Noise Reduction

• US 20090254340A1
• Filed: 04/07/2008
• Published: 10/08/2009
• Est. Priority Date: 04/07/2008
• Status: Active Grant

• Current Assignee: Qualcomm technologies international, ltd. (Qualcomm, Inc.)
• Original Assignee: Cambridge Silicon Radio Limited (Qualcomm, Inc.)
• Inventors: Alves, Rogerio Guedes, Sun, Xuejing, Yen, Kuan-Chieh
• Granted Patent: US 9,142,221 B2
• Time in Patent Office: Days
• US Class Current: 704/226
• CPC Class Codes: G10L 2021/02163 Only one microphone
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 25/78 Detection of presence or absence of voice signals switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals

Abstract

A signal processor for estimating noise power in an audio signal includes a filter unit for generating a series of power values, each power value representing the power in the audio signal at a respective one of a plurality of frequency bands; a signal classification unit for analysing successive portions of the audio signal to assess whether each portion contains features characteristic of speech, and for classifying each portion in dependence on that analysis; a correction unit for estimating a minimum power value in a time-limited part of the audio signal, estimating the total noise power in that part of the audio signal and forming a correction factor dependent on the ratio of the minimum power value to the estimated total noise power, the correction unit being configured to estimate the minimum power value and the total noise power over only those portions of the time-limited part of the signal that are classified by the signal classification unit as being less characteristic of speech; and a noise estimation unit for estimating noise in the audio signal in dependence on the power values output by the filter unit and the correction factor formed by the correction unit.

Claims

1. A signal processor for estimating noise power in an audio signal, the signal processor comprising:

a filter function for generating a series of power values, each power value representing the power in the audio signal at a respective one of a plurality of frequency bands;

a signal classification function for analysing successive portions of the audio signal to assess whether each portion contains features characteristic of speech, and for classifying each portion in dependence on that analysis;

a correction function for estimating a minimum power value in a time-limited part of the audio signal, estimating the total noise power in that part of the audio signal and forming a correction factor dependent on the ratio of the minimum power value to the estimated total noise power, the correction function being configured to estimate the minimum power value and the total noise power over only those portions of the time-limited part of the signal that are classified by the signal classification function as being less characteristic of speech; and

a noise estimation function for estimating noise in the audio signal in dependence on the power values output by the filter function and the correction factor formed by the correction function.

2. A signal processor as claimed in claim 1, wherein the filter function implements a Fourier transform.

3. A signal processor as claimed in claim 1, wherein the signal classification function is configured to analyse the portions of the audio signal to detect harmonicity therein and to classify each portion in dependence on that analysis.

4. A signal processor as claimed in claim 1, wherein the signal classification function is configured to analyse the portions of the audio signal to detect pitch characteristics therein and to classify each portion in dependence on that analysis.

5. A signal processor as claimed in claim 1, wherein the minimum power is the minimum power of a plurality of time domain samples derived from the time-limited part of the audio signal.

6. A signal processor as claimed in claim 1, wherein the minimum power is the minimum power of a plurality of frequency domain samples derived from the time-limited part of the audio signal.

7. A signal processor as claimed in claim 1, wherein the minimum power is the derivative of the minimum power of a plurality of time domain samples derived from the time-limited part of the audio signal.

8. A signal processor as claimed in claim 1, wherein the minimum power is the derivative of the minimum power of a plurality of frequency domain samples derived from the time-limited part of the audio signal.

9. A signal processor as claimed in claim 1, wherein in a first mode of operation the noise estimation function is configured to estimate noise in the audio signal as the product of the power values output by the filter function and the correction factor formed by the correction function divided by a predetermined scaling factor that is greater than one.

10. A signal processor as claimed in claim 9, wherein the noise estimation function is configured to operate in the first mode of operation if the correction factor is below a first predetermined threshold.

11. A signal processor as claimed in claim 1, wherein in a second mode of operation the noise estimation function is configured to estimate noise in the audio signal as the power values output by the filter function if the correction factor formed by the correction function is between a/the first threshold and a second threshold.

12. A signal processor as claimed in claim 1, wherein in a third mode of operation the noise estimation function is configured to estimate noise in the audio signal as the product of the power values output by the filter function and the correction factor formed by the correction function.

