hz are used. It can also be applied to.
- the noise-suppressed audio signal is transmitted in a digital data format to various audio-acoustic processing devices such as an audio encoding device, an audio recognition device, an audio storage device, and a hands-free call device.
- the noise suppression device according to the first embodiment can be realized by a DSP (digital signal processor) alone or together with the other devices described above, or by being executed as a software program.
- the program may be stored in a storage device of a computer that executes the software program, or may be distributed in a storage medium such as a CD-ROM. It is also possible to provide a program through a network.
- D / A digital / analog
- the present invention can be modified with any constituent element of the embodiment or omitted with any constituent element of the embodiment.
- the noise suppression device is capable of high-quality noise suppression, a voice communication system such as a car navigation system, a mobile phone, and an interphone, in which a voice communication / sound storage / recognition system is introduced. -Suitable for use in improving the sound quality of hands-free call systems, video conference systems, monitoring systems, etc., and improving the recognition rate of voice recognition systems.
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Abstract
Description
図6は特許文献2に記載の従来技術について模式的に説明する図であり、縦軸は振幅、横軸は周波数(0~4000Hz)を示す。また、図6において、点線は推定雑音スペクトル、一点鎖線は所定の目標スペクトル、実線は特許文献2の方法により雑音抑圧を行った後の出力信号である残留雑音のスペクトル、破線は特許文献2の方法を導入しない場合、即ち、全帯域一定の抑圧量で抑圧した場合の残留雑音のスペクトルである。特許文献2の方法では残留雑音のスペクトルのレベルを目標スペクトルの振幅レベルに合うように、雑音抑圧のための最大抑圧量を制御するので、目標スペクトルの形状およびパワーが入力信号の推定雑音スペクトルのそれと大きく異なった場合、極端に抑圧過剰な帯域、および極端に抑圧不足な帯域が発生する。その結果、音声に歪みおよび雑音感が生じる課題があった。
実施の形態1.
図1に示す雑音抑圧装置は、入力端子1と、フーリエ変換部2と、パワースペクトル計算部3と、音声・雑音区間判定部4と、雑音スペクトル推定部5と、補正スペクトル計算部6と、抑圧量制限係数計算部7と、SN比計算部8と、抑圧量計算部9と、スペクトル抑圧部10と、逆フーリエ変換部11と、出力端子12とを備える。
入力端子1は、上述のような信号を受け付けて、入力信号としてフーリエ変換部2へ出力する。
ここで、λは入力信号をフレーム分割したときのフレーム番号、kはパワースペクトルの周波数帯域の周波数成分を指定する番号(以下、スペクトル番号を称する)、FT[・]はフーリエ変換処理を表す。また、tは離散時間番号を表す。
ここで、Re{X(λ,k)}およびIm{X(λ,k)}は、それぞれフーリエ変換後の入力信号スペクトルの実数部および虚数部を表す。
先ず、次の式(5)を用いて、パワースペクトルY(λ,k)から正規化自己相関関数ρN(λ,τ)を求める。
ここで、τは遅延時間であり、FT[・]は上述と同じフーリエ変換処理を表し、例えば上式(1)と同じポイント数=256にて高速フーリエ変換を行えばよい。なお、式(5)はウィナーヒンチン(Wiener-Khintchine)の定理であるので説明は省略する。
ここで、上式(6)は、τ=16~96の範囲で正規化自己相関関数ρN(λ,τ)の最大値を検索することを意味している。なお、自己相関関数の分析には、上式(3)に示した方法の他、ケプストラム分析など公知の手法を用いることができる。
ここで、N(λ-1,k)は前フレームにおける推定雑音スペクトルであり、雑音スペクトル推定部5内のRAM(Random Access Memory)などの記憶手段(不図示)に保持されている。また、αは更新係数であり、0<α<1の範囲の所定の定数である。好適な例としてはα=0.95であるが、入力信号の状態および雑音レベルに応じて適宜変更することもできる。
