Noise suppression device Number:7,043,030 from the United States Patent and Trademark Office (PTO) owispatent A noise suppressor device for attaining perceptually preferable noise suppression is disclosed. The device minimizes reduction in quality even in the presence of increased noises. The device is adaptable for use in voice communications systems and speech recognition systems employed in a variety of kinds of noisy environments. The device includes a spectrum subtracter and a spectrum amplitude suppressor that operate on the basis of perceptual weights.<H suppression, device, Noise, suppressi, 7043030.html, Patent, pto, 7043030

Title: Noise suppression device

Abstract: A noise suppressor device for attaining perceptually preferable noise suppression is disclosed. The device minimizes reduction in quality even in the presence of increased noises. The device is adaptable for use in voice communications systems and speech recognition systems employed in a variety of kinds of noisy environments. The device includes a spectrum subtracter and a spectrum amplitude suppressor that operate on the basis of perceptual weights.

Patent Number: 7,043,030 Issued on 05/09/2006 to Furuta

Inventors: Furuta; Satoru (Tokyo, JP)
Assignee: Mitsubishi Denki Kabushiki Kaisha (Tokyo, JP)

Appl. No.: 587612

Filed: June 5, 2000

Foreign Application Priority Data


Jun 09, 1999 [JP]			11-162240

Current U.S. Class: 381/94.1 ; 381/94.2; 381/94.3; 704/226

Current International Class: H04B 15/00 (20060101)

Field of Search: 381/94.1,94.2,94.3 704/226,220,221,227,228,206-10 361/2

References Cited [Referenced By]

U.S. Patent Documents


5742927	April 1998	Crozier et al.
6044341	March 2000	Takahashi
6591234	July 2003	Chandran et al.

Foreign Patent Documents


9-212196	Aug., 1997	JP

Other References

Steven F. Boll, "Suppression of Acoustic Noise in Speech Using Spectral Subtraction," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-27, No. 2, Apr. 1979, pp. 113-120. cited by other .
R. L. Bouquin, Speech Communication, vol. 18, No. 1, XP-004008920, pps. 3-19, "Enhancement of Noisy Speech Signals: Application to Mobile Radio Communications," 1996. cited by other .
B. L. Sim, et al., IEEE Transactions on Speech and Audio Processing, vol. 6, No. 4, XP-000785363, pps. 328-336, "A Parametric Formulation of the Generalized Spectral Subraction Method," Jul. 1, 1998. cited by other.

Primary Examiner: Chin; Vivian
Assistant Examiner: Michalski; Justin
Attorney, Agent or Firm: Oblon, Spivak, McClelland, Maier & Neustadt, P.C.

Claims

What is claimed is:

1. A noise suppression device comprising: a time to frequency converter configured to perform frequency analyzation of an input time domain signal for conversion to an amplitude spectrum; a noise spectrum unit configured to obtain a noise spectrum of the input time domain signal; a signal to noise calculator configured to obtain a signal to noise ratio from the amplitude spectrum and the noise spectrum; a perceptual weight controller configured to control, based on the signal to noise ratio, first and second perceptual weights; a spectrum subtracter configured to subtract from said amplitude spectrum a product of said noise spectrum and the first perceptual weight as controlled by said perceptual weight controller; a spectrum amplitude suppressor configured to multiply a spectrum obtained from said spectrum subtracter by the second perceptual weight as controlled by said perceptual weight controller, the perceptual weight controller configured to control the second perceptual weight such that the amount of amplitude suppression by the spectrum amplitude suppressor decreases for at least a portion of the spectrum obtained from the spectrum subtracter as the signal-to-noise ratio increases; and a frequency to time converter configured to convert an output of said spectrum amplitude suppressor to a time domain signal.

2. The noise suppression device as recited in claim 1, wherein said perceptual weight controller is operable to let said first and second perceptual weights become larger at certain frequencies with increased signal to noise ratios while letting said first and second perceptual weights be smaller at frequencies with reduced signal to noise ratios.

3. The noise suppression device as recited in claim 1, further comprising: a perceptual weight modifier configured to modify at least one of the first and second perceptual weights at a ratio of a high frequency power to a low frequency power of any one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

4. The noise suppression device as recited in claim 1, further comprising: a perceptual weight modifier configured to modify the first and second perceptual weights based on a determination result as to whether an input signal is a noise or an audio component.

5. The noise suppression device as recited in claim 1, wherein the spectrum subtracter is further configured to perform fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum.

6. The noise suppression device as recited in claim 5, wherein said specified spectrum is one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input amplitude spectrum and the noise spectrum.

7. The noise suppression device as recited in claim 5, further comprising means for modifying the third perceptual weight at a ratio of a high frequency power to a low frequency power of at least one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

8. The noise suppression device as recited in claim 5, further comprising means for controlling the third perceptual weight based on the signal to noise ratio.

9. The noise suppression device as recited in claim 5, further comprising a perceptual weight adjuster configured to adjust the third perceptual weight in value through multiplication of a ratio of an input signal amplitude spectrum and an average noise spectrum.

10. The noise suppression device as recited in claim 1, wherein at least one perceptual weight is externally controlled or selected.

11. The noise suppression device as recited in claim 1, further comprising: a noise similarity analyzer configured to obtain a coefficient based on a noise similarity level of the input time domain signal, wherein the noise spectrum unit is further configured to obtain the noise spectrum based on the coefficient and the amplitude spectrum.

12. A method for noise suppression, comprising: generating an amplitude spectrum from an input time domain signal; generating a noise spectrum of the input time domain signal; determining a signal to noise ratio from the amplitude spectrum and the noise spectrum; controlling, based on the signal to noise ratio, a first perceptual weight and a second perceptual weight; subtracting from the amplitude spectrum a product of the noise spectrum and the first perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-removed spectrum; multiplying the noise-removed spectrum by the second perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-suppressed spectrum; controlling the second perceptual weight such that an amount of noise suppression decreases for at least a portion of the noise-removed spectrum, as the signal-to-noise ratio increases; and converting the noise-suppressed spectrum to an output time domain signal.

