VOICE ACTIVITY DETECTION IN PRESENCE OF BACKGROUND NOISE

• US 20130191117A1
• Filed: 11/06/2012
• Published: 07/25/2013
• Est. Priority Date: 01/20/2012
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Atti, Venkatraman Srinivasa, Krishnan, Venkatesh
• Granted Patent: US 9,099,098 B2
• Time in Patent Office: Days
• US Class Current: 704/226
• CPC Class Codes: G10L 25/84 for discriminating voice from noise

Abstract

In speech processing systems, compensation is made for sudden changes in the background noise in the average signal-to-noise ratio (SNR) calculation. SNR outlier filtering may be used, alone or in conjunction with weighting the average SNR. Adaptive weights may be applied on the SNRs per band before computing the average SNR. The weighting function can be a function of noise level, noise type, and/or instantaneous SNR value. Another weighting mechanism applies a null filtering or outlier filtering which sets the weight in a particular band to be zero. This particular band may be characterized as the one that exhibits an SNR that is several times higher than the SNRs in other bands.

Claims

1. A method for detecting voice activity in the presence of background noise, comprising:

receiving one or more input frames of sound at a voice activity detector of a mobile station;

determining at least one noise characteristic of each of the input frames;

determining a plurality of bands based on the noise characteristics;

determining a signal-to-noise ratio (SNR) value per band based on the noise characteristics;

determining at least one outlier band;

determining a weighting based on the at least one outlier band;

applying the weighting on the SNRs per band; and

detecting the presence or absence of voice activity using the weighted SNRs per band.

2. The method of claim 1, further comprising performing SNR outlier filtering.

3. The method of claim 1, wherein each noise characteristic comprises at least one of a noise level variation, a noise type, or an instantaneous SNR value.

4. The method of claim 3, wherein determining the plurality of bands based on the noise characteristics comprises determining the plurality of bands based on at least one of the noise level variations or the noise types.

5. The method of claim 3, wherein determining the SNR value per band comprises determining a modified instantaneous SNR value per band based on at least one of the noise level variations or the noise types.

6. The method of claim 5, wherein determining the modified instantaneous SNR value per band comprises:

selectively smoothing present estimates of signal energies per band using past estimates of signal energies per band based on at least the instantaneous SNR of the input frame;

selectively smoothing present estimates of noise energies per band using past estimates of noise energies per band based on at least the noise level variations and the noise types; and

determining ratios of smoothed estimates of signal energies and smoothed estimates of noise energies per band.

7. The method of claim 6, wherein a modified instantaneous SNR in any one of the bands is greater than a sum of modified instantaneous SNRs in a remainder of the bands.

8. The method of claim 5, wherein determining the weighting based on the at least one outlier band comprises determining an adaptive weighting function based on at least one of the noise level variations, the noise types, the locations of the outlier bands, or the modified instantaneous SNR value per band.

9. The method of claim 8, wherein applying the weighting on the SNRs per band comprises applying the adaptive weighting function on the modified instantaneous SNRs per band.

10. The method of claim 9, further comprising:

determining a weighted average SNR per input frame by adding the weighted modified instantaneous SNRs across the bands; and

comparing the weighted average SNR against a threshold to detect the presence or absence of signal or voice activity.

11. The method of claim 10, wherein