13. A signal processor as claimed in claim 12, wherein the noise estimation function is configured to operate in the third mode of operation if the correction factor is between a/the second threshold and a third threshold.

14. A signal processor as claimed in claim 9, wherein in a fourth mode of operation the noise estimation function is configured to estimate noise in the audio signal in dependence on the estimated minimum power value divided by a representation of the breadth of the frequency spectrum that contributed to that value.

15. A signal processor as claimed in claim 14, wherein the noise estimation function is configured to operate in the fourth mode of operation if the correction factor is above a/the third predetermined threshold.

16. A method for estimating noise power in an audio signal, the method comprising:

generating a series of power values, each power value representing the power in the audio signal at a respective one of a plurality of frequency bands;

analysing successive portions of the audio signal to assess whether each portion contains features characteristic of speech, and classifying each portion in dependence on that analysis;

estimating a minimum power value in a time-limited part of the audio signal, estimating the total noise power in that part of the audio signal and forming a correction factor dependent on the ratio of the minimum power value to the estimated total noise power, the method comprising estimating the minimum power value and the total noise power over only those portions of the time-limited part of the signal that have been classified in the analysing step as being less characteristic of speech; and

estimating noise in the audio signal in dependence on the estimated power values and the formed correction factor.

18. A method as claimed in claim 16, comprising analysing the portions of the audio signal to detect harmonicity therein and classifying each portion in dependence on that analysis.

19. A method as claimed in claim 16, comprising analysing the portions of the audio signal to detect pitch characteristics therein and classifying each portion in dependence on that analysis.

20. A method as claimed in claim 16, wherein the minimum power is the minimum power of a plurality of time domain samples derived from the time-limited part of the audio signal.

21. A method as claimed in claim 16, wherein the minimum power is the minimum power of a plurality of frequency domain samples derived from the time-limited part of the audio signal.

22. A method as claimed in claim 16, wherein the minimum power is the derivative of the minimum power of a plurality of time domain samples derived from the time-limited part of the audio signal.

23. A method as claimed in claim 16, wherein the minimum power is the derivative of the minimum power of a plurality of frequency domain samples derived from the time-limited part of the audio signal.

24. A method as claimed in claim 16, comprising:

in a first mode of operation estimating noise in the audio signal as the product of the power values output by the filter function and the correction factor formed by the correction function divided by a predetermined scaling factor that is greater than one.

25. A method as claimed in claim 24, comprising operating in the first mode of operation if the correction factor is below a first predetermined threshold.

26. A method as claimed in claim 16, comprising:

in a second mode of operation estimating noise in the audio signal as the power values output by the filter function if the correction factor formed by the correction function is between a/the first threshold and a second threshold.

27. A method as claimed in claim 16, comprising:

in a third mode of operation estimating noise in the audio signal as the product of the power values output by the filter function and the correction factor formed by the correction function.

28. A method as claimed in claim 27, comprising operating in the third mode of operation if the correction factor is between a/the second threshold and a third threshold.

29. A method as claimed in claim 16, comprising:

in a fourth mode of operation estimating noise in the audio signal in dependence on the estimated minimum power value divided by a representation of the breadth of the frequency spectrum that contributed to that value.

30. A method as claimed in claim 29, comprising operating in the fourth mode of operation if the correction factor is above a/the third predetermined threshold.

17. A method as claimed in claim 17, wherein the step of generating a series of power values comprises implementing a Fourier transform.

31. A signal processor for estimating noise in an audio signal, the signal processor comprising:

a frequency analysis function for performing frequency analysis on the audio signal to periodically determine the power of the signal in each of a plurality of frequency ranges;

an aggregation function for forming a plurality of power data sets, each of the power data sets representing the powers determined by the frequency analysis function over a respective frequency range and over a time period, and each of the components of at least one of the power data sets being formed by combining the powers determined by the frequency analysis function for two or more frequency ranges; and

a minimisation function for determining the minima of each of the power data sets; and

a noise estimation function for estimating noise in the audio signal in dependence on the minima determined by the minimisation function.

32. A signal processor as claimed in claim 31, wherein the noise estimation function is configured to estimate noise in the audio signal by forming one or more first noise estimates in dependence on the audio signal and modifying that/those first noise estimate(s) in dependence on the minima determined by the minimisation function.