13. The method as recited in claim 12, wherein the step of controlling comprises: increasing the first perceptual weight and the second perceptual weight at frequencies with increased signal to noise ratios; and decreasing the first perceptual weight and the second perceptual weight at frequencies with reduced signal to noise ratios.

14. The method as recited in claim 12, further comprising: modifying at least one of the first perceptual weight and the second perceptual weight at a ratio of a high frequency power to a low frequency power of any one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

15. The method as recited in claim 12, further comprising: modifying the first perceptual weight and the second perceptual weight, based on a determination result as to whether an input signal is a noise component or an audio component.

16. The method as recited in claim 12, further comprising: performing fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum.

17. The method as recited in claim 16, wherein said specified spectrum is one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input amplitude spectrum and the noise spectrum.

18. The method as recited in claim 16, further comprising: modifying the third perceptual weight at a ratio of a high frequency power to a low frequency power of at least one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

19. The method as recited in claim 16, further comprising: controlling the third perceptual weight based on the signal to noise ratio.

20. The method as recited in claim 16, further comprising: adjusting the third perceptual weight in value through multiplication of a ratio of an input signal amplitude spectrum and an average noise spectrum.

21. The method as recited in claim 12, wherein the step of controlling comprises: externally selecting one of the first perceptual weight and the second perceptual weight.

22. The method as recited in claim 12, further comprising: determining a coefficient from a noise similarity level of the input time domain signal, wherein the step of generating the noise spectrum comprises: generating the noise spectrum based on the coefficient and the amplitude spectrum.

23. A noise suppression device comprising: a time to frequency converter configured to perform frequency analyzation of an input time domain signal for conversion to an amplitude spectrum; a circuit noise spectrum unit configured to obtain a noise spectrum of the input time domain signal; signal to noise calculator configured to obtain a signal to noise ratio from the amplitude spectrum and the noise spectrum; a perceptual weight controller configured to control, based on the signal to noise ratio, first and second perceptual weights; means for subtracting from the amplitude spectrum a product of the noise spectrum and the first perceptual weight as controlled by the perceptual weight controller; means for multiplying a spectrum obtained from the means for subtracting by the second perceptual weight as controlled by the perceptual weight controller, the perceptual weight controller configured to control the second perceptual weight such that an amount of amplitude suppression by the means for multiplying decreases for at least a portion of the spectrum obtained from the means for subtraction as the signal-to-noise ratio increases; and a frequency to time converter configured to convert an output of the means for multiplying to a time domain signal.

24. A noise-suppressed time domain signal generated by a noise suppression method comprising: generating an amplitude spectrum from an input time domain signal; generating a noise spectrum of the input time domain signal; determining a signal to noise ratio from the amplitude spectrum and the noise spectrum; controlling, based on the signal to noise ratio, a first perceptual weight and a second perceptual weight; subtracting from the amplitude spectrum a product of the noise spectrum and the first perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-removed spectrum; multiplying the noise-removed spectrum by the second perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-suppressed spectrum; controlling the second perceptual weight such that an amount of noise suppression decreases for at least a portion of the noise-removed spectrum, as the signal-to-noise ratio increases; and converting the noise-suppressed spectrum to an output time domain signal.

25. A noise suppression device for suppressing noise other than an objective signal contained in an input signal, comprising: means for controlling first and second perceptual weights for use in performing perceptual weighting, according to the input signal; means for performing a spectral subtraction on a signal derived from a spectrum of said input signal, using said controlled first perceptual weight, and for performing a spectral amplitude suppression on an other signal derived from the spectrum of said input signal, using said controlled second perceptual weight, to produce a spectrally subtracted and amplitude suppressed signal; and means for controlling the second perceptual weight such that the amount of amplitude suppression decreases for at least a portion of the other signal derived from the spectrum of the input signal, as the signal-to-noise ratio increases.

26. The noise suppression device set forth in claim 25, further comprising: means for controlling the first perceptual weight in such a way as to let the subtraction amount increase with increasing signal-to-noise ratio.

27. The noise suppression device set forth in 26, further comprising means for performing perceptual weighting with the first and second perceptual weights according to the frequency of the spectrum of the input signal.

28. The noise suppression device set forth in claim 25, further comprising means for performing perceptual weighting with the first perceptual weight according to a gradient in such a way as to let the subtraction amount decrease with increasing frequency of the spectrum of the input signal.

29. The noise suppression device set forth in claim 28, further comprising means for controlling the gradient of the first perceptual weight in such a way as to become steep with increasing signal-to-noise ratio.

30. The noise suppression device set forth in claim 25, further comprising means for performing perceptual weighting with the second perceptual weight according to a gradient in such a way as to let the amplitude suppression amount increase with increasing frequency of the spectrum of the input signal.

31. The noise suppression device set forth in claim 30, further comprising means for controlling the gradient of the second perceptual weight in such a way as to become moderate with increasing signal-to-noise ratio.

32. The noise suppression device set forth in claim 25, further comprising means for performing perceptual weighting with the first perceptual weight according to a gradient in such a way as to let the subtraction amount decrease with increasing frequency of the spectrum of the input signal; and means for performing perceptual weighting with the second perceptual weight according to a gradient in such a way as to let the amplitude suppression amount increase with increasing frequency of the spectrum of the input signal.

33. The noise suppression device set forth in claim 32, further comprising means for controlling the gradient of the first perceptual weight in such a way as to become steep with increasing signal-to-noise ratio; and further comprising means for controlling the gradient of the second perceptual weight in such a way as to become moderate with increasing signal-to-noise ratio.

34. The noise suppression device set forth in 25, further comprising means for performing perceptual weighting with the first and the second perceptual weights according to the frequency of the spectrum of the input signal.