一方、判定フラグVflag=1の場合には、現フレームの入力信号が雑音ではなく音声と判定されていることから、前フレームの推定雑音スペクトルN(λ-1,k)をそのまま現フレームの推定雑音スペクトルN(λ,k)として出力する。
この補正スペクトルR(λ,k)は、後述する抑圧量制限係数計算部7において、抑圧量制限係数の周波数特性を決めるために用いる。
図2に示す補正スペクトル計算部6は、雑音スペクトル分析部61と、雑音スペクトル補正部62と、補正スペクトル更新部63とを備える。
ここで、Nはスペクトルの個数であり、N=128とする。また、NAVE(λ)は現フレームλの推定雑音スペクトルN(λ)の平均を表す。
推定雑音スペクトルの補正には、例えば次の式(9)のようなメディアンフィルタ(median filter)を用い、分散V(λ)の大きさに応じてフィルタを切り替える。なお、メディアンフィルタとは、所定の領域内の信号をパワーの大きさ順に並べ替えを行い、その中央値をとることによって平滑化を行う処理である。
ここでは電子出願の関係上、下式(9)中の“ ̄”(オーバーライン)を“ ̄”と表記し、これ以降に示す式の説明でも“ ̄”と表記する。
ここで、Fsm[N(λ,k),L]はメディアンフィルタを表す。Lは領域の大きさを示し、領域Lが大きくなる程メディアンフィルタによる平滑化の度合いが強くなる。また、VHおよびVLは、VH>VLの関係を持ったフィルタを切り替えるための所定の閾値であり、VHは分散が大きい、即ちスペクトルのばらつきが極めて大きい場合を意味し、他方のVLはスペクトルのばらつきがVHの場合よりは大きくないものの、スペクトルのばらつきが認められる場合を意味し、それぞれ入力される雑音の種類およびそのレベルに応じて適宜変更することができる。
また、分散V(λ)が小さい場合(VL>V(λ))には、推定雑音スペクトルの平滑化を行わない。また、判定フラグVflag=1の場合は、現フレームが音声であるので、前フレームの平滑化した推定雑音スペクトルN ̄(λ-1,k)を出力する。こうすることで、過度の平滑化を止め、かつ、推定雑音スペクトルに音声信号が誤って混入した場合に補正スペクトルへの影響を防止することができるので、良好な雑音抑圧が可能となる。
なお、前フレームの平滑化した推定雑音スペクトルN ̄(λ-1,k)は、例えば補正スペクトル計算部6内のRAMなどの記憶手段(不図示)にて記憶されている。
図3より、平滑化した推定雑音スペクトルN ̄(λ,k)には、残留雑音の耳障りなミュージカルトーンの要因となる細かな凹凸が軽減すると共に、鋭いピークおよび谷が消失していることが分かる。
また、スペクトルの分散に応じてフィルタの種類を切り替える代わりに、例えば領域L=3のメディアンフィルタを複数回掛けることにより平滑化を強めるといったことも可能である。さらに、上式(9)のフィルタ処理の各要素はすべて重みが均一であるが、非均一な重み付けを行ってもよく、例えば、当該スペクトル成分に大きく重み付けすることが考えられる。
なお、フィルタの種類および平滑化強度によっては、平滑化前後で推定雑音スペクトルの低域と高域のパワーのバランスが変わることがあるが、この場合には周波数イコライザおよび強調フィルタなどを用いてスペクトルの傾斜などを適宜調整すればよい。
ここで、αは所定のフレーム間平滑化係数であり、α=0.9が好適な値であるが、分散V(λ)の値に応じてαの値も変更することが可能である。例えば、分散が大きい場合には、αを小さくすることで補正スペクトルの更新速度を早めることができ、入力信号中の雑音の急激な変化に追従することができる。また、判定フラグVflag=1の場合には雑音ではなく音声であるので、前フレームの補正スペクトルR(λ-k,k)を出力することで、補正スペクトルの更新を停止する。
なお、前フレームの補正スペクトルR(λ-1,k)は、抑圧量制限係数計算部7内のRAMなどの記憶手段(不図示)に記憶されている。
図4に示すパワー計算部71は、パワー計算部71と、係数補正部72とを備える。
ここで、POWR(λ)は現フレームの補正スペクトルR(λ,k)のパワー、POWN(λ)は現フレームの推定雑音スペクトルN(λ,k)のパワーであり、また、N=128である。
ここで、DUPおよびDDOWNは所定の定数であり、本実施の形態1ではDUP=1.05,DDOWN=0.95がそれぞれ好適であるが、雑音の種類および雑音レベルに応じて適宜変更することができる。また、DUP,DDOWNの値はそれぞれ1種類だけに限らず、複数個用いて修正量D(λ)を決定してもよい。例えば、上式(12)ではパワーの大小比較だけで修正量D(λ)を決定しているが、パワーの差が所定の閾値より大きい(または小さい)場合に、DUP=1.2(または小さい場合にDDOWN=0.8)として、より大きな修正量を設定することができる。このように、パワーの差によって修正量D(λ)の値を変更することで、修正誤差をより小さくすると共に、修正速度も早くすることができる。
なお、ここでは電子出願の関係上、下式(13)中の“^”(ハット記号)を“^”と表記し、これ以降に示す式の説明でも“^”と表記する。
ここで、GMAXは最大ゲイン量、即ち、雑音抑圧装置の最小の抑圧量となる1以下の所定の定数である。また、βは所定の平滑化係数を表し、β=0.1が好適である。
ここで、δは忘却係数であって0<δ<1の範囲の所定の定数であり、本実施の形態1ではδ=0.98が好適である。また、F[・]は半波整流を意味し、事後SNRγ(λ,k)がデシベル値で負の場合に値をゼロにフロアリング(flooring)するものである。
逆フーリエ変換部11は、スペクトル抑圧部10が出力する音声信号スペクトルS(λ,k)と、音声信号の位相スペクトルとを用いて逆フーリエ変換し、前フレームの出力信号と重ね合わせ処理した後、雑音抑圧された音声信号s(t)を出力端子12へ出力する。