33. A signal processor as claimed in claim 31, wherein there are only two power data sets.

34. A signal processor as claimed in claim 31, wherein each of the components of all of the power data sets are formed by combining the powers determined by the frequency analysis function for two or more frequency ranges.

35. A signal processor as claimed in claim 31, wherein the frequency analysis function implements a Fourier transform.

36. A signal processor as claimed in claim 31, wherein signal processor is configured to amplify each of the determined powers of the signal in each of the plurality of frequency ranges by a respective gain value, and re-synthesise an audio signal in dependence on the outputs of those amplifications so as to form a noise reduced signal.

37. A signal processor as claimed in claim 31, wherein each time period spans a plurality of frames and the minimisation function is configured to determine the minima of each of the power data sets for a time period as being the minimum of the powers determined by the frequency analysis function over a respective frequency range for individual frames during that time period.

38. A signal processor as claimed in claim 31, wherein the or each of the power data sets that is formed by combining the powers determined by the frequency analysis function for two or more frequency ranges is formed by combining the powers determined by the frequency analysis function for adjacent frequency ranges.

39. A method for estimating noise in an audio signal, the method comprising:

performing frequency analysis on the audio signal to periodically determine the power of the signal in each of a plurality of frequency ranges;

forming a plurality of power data sets, each of the power data sets representing the powers determined over a respective frequency range and over a time period, and each of the components of at least one of the power data sets being formed by combining the powers determined by the frequency analysis function for two or more frequency ranges; and

determining the minima of each of the power data sets; and

estimating noise in the audio signal in dependence on the determined minima.

40. A method as claimed in claim 39, comprising estimating noise in the audio signal by forming one or more first noise estimates in dependence on the audio signal and modifying that/those first noise estimate(s) in dependence on the determined minima.

41. A method as claimed in claim 39, wherein there are only two power data sets.

42. A method as claimed in claim 39, wherein each of the components of all of the power data sets are formed by combining the powers determined for two or more frequency ranges.

43. A method as claimed in claim 39, wherein the step of performing frequency analysis comprises implementing a Fourier transform.

44. A method as claimed in claim 39, comprising amplifying each of the determined powers of the signal in each of the plurality of frequency ranges by a respective gain value, and re-synthesising an audio signal in dependence on the outputs of those amplifications so as to form a noise reduced signal.

45. A method as claimed in claim 39, wherein each time period spans a plurality of frames and the method comprises determining the minima of each of the power data sets for a time period as being the minimum of the powers determined over a respective frequency range for individual frames during that time period.

46. A method as claimed in claim 39, wherein the or each of the power data sets that is formed by combining the powers determined for two or more frequency ranges is formed by combining the powers determined for adjacent frequency ranges.

47. A signal processor for reducing noise in an audio signal, the signal processor comprising:

an analysis function for analysing the audio signal to form one or more first intermediate signals;

a gain function for applying a determined gain to the or each first intermediate signal to form one or more second intermediate signals; and

a synthesis function for synthesising a reduced noise audio signal from the second intermediate signal(s); and

a gain determination function configured to determine the gain to be applied to the or each first intermediate signal as the Weiner gain of the respective intermediate signal smoothed by the instantaneous variance of the Weiner gain.

48. A signal processor as claimed in claim 47, wherein the analysis function implements a frequency analysis of the audio signal to form the intermediate signals, and each of the intermediate signals is representative of the power in the audio signal in a respective frequency range.

49. A signal processor as claimed in claim 48, wherein the analysis function implements the frequency analysis by means of a Fourier transform.

50. A signal processor as claimed in claim 48, wherein the analysis function downsamples the results of the frequency analysis to form the intermediate signals.

51. A signal processor as claimed in claim 47, wherein the synthesis function implements an inverse frequency analysis in dependence on the second intermediate signals to form the reduced noise audio signal.

52. A signal processor as claimed in claim 51, wherein the synthesis function implements the inverse frequency analysis by means of an inverse Fourier transform.

53. A signal processor as claimed in claim 47, wherein the synthesis function upsamples second intermediate signals to form upsampled signals and the inverse frequency analysis is performed on the upsampled signals.

54. A signal processor as claimed in claim 51, wherein there are a plurality of second intermediate signals, each formed in dependence on a respective one of a plurality of first intermediate signals, and wherein the synthesis function synthesises each of a plurality of reduced noise audio signals in dependence on a respective one of the second intermediate signals and the said reduced noise signal is formed as the aggregate of the said plurality of reduced noise audio signals.

55. A method for reducing noise in an audio signal, the method comprising:

analysing the audio signal to form one or more first intermediate signals;

applying a determined gain to the or each first intermediate signal to form one or more second intermediate signals; and

synthesising a reduced noise audio signal from the second intermediate signal(s); and

determining the gain to be applied to the or each first intermediate signal as the Weiner gain of the respective intermediate signal smoothed by the instantaneous variance of the Weiner gain.

56. A method as claimed in claim 55, wherein the method comprises implementing a frequency analysis of the audio signal to form the intermediate signals, and wherein each of the intermediate signals is representative of the power in the audio signal in a respective frequency range.

57. A method as claimed in claim 56, comprising implementing the frequency analysis by means of a Fourier transform.

58. A method as claimed in claim 56, comprising downsampling the results of the frequency analysis to form the intermediate signals.

59. A method as claimed in claim 55, comprising implementing an inverse frequency analysis in dependence on the second intermediate signals to form the reduced noise audio signal.

60. A method as claimed in claim 59, comprising implementing the inverse frequency analysis by means of an inverse Fourier transform.

61. A method as claimed in claim 55, comprising upsampling second intermediate signals to form upsampled signals and performing the inverse frequency analysis on the upsampled signals.

62. A method as claimed in claim 59, wherein there are a plurality of second intermediate signals, each formed in dependence on a respective one of a plurality of first intermediate signals, and wherein the method comprises synthesising each of a plurality of reduced noise audio signals in dependence on a respective one of the second intermediate signals and forming the said reduced noise signal as the aggregate of the said plurality of reduced noise audio signals.

63. A signal processor for reducing noise in an audio signal, the signal processor comprising:

an analysis function for analysing the audio signal to form one or more first intermediate signals;

a gain function for applying a determined gain to the or each first intermediate signal to form one or more second intermediate signals; and

a synthesis function for synthesising a reduced noise audio signal from the second intermediate signal(s);

a signal classification function for analysing successive portions of the audio signal to assess whether each portion contains features characteristic of speech, and for classifying each portion in dependence on that analysis;

a gain determination function configured to determine the gain to be applied to each portion of the or each first intermediate signal according to a first algorithm if the portion of the audio signal corresponding to that portion of the first intermediate signal has been classified by the signal classification function as containing features characteristic of speech, and according to a second algorithm otherwise.

64. A signal processor as claimed in claim 63, wherein the first algorithm is one that has the effect of reducing noise by a lesser amount than the second algorithm.

65. A signal processor as claimed in claim 63, wherein the second algorithm is computationally less intensive than the second algorithm.

66. A signal processor as claimed in claim 63, wherein the first algorithm is based on the MMSE-LSA gain function.

67. A signal processor as claimed in claim 63, wherein the first algorithm is based on the Weiner gain function.

68. A method for reducing noise in an audio signal, the method comprising:

an analysis function for analysing the audio signal to form one or more first intermediate signals;

a gain function for applying a determined gain to the or each first intermediate signal to form one or more second intermediate signals; and

a synthesis function for synthesising a reduced noise audio signal from the second intermediate signal(s);

a signal classification function for analysing successive portions of the audio signal to assess whether each portion contains features characteristic of speech, and for classifying each portion in dependence on that analysis;

a gain determination function configured to determine the gain to be applied to each portion of the or each first intermediate signal according to a first algorithm if the portion of the audio signal corresponding to that portion of the first intermediate signal has been classified by the signal classification function as containing features characteristic of speech, and according to a second algorithm otherwise.

69. A method as claimed in claim 68, wherein the first algorithm is one that has the effect of reducing noise by a lesser amount than the second algorithm.

70. A signal processor as claimed in claim 68, wherein the second algorithm is computationally less intensive than the second algorithm.

71. A method as claimed in claim 68, wherein the first algorithm is based on the MMSE-LSA gain function.

72. A method as claimed in claim 68, wherein the first algorithm is based on the Weiner gain function.