35. A noise suppression method of suppressing noise other than an objective signal contained in an input signal, comprising the steps of: controlling first and second perceptual weights for use in performing perceptual weighting, according to the input signal; performing a spectral subtraction on a signal derived from a spectrum of said input signal, using said controlled first perceptual weight, and a spectral amplitude suppression on an other signal derived from the spectrum of said input signal, using said controlled second perceptual weight, to produce a spectrally subtracted and amplitude suppressed signal: and controlling the second perceptual weight such that the amount of amplitude suppression decreases for at least a portion of the other signal derived from the spectrum of the input signal, as the signal-to-noise ratio increases.

36. A noise suppression device for suppressing noise other than an objective signal contained in an input signal, comprising: a perceptual weight controller configured to control first and second perceptual weights for use in performing perceptual weighting, according to the input signal; a spectrum subtractor configured to perform a spectral subtraction on a signal derived from a spectrum of said input signal, using said controlled first perceptual weight; and a spectrum amplitude suppressor configured to perform a spectral amplitude suppression on an other signal derived from the spectrum of said input signal, using said controlled second perceptual weight, the perceptual weight controller configured to control the second perceptual weight such that the amount of amplitude suppression decreases for at least a portion of the other signal derived from the spectrum of the input signal, as the signal-to-noise ratio increases.

37. A noise suppression device comprising: a time to frequency converter configured to perform frequency analyzation of an input time domain signal for conversion to an amplitude spectrum; a noise spectrum unit configured to obtain a noise spectrum of the input time domain signal; a signal to noise calculator configured to obtain a signal to noise ratio from the amplitude spectrum and the noise spectrum; a perceptual weight controller configured to control, based on the signal to noise ratio, first and second perceptual weights; a spectrum subtracter configured to subtract from said amplitude spectrum a product of said noise spectrum and the first perceptual weight as controlled by said perceptual weight controller; a spectrum amplitude suppressor configured to multiply a spectrum obtained from said spectrum subtracter by the second perceptual weight as controlled by said perceptual weight controller, the perceptual weight controller configured to control the second perceptual weight such that the amount of amplitude suppression by the spectrum amplitude suppressor decreases for at least a portion of the spectrum obtained from the spectrum subtracter as the signal-to-noise ratio increases; a frequency to time converter configured to convert an output of said spectrum amplitude suppressor to a time domain signal; and a perceptual weight modifier configured to modify at least one of the first and second perceptual weights at a ratio of a high frequency power to a low frequency power of any one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

38. A noise suppression device comprising: a time to frequency converter configured to perform frequency analyzation of an input time domain signal for conversion to an amplitude spectrum; a noise spectrum unit configured to obtain a noise spectrum of the input time domain signal; a signal to noise calculator configured to obtain a signal to noise ratio from the amplitude spectrum and the noise spectrum; a perceptual weight controller configured to control, based on the signal to noise ratio, first and second perceptual weights; a spectrum subtracter configured to subtract from said amplitude spectrum a product of said noise spectrum and the first perceptual weight as controlled by said perceptual weight controller; a spectrum amplitude suppressor configured to multiply a spectrum obtained from said spectrum subtracter by the second perceptual weight as controlled by said perceptual weight controller, the perceptual weight controller configured to control the second perceptual weight such that the amount of amplitude suppression by the spectrum amplitude suppressor decreases for at least a portion of the spectrum obtained from the spectrum subtracter as the signal-to-noise ratio increases; a frequency to time converter configured to convert an output of said spectrum amplitude suppressor to a time domain signal, wherein the spectrum subtracter is further configured to perform fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum; and means for modifying the third perceptual weight at a ratio of a high frequency power to a low frequency power of at least one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

39. A noise suppression device comprising: a time to frequency converter configured to perform frequency analyzation of an input time domain signal for conversion to an amplitude spectrum; a noise spectrum unit configured to obtain a noise spectrum of the input time domain signal; a signal to noise calculator configured to obtain a signal to noise ratio from the amplitude spectrum and the noise spectrum; a perceptual weight controller configured to control, based on the signal to noise ratio, first and second perceptual weights; a spectrum subtracter configured to subtract from said amplitude spectrum a product of said noise spectrum and the first perceptual weight as controlled by said perceptual weight controller; a spectrum amplitude suppressor configured to multiply a spectrum obtained from said spectrum subtracter by the second perceptual weight as controlled by said perceptual weight controller, the perceptual weight controller configured to control the second perceptual weight such that the amount of amplitude suppression by the spectrum amplitude suppressor decreases for at least a portion of the spectrum obtained from the spectrum subtracter as the signal-to-noise ratio increases; a frequency to time converter configured to convert an output of said spectrum amplitude suppressor to a time domain signal, wherein the spectrum subtracter is further configured to perform fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum; and means for controlling the third perceptual weight based on the signal to noise ratio.

40. A noise suppression device comprising: a time to frequency converter configured to perform frequency analyzation of an input time domain signal for conversion to an amplitude spectrum; a noise spectrum unit configured to obtain a noise spectrum of the input time domain signal; a signal to noise calculator configured to obtain a signal to noise ratio from the amplitude spectrum and the noise spectrum; a perceptual weight controller configured to control, based on the signal to noise ratio, first and second perceptual weights; a spectrum subtracter configured to subtract from said amplitude spectrum a product of said noise spectrum and the first perceptual weight as controlled by said perceptual weight controller; a spectrum amplitude suppressor configured to multiply a spectrum obtained from said spectrum subtracter by the second perceptual weight as controlled by said perceptual weight controller, the perceptual weight controller configured to control the second perceptual weight such that the amount of amplitude suppression by the spectrum amplitude suppressor decreases for at least a portion of the spectrum obtained from the spectrum subtracter as the signal-to-noise ratio increases; a frequency to time converter configured to convert an output of said spectrum amplitude suppressor to a time domain signal, wherein the spectrum subtracter is further configured to perform fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum; and a perceptual weight adjuster configured to adjust the third perceptual weight in value through multiplication of a ratio of an input signal amplitude spectrum and an average noise spectrum.

41. A method for noise suppression, comprising: generating an amplitude spectrum from an input time domain signal; generating a noise spectrum of the input time domain signal; determining a signal to noise ratio from the amplitude spectrum and the noise spectrum; controlling, based on the signal to noise ratio, a first perceptual weight and a second perceptual weight; subtracting from the amplitude spectrum a product of the noise spectrum and the first perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-removed spectrum; multiplying the noise-removed spectrum by the second perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-suppressed spectrum; controlling the second perceptual weight such that an amount of noise suppression decreases for at least a portion of the noise-removed spectrum, as the signal-to-noise ratio increases; converting the noise-suppressed spectrum to an output time domain signal; and modifying at least one of the first perceptual weight and the second perceptual weight at a ratio of a high frequency power to a low frequency power of any one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

42. A method for noise suppression, comprising: generating an amplitude spectrum from an input time domain signal; generating a noise spectrum of the input time domain signal; determining a signal to noise ratio from the amplitude spectrum and the noise spectrum; controlling, based on the signal to noise ratio, a first perceptual weight and a second perceptual weight; subtracting from the amplitude spectrum a product of the noise spectrum and the first perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-removed spectrum; multiplying the noise-removed spectrum by the second perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-suppressed spectrum; controlling the second perceptual weight such that an amount of noise suppression decreases for at least a portion of the noise-removed spectrum, as the signal-to-noise ratio increases; converting the noise-suppressed spectrum to an output time domain signal; performing fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum; and modifying the third perceptual weight at a ratio of a high frequency power to a low frequency power of at least one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

43. A method for noise suppression, comprising: generating an amplitude spectrum from an input time domain signal; generating a noise spectrum of the input time domain signal; determining a signal to noise ratio from the amplitude spectrum and the noise spectrum; controlling, based on the signal to noise ratio, a first perceptual weight and a second perceptual weight; subtracting from the amplitude spectrum a product of the noise spectrum and the first perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-removed spectrum; multiplying the noise-removed spectrum by the second perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-suppressed spectrum; controlling the second perceptual weight such that an amount of noise suppression decreases for at least a portion of the noise-removed spectrum, as the signal-to-noise ratio increases; converting the noise-suppressed spectrum to an output time domain signal; performing fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum; and controlling the third perceptual weight based on the signal to noise ratio.

44. A method for noise suppression, comprising: generating an amplitude spectrum from an input time domain signal; generating a noise spectrum of the input time domain signal; determining a signal to noise ratio from the amplitude spectrum and the noise spectrum; controlling, based on the signal to noise ratio, a first perceptual weight and a second perceptual weight; subtracting from the amplitude spectrum a product of the noise spectrum and the first perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-removed spectrum; multiplying the noise-removed spectrum by the second perceptual weight controlled on the basis of the signal to noise ratio, to generate a noise-suppressed spectrum; controlling the second perceptual weight such that an amount of noise suppression decreases for at least a portion of the noise-removed spectrum, as the signal-to-noise ratio increases; converting the noise-suppressed spectrum to an output time domain signal; performing fill-up processing, when a subtraction result of said spectrum subtracter is negative or zero, to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum; and adjusting the third perceptual weight in value through multiplication of a ratio of an input signal amplitude spectrum and an average noise spectrum.

45. A noise suppression device for suppressing noise other than an objective signal contained in an input signal, comprising: means for controlling first and second perceptual weights for use in performing perceptual weighting, according to the input signal; means for performing a spectral subtraction on a signal derived from a spectrum of said input signal, using said controlled first perceptual weight, and for performing a spectral amplitude suppression on an other signal derived from the spectrum of said input signal, using said controlled second perceptual weight, to produce a spectrally subtracted and amplitude suppressed signal; means for controlling the second perceptual weight such that the amount of amplitude suppression decreases for at least a portion of the other signal derived from the spectrum of the input signal, as the signal-to-noise ratio increases; and means for performing perceptual weighting with the second perceptual weight according to a gradient in such a way as to let the amplitude suppression amount increase with increasing frequency of the spectrum of the input signal.

46. The noise suppression device set forth in claim 45, further comprising means for controlling the gradient of the second perceptual weight in such a way as to become moderate with increasing signal-to-noise ratio.

47. A noise suppression device for suppressing noise other than an objective signal contained in an input signal, comprising: means for controlling first and second perceptual weights for use in performing perceptual weighting, according to the input signal; means for performing a spectral subtraction on a signal derived from a spectrum of said input signal, using said controlled first perceptual weight, and for performing a spectral amplitude suppression on an other signal derived from the spectrum of said input signal, using said controlled second perceptual weight, to produce a spectrally subtracted and amplitude suppressed signal; means for controlling the second perceptual weight such that the amount of amplitude suppression decreases for at least a portion of the other signal derived from the spectrum of the input signal, as the signal-to-noise ratio increases; means for performing perceptual weighting with the first perceptual weight according to a gradient in such a way as to let the subtraction amount decrease with increasing frequency of the spectrum of the input signal; and means for performing perceptual weighting with the second perceptual weight according to a gradient in such a way as to let the amplitude suppression amount increase with increasing frequency of the spectrum of the input signal.

48. The noise suppression device set forth in claim 47, further comprising means for controlling the gradient of the first perceptual weight in such a way as to become steep with increasing signal-to-noise ratio; and further comprising means for controlling the gradient of the second perceptual weight in such a way as to become moderate with increasing signal-to-noise ratio.

Description

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to noise suppression devices for reducing or suppressing noises other than objective signals in voice communications systems and speech recognition systems often used in various noisy environments.

2. Description of the Prior Art

Noise suppressor devices for suppressing any possible nonobjective signal components such as noises mixed into audio/voice signals are known in the art, one of which has been disclosed in, for example, Japanese Patent Laid-Open No. 212196/1997. The noise suppressor as taught by this Japanese publication is inherently designed to employ what is called the spectral subtraction method. This method is for noise reduction based on amplitude spectra in a way as suggested from Steven F. Boll, "Suppression of Acoustic Noise in Speech using Spectral Subtraction," IEEE Trans. ASSP, Vol. ASSP-27, No. 2, April 1979.

The prior known noise suppression technique of the above-identified Japanese Patent Laid-Open No. 212196/1997, will be explained in detail with reference to FIG. 1. In FIG. 1, reference numeral "200" designates such related art noise suppressor; 201 denotes a perceptual weighting side; and 202 indicates a loss control side. Numeral 101 denotes an input signal node; 102 is a frequency analyzer circuit; 103, linear prediction circuit; 104, auto-correlative analyzer circuit; 105, maximum value analyzer circuit. 106 designates an audio/non-audio analyzer circuit, an output of which is used for turn-on/off controlling of switches 107A, 107B. 108 is a noise spectrum characteristics calculation and storage circuit, which is for performing perceptual weighting processing. 109 is a subtractor means; 110 is an inverse frequency analyzer circuit for performing an adverse operation to that of the frequency analyzer circuit 102. 111 is an average noise level storage circuit; 112, loss control coefficient circuit; 113, output signal calculator circuit; 114, arithmetic means; 115, output signal node.

When an input signal is supplied to the input node 101 and taken into the noise suppressor 200, the frequency analyzer circuit 102 is rendered operative to convert a time domain or timebase signal into a frequency domain signal for separation into a power spectrum S(f) and phase spectrum P(f). Simultaneously, the input signal is subjected to linear prediction analyzation at the linear prediction analyzer circuit 103, thereby obtaining a linear prediction difference signal (error signal) from a difference between the input signal and a predicted value. This error signal is supplied to the auto-correlation analyzer circuit 104 to thereby obtain a self- or auto-correlation coefficient. The maximum value selector circuit 105 operates to search for the maximum value, Rmax, of such auto-correlation factor. The maximum value Rmax is then passed to the audio/nonaudio identifier circuit 106, which identifies the kind or type of the input signal. If the value Rmax is greater than a prespecified threshold value, then identify the signal as an audio signal; if the former is less than the latter then identify it as noise components.

The signal spectrum S(f) identified as noise at the audio/nonaudio identifier 106 is stored or accumulated as a noise spectrum Sns(f) in the noise spectrum characteristics calculation/storage circuit 108 in response to an operation of the switch 107A. Updating of the noise spectrum is carried out through multiplication of a weighting coefficient .beta. to a noise spectrum Sns.sub.old before updating and the input signal spectrum S(f), in a way as defined by the following Equation (1): Sns .sub.now(f)=Sns.sub.old(f).beta.+S(f)(1-.beta.) (1)

Subsequently, for the purpose of noise suppression processing, a weighting factor W(f) is used for the noise spectrum Sns(f) to perform perceptual weighting. W(f) may be represented by Equation (2) below: W(f)={B-(B/fc)f}+K, f=0, . . . fc (2)

In the equation above, "fc" is the value equivalent to the frequency band of an input signal, B and K are the weighting coefficients or factors, wherein the greater the value, the greater the amount of suppression. The values B, K are changeable or alterable depending on the kind and significance of noises.

The arithmetic means 109 performs subtraction processing of an average noise spectrum S.sub.ns(f) from the input signal spectrum S(f) in accordance with Equation (3), to be presented below, thereby obtaining a noise-removed spectrum S' (f). If the noise-removed spectrum S' (f) is negative then add thereto either zero (0) or low-level noise th(f).

[Eq. 3]

'.function..function..function..function..times..times..function.>.func- tion..times..times..times..times..function. ##EQU00001##

The inverse frequency analyzer 110 makes use of the noise-removed spectrum S' (f) and phase spectrum P(f) to obtain a signal waveform through conversion from a frequency domain to a time domain.

Subsequently the average noise level storage circuit 111 stores therein a residual noise level at an instant that the input signal is determined as noise. The average noise level Lns will be updated only when the input signal is determined as noise by using Equation (4) to be later presented. Here, Lns.sub.new[t] is the average noise level updated at a time point t, Lns.sub.old is the average noise level within a frame prior to updating, Lns[t] is the residual noise level of an output signal of the inverse frequency analyzer 110 at a time point t, and .beta. is the weighting factor. Lns.sub.now[t]=Lns.sub.old.beta.+LnS[t](1-.beta.) (4)

Using the values Lns[t] and L.sub.s[t] thus obtained, calculate a loss control coefficient A[t] by Equation (5) presented below. Here, .mu. is the loss amount. Ls[t] is a signal as output by the output signal calculator 113 in response to receipt of an output signal of the inverse frequency analyzer 110. A[t]=Ls[t]/.mu.Lns[t] (5)

The arithmetic circuit 114 multiplies the output signal of the inverse frequency analyzer 110 by the above obtained loss control coefficient A[t] to provide a resultant signal, which is output from the signal output node 115.

SUMMARY OF THE INVENTION

The noise suppressor stated above is capable of suppressing residual noises through execution of spectral subtraction processing after completion of the perceptual weighting relative to the average noise spectrum and further by use of the loss control coefficient, thereby making it possible to minimize distortion of intended signals and thus perceptually suppressing residual noises. Unfortunately, these advantages do not come without accompanying problems which follow.

As residual noises that could not have been removed away by spectral subtraction processing are subject to suppression processing on the time domain rather than on spectrum, any successful amplitude suppression will hardly be achievable on spectrum in a perceptually preferable way. Another problem faced with the related art is that in audio domains, it is impossible or at least greatly difficult to suppress residual noises without suppressing an audio signal waveform per se, which would disadvantageously result in a decrease in sound volume of audio and/or voice data.

Still another problem encountered with the related art lies in inherent limitations to the performance of noise suppression processing, which merely relies upon noise removal coefficient control schemes based on perceptual weighting of the average noise spectrum. This can be said because such related art approach is incapable of suppressing "special" noises that can occur in special environments. One example is that in highly noisy environments such as inside of a land vehicle that is running on express motorways or highways, the prediction accuracy of the average noise spectrum decreases due to degradation of noise domain determination accuracies, which results in creation of specific noises (called the "musical noises") due to excessive removal processing or the like, which is unique to the spectral subtraction methodology. Reduction or suppression of such musical noises will thus hardly be attainable by mere use of the related art removal coefficient control-based on-spectrum noise suppression processing.

A further problem faced with the related art lies in inability to suppress creation of sharp spectrum patterns which stand alone on the axis of frequency, which may be considered as one of the factors of musical noise creation, in low-level noises to be added during processing (fill-up process) in the event that the noise-removed spectrum becomes negative. It may be considered that the creation of such sharp spectrum patterns can badly behave to cause the musical noises discussed above.

This invention has been made in order to avoid the problems associated with the related art, and its primary object is to provide a new and improved noise suppression device capable of offering perceptually preferable noise suppressibility while at the same time reducing quality degradation even under high noisy environments.

A noise suppression device in accordance with this invention is specifically arranged so that it includes a time to frequency converter circuit for performing frequency analyzation of an input time domain signal for conversion to an amplitude spectrum, a circuit for obtaining a noise spectrum from the input signal, a circuit for obtaining a signal to noise ratio from the amplitude spectrum and the noise spectrum, a perceptual weight control circuit for controlling based on the signal to noise ratio first and second perceptual weights for use in performing perceptual weighting in accordance with spectra, a spectrum subtractor circuit for subtracting from said amplitude spectrum a product of said noise spectrum and the first perceptual weight as controlled by said perceptual weight control circuit, a spectrum amplitude suppressor circuit for multiplying a spectrum obtained from said spectrum subtractor circuit by the second perceptual weight as controlled by said perceptual weight control circuit, and a frequency to time converter circuit for converting an output of said spectrum suppressor circuit to a time domain signal.

The noise suppressor device may be arranged so that the perceptual weight control circuit is operable to let said first and second perceptual weights become larger at certain frequencies with increased signal to noise ratios while letting said first and second perceptual weights be smaller at frequencies with reduced signal to noise ratios.

The noise suppressor device may also be arranged to include a perceptual weight modifier circuit for modifying at least one of the first and second perceptual weights at a ratio of a high frequency power to a low frequency power of any one of an input signal amplitude spectrum and a noise spectrum as well as an average spectrum of the input signal amplitude spectrum and the noise spectrum.

A perceptual weight modifier circuit may also be provided for modifying the first and second perceptual weights based on a determination result as to whether an input signal is a noise or an audio component.

In addition, in cases where a subtraction result of said spectrum subtractor circuit is negative, fill-up processing may be executed to a spectrum obtained by multiplying a third perceptual weight to a specified spectrum.

Additionally, said the specified spectrum may be one of an input signal amplitude spectrum, a noise spectrum, and an average spectrum of the input signal amplitude spectrum and the noise spectrum.

Additionally the third perceptual weight is modified at a ratio of a high frequency power to a low frequency power of one of an input signal amplitude spectrum and a noise spectrum as well as an average spectrum of the input signal amplitude spectrum and the noise spectrum.

Alternatively, the third perceptual weight may be controlled depending on the signal to noise ratio.

Still alternatively, the third perceptual weight is adjusted in value through multiplication of a ratio of an input signal amplitude spectrum and a noise spectrum.

At least one perceptual weight is externally controlled or selected.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing a configuration of one related art noise suppressor device;

FIG. 2 is a block diagram showing a noise suppressor device in accordance with one embodiment of this invention;

FIG. 3 is a detailed circuit diagram of an auto-correlation analyzer circuit 14 shown in FIG. 2;

FIG. 4 is a detailed circuit diagram of an updated rate coefficient determinator circuit 16 of FIG. 2;

FIG. 5 is a detailed circuit diagram of a perceptual weight calculator circuit 6 of FIG. 2;

FIG. 6 is a detailed circuit diagram of an average noise spectrum updating and holding means 4 of FIG. 2;

FIG. 7 is a detailed circuit diagram of a signal-to-noise (SN) ratio calculator circuit 5 of FIG. 2;

FIG. 8 is a diagram showing one example of a first perceptual weight .alpha..sub.w(f) and second perceptual weight .beta..sub.w(f) of this invention;

FIG. 9 shows one example of a control scheme of a perceptual weight control circuit of the noise suppressor embodying this invention, which scheme is for controlling the first perceptual weight .alpha..sub.w(f) and second perceptual weight .beta..sub.w;

FIG. 10 is a detailed circuit diagram of a spectrum subtractor circuit 8 of FIG. 2;

FIG. 11 is a block diagram showing a configuration of a noise suppressor in accordance with another embodiment of this invention;

FIG. 12 is a detailed circuit diagram of a perceptual weight modifier circuit 17 of FIG. 11;

FIG. 13 is a block diagram showing a configuration of a noise suppressor in accordance with still another embodiment of this invention;

FIG. 14 shows one example of a third perceptual weight .gamma..sub.w(f) of this invention;

FIG. 15 shows one exemplary spectrum obtainable after noise removal processing in the case (a) of preventing perceptual weighting relative to a low-level noise n(f) spectrum being filled up when the resultant noise-removed spectrum is negative in the noise suppressor embodying this invention, along with another exemplary noise-removed spectrum in the case (b) of performing the perceptual weighting therein;

FIG. 16 is a block diagram showing a configuration of a noise suppressor in accordance with yet another embodiment of this invention;

FIG. 17 is a block diagram showing a configuration of a noise suppressor in accordance with a further embodiment of this invention;

FIG. 18 is a detailed circuit diagram of a perceptual weight adjuster circuit 18 of FIG. 17; and

FIG. 19 is a block diagram showing a configuration of a noise suppressor in accordance with a still further embodiment of the invention;

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Embodiment 1

An explanation will now be given of a noise suppression device incorporating the principles of this invention, with reference to the accompanying drawings.

FIG. 2 is a block diagram showing a configuration of a noise suppressor device in accordance with an embodiment 1 of the present invention. The illustrative noise suppressor is generally constituted from an input signal receive terminal 1, a time-to-frequency (time/frequency) converter circuit 2, a noise similarity analyzer circuit 3, an average noise spectrum update and storage circuit 4, a signal-to-noise ratio (SNR) calculator circuit 5, a perceptual weight calculator circuit 6, a perceptual weighting control circuit 7, a spectrum subtractor circuit 8, a spectrum suppressor circuit 9, a frequency/time converter circuit 10, and an output signal terminal 11. The principles of an operation of the noise suppressor embodying the present invention will be explained in conjunction with FIG. 2 below.

An input signal is input to the input signal terminal 1, which signal has been subjected to sampling at a specified frequency (for example, 8 kHz) and then subdivided into portions in units of certain frames (e.g. 20 ms). This input signal may be full of background noise components in some cases; in other cases, this signal may be an audio/voice signal with background noises partly mixed thereinto.

The time/frequency converter circuit 2 is a circuit for converting the input signal in such a way that a time domain or timebase signal is converted to a frequency domain signal. The time/frequency converter circuit 2 is operable to make use of, for example, 256-point fast Fourier transformation (F F T) techniques for converting the input signal into an amplitude spectrum S(f) and phase spectrum P(f). Note that the F F T techniques per se are well known in the art to which the invention pertains.

The noise similarity analyzer circuit 3 is generally configured from a linear prediction/analyze circuit 15, a low-pass filter (LPF) 12, an inverse filter 13, a self- or auto-correlation analyzer circuit 14, and an updated rate coefficient determination circuit 16. First, let the LPF 12 perform filtering processing of the input signal to obtain a low-pass filtered signal. This filter is 2 kHz in cut-off frequency thereof, by way of example. Performing the low-pass filtering processing makes it possible to remove away the influence of high frequency noise components, which in turn enables achievement of stable analyzation required.

The inverse filter 13 applies inverse filtering processing to the low-pass filter signal by use of a linear prediction coefficient or factor, thereby outputting a low-pass linear prediction residual signal (referred to as "low-pass difference" signal hereinafter). Subsequently the auto-correlation analyzer circuit 14 operates to perform auto-correlation analyzation of such low-pass difference signal to obtain a peak value positive in polarity, which is represented by RAC.sub.max.

A detailed configuration of the auto-correlation analyzer circuit 14 is shown in FIG. 3. This circuit includes a correlator 14a that performs within-frame auto-correlation computation of the low-pass filter signal to thereby obtain an auto-correlation series r[0] to r[N], where N is the length of a frame. Note that the auto-correlation series is subject to normalization at a normalizer 14b. Subsequently the normalized auto-correlation series is passed to a searcher 14c, which performs searching for a positive maximal value and then outputs the maximum value RAC.sub.max of the positive polarity. Next, let the linear prediction/analyze circuit 15 perform linear prediction analysis of the low-pass filter signal, thus obtaining a linear prediction coefficient (e.g. .alpha. parameter of 10-dimension).

An operation of the linear prediction/analyze circuit 15 is as follows. First, obtain the auto-correlation coefficient by auto-correlation analyzation of 10-dimension. Then, use this auto-correlation coefficient to obtain a reflection coefficient by the so-called "le roux" method, which in turn is used to obtain an a parameter that is a linear predictive coefficient. This procedure per se is well known among those skilled in the art. Additionally, when obtaining the linear predictive coefficient, a frame power and a linear predictive residual power of low-pass filter signal (low-pass difference power) are also obtained simultaneously.

The updated rate coefficient determination circuit 16 operates, for example, in such a way as to use the above-noted RAC.sub.max and also the frame power and the power of the low-pass residual signal to determine the noise similarity at five levels as shown in Table 1 below to thereby determine the average noise spectrum update rate coefficient r in accordance with each level.

TABLE-US-00001 TABLE 1 Average Noise Spectrum Update Level Noise Similarity Rate Coefficient r 0 Great 0.5 1 '' 0.6 2 '' 0.8 3 '' 0.95 4 Less 0.9999

A practically implementable circuit is shown in FIG. 4. It has a status variable memory "stt", which is reset to 0 in the determination input pre-stage. Next, let a comparator 16a compare the low-pass residual auto-correlation coefficient maximum value RAC.sub.max to a predetermined threshold value TH_RAC.sub.max; when the former is greater than the latter, permit an adder 16b to count up the value of state variable stt by +2. Subsequently, at a comparator 16c, compare a low-pass residual power rp to a specified threshold value TH_rp; if the former is greater than the latter then cause an adder 16d to count up the value of state variable stt by +1. Next, let a comparator 16e compare a frame power fp to a certain threshold value TH_fp; if the former is greater than the latter then force an adder 16f to count up the value of state variable stt by +1. The content of the resultant state variable stt thus counted in this way will be output as a level toward a memory 16g. The memory 16g presently stores therein the average noise spectrum update rate coefficient r in accordance with the value of each level, and outputs an updated rate coefficient r in accordance with such level value.

The perceptual weight calculator circuit 6 inputs specified constant values .alpha., .alpha.' (for example, .alpha.=1.2, .alpha.'=0.5) along with constant values .beta., .beta.' (for instance, .beta.=0.8, .beta.'=0.1), and then calculates by Equation (6) a first perceptual weight .alpha.w(f) and second perceptual weight .beta.w(f). fc is a Nyquist frequency(a half of sampling frequency). .alpha.w(f)=(.alpha.'-.alpha.)f/fc+.alpha., f=0, . . . . fc .beta.w(f)=(.beta.'-.beta.)f/fC+.beta., f=0, . . . fc (6)

The perceptual weight calculator circuit 6 is shown in FIG. 5. This circuit includes a multiplier 6a that is operable to perform multiplication of a precalculated constant (.alpha.'-.alpha.)/fc and a frequency f. Subsequently, an adder 6b operates to add an output result of the multiplier 6a to a constant .alpha., obtaining the first perceptual weight .alpha.w(f). This will be repeated up to a frequency band ranging from f to fc. With regard to the second perceptual weight .beta.w(f) also, this may be obtained through similar processing to that of the first perceptual weight .alpha.w(f).

It should be noted that the first perceptual weight .alpha..sub.w and second perceptual weight .beta..sub.w are determinable depending on an input signal level and/or in-use environments. FIG. 8 shows one exemplary case where the use environment is inside of a land vehicle that is presently travelling on highways.

The average noise spectrum update and storage circuit 4 is operatively responsive to receipt of the amplitude spectrum S(f) and the average noise spectrum update rate coefficient r as output from the noise similarity analyzer 3, for performing updating of the average noise spectrum N(f) in a way defined by Equation (7) presented below. N.sub.old(f) is the average noise spectrum prior to such updating, and N.sub.new(f) is the average noise spectrum thus updated. N.sub.new (f)=(1-r)N.sub.old(f)+rS(f) (7)

A configuration of the average noise spectrum update and storage circuit 4 is shown in FIG. 6.

Firstly, at a multiplier 4b, execute multiplication of the update rate determination coefficient r and input signal spectrum S(f) together. Also perform multiplication of the "past" average noise spectrum Nold(f) that has been read out of a memory 4a and a specific value as obtained through subtraction of the update rate determination coefficient r from 1, i.e. 1-r, thus letting the result be output to an adder 4c. Subsequently, at an adder 4c, perform addition of two resultant values as output from said adder 4b to output a new average noise spectrum Nnew(f) while at the same time using the average noise spectrum Nnew(f) to update the content of the memory 4a.

The SN ratio calculator circuit 5 calculates from the input signal amplitude spectrum and average noise spectrum a ratio (SN ratio) of the input signal spectrum to the average noise spectrum.

A configuration of the SN ratio calculator circuit is shown in FIG. 7. At an average value calculator 5a, calculate the average value of per-band spectrum components of the input signal spectrum S(f), and then output the average input signal spectrum Sa(f). The average input signal spectrum Sa(f) and the noise spectrum N(f) are converted into logarithmic value by the converter 5b.

Next, at a subtractor 5c, subtraction is done between log {S(f)} and log {N(f)} to thereby obtain a ratio (SNR) of the input signal spectrum Sa(f) to the average noise spectrum N(f), which ratio is then output to the perceptual weight calculation means 6.

The perceptual weight control circuit 7 controls, on the basis of the SN ratio as output from the SN ratio calculator circuit 5, the first perceptual weight .alpha..sub.w(f) and the second perceptual weight .beta..sub.w(f) of FIG. 8 in such a way as to become appropriate values adapted to the SN ratio of a present frame. Thereafter, output them as an SN ratio-controlled first perceptual weight .alpha..sub.wc(f) and an SN ratio-controlled second perceptual weight .beta..sub.wc(f). FIG. 9 is one example of such control. When the SN ratio is high, set up a difference between .alpha..sub.w(0) and .alpha..sub.w(fc) so that it is great (namely, the gradient of .alpha..sub.w(f) in FIG. 8 gets larger). Adversely, in the case of .beta..sub.w(f), let a difference between .beta..sub.w(0) and .beta..sub.w(fc) become less (the gradient of 1/.beta..sub.w(f) of FIG. 8 becomes moderate). And, as the SN ratio gets smaller, let a difference between .alpha..sub.w(0) and .alpha..sub.w(fc) becomes less (the gradient of .alpha..sub.w(f) is moderated); adversely, a difference between .beta..sub.w(0) and .beta..sub.w(fc) gets larger (the gradient of 1/.beta..sub.w increases).

A practically implementable processing scheme is such that the perceptual weight control circuit 7 is responsive to receipt of the SN ratio of a present frame for performing control of the values of .alpha.c(f) and .beta.c(f) in a way as given by the following equations:

.alpha..times..times..function.<.times..times..alpha..times..times..fun- ction..alpha..times..times..function..times..times.<<.times..times..- alpha..times..times..function.>.times..times. ##EQU00002##

.beta..times..times..function..beta..times..times..function.<.times..ti- mes..beta..times..times..function..beta..times..times..function..times..ti- mes.<<.times..times.>.times..times. ##EQU00003##

The spectrum subtractor circuit 8 multiplies the average noise spectrum N(f) by the SN ratio-controlled first perceptual weight .alpha..sub.c(f), executes subtraction of the amplitude spectrum S(f) in a way defined by Equation (8), and then outputs a noise-removed spectrum S.sub.s(f). In addition, when the noise-removed spectrum S.sub.s(f) is negative, insert zero or a prespecified low-level noise n(f), and then perform fill-up processing with this being as the noise-removed spectrum.

.function..times..function..alpha..function..function..times..times..funct- ion.>.alpha..function..function..times..times..times..times..function. ##EQU00004##

A detail of the spectrum subtractor circuit 8 is shown in FIG. 10. At a multiplier 8a, multiply the average noise spectrum N(f) by the SN ratio-controlled first perceptual weight .alpha.c(f), and then output the result to a subtractor 8b. At a subtractor 8b, subtract the output result of the multiplier 8a from the input signal spectrum S(f) thereby obtaining the noise-removed spectrum Ss(f). Subsequently the noise-removed spectrum Ss(f) is input to a comparator 8c, which performs check/verifying of such sign. When the sign check result is negative, let the noise-removed spectrum Ss(f) be sent forth to a fill-up processor 8d, which executes fill-up processing for replacement it with 0 or a specified low-level noise n(f).

The spectrum suppression circuit 9 multiplies the noise-removed spectrum S.sub.s(f) by the SN ratio-controlled second perceptual