出力端子12は、雑音抑圧された音声信号s(t)を外部へ出力する。
なお、推定雑音スペクトルに対する補正処理としては、周波数方向平滑化およびフレーム間平滑化のいずれか一方、またはその両方を行うことができる。周波数方向平滑化の補正を行うことにより、雑音の周波数毎の凹凸を軽減してミュージカルトーンの発生を抑制できる。また、フレーム間平滑化の補正を行うことにより、入力信号中の雑音の急激な変化に追従することができる。よって、更に良好な雑音抑圧が可能である。
さらに、補正スペクトルの更新速度を低域から高域になるに従って小さくすることにより、周波数・時間変化の大きな高域成分の更新速度を速めることができ、更に良好な雑音抑制が可能となる。
また、上式(10)で得られた補正スペクトルに対し、予め学習しておいた所定の補正スペクトルを常時少量混入してもよい。所定の補正スペクトルを少量混入することで、補正スペクトルの過学習を抑制する(補正スペクトルを徐々に忘却する)ことができ、更に良好な雑音抑圧を行うことが可能となる。
さらに、図示例では狭帯域電話(0~4000Hz)の場合について説明しているが、雑音抑圧対象は狭帯域電話音声に限定されるものではなく、例えば0~8000Hzの広帯域電話音声および音響信号に対しても適用可能である。
Claims (5)
- 入力信号を時間領域から周波数領域へ変換したスペクトル成分と、当該入力信号から推定した推定雑音スペクトルとを用いて雑音抑圧のための抑圧係数を算出し、当該抑圧係数を用いて当該入力信号のスペクトル成分を振幅抑圧し、時間領域へ変換した雑音抑圧信号を生成する雑音抑圧装置において、
前記推定雑音スペクトルの特徴を表す統計的情報を求め、当該統計的情報に基づいて前記推定雑音スペクトルを補正して補正スペクトルを生成する補正スペクトル計算部と、
前記補正スペクトル計算部が生成した補正スペクトルに基づいて、前記雑音抑圧の上下限を規定する抑圧量制限係数を生成する抑圧量制限係数計算部と、
前記抑圧量制限係数計算部が生成した抑圧量制限係数を用いて、前記抑圧係数を制御する抑圧量計算部とを備えることを特徴とする雑音抑圧装置。 - 前記補正スペクトル計算部は、統計的情報の値に応じて、推定雑音スペクトルの補正量を制御することを特徴とする請求項1記載の雑音抑圧装置。
- 前記補正スペクトル計算部は、統計的情報の値が所定の閾値以下の場合、推定雑音スペクトルの補正を停止することを特徴とする請求項1記載の雑音抑圧装置。
- 前記補正スペクトル計算部は、推定雑音スペクトルに対して、周波数方向平滑化およびフレーム間平滑化のいずれか一方、またはその両方の補正を行うことを特徴とする請求項1記載の雑音抑圧装置。
- 前記補正スペクトル計算部は、推定雑音スペクトルに対して、周波数が高くなるに従って平滑化が強くなる補正を行うことを特徴とする請求項1記載の雑音抑圧装置。
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- 2011-01-19 WO PCT/JP2011/000257 patent/WO2012098579A1/ja active Application Filing
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JP2014051149A (ja) * | 2012-09-05 | 2014-03-20 | Yamaha Corp | エンジン音加工装置 |
JP2015025913A (ja) * | 2013-07-25 | 2015-02-05 | 沖電気工業株式会社 | 音声信号処理装置及びプログラム |
EP2916322A1 (en) | 2014-03-03 | 2015-09-09 | Fujitsu Limited | Voice processing device, noise suppression method, and computer-readable recording medium storing voice processing program |
US9761244B2 (en) | 2014-03-03 | 2017-09-12 | Fujitsu Limited | Voice processing device, noise suppression method, and computer-readable recording medium storing voice processing program |
US10109291B2 (en) | 2016-01-05 | 2018-10-23 | Kabushiki Kaisha Toshiba | Noise suppression device, noise suppression method, and computer program product |
Also Published As
Publication number | Publication date |
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JP5265056B2 (ja) | 2013-08-14 |
CN103238183A (zh) | 2013-08-07 |
US20130216058A1 (en) | 2013-08-22 |
DE112011104737B4 (de) | 2015-06-03 |
US8724828B2 (en) | 2014-05-13 |
JPWO2012098579A1 (ja) | 2014-06-09 |
CN103238183B (zh) | 2014-06-04 |
DE112011104737T5 (de) | 2013-11-07 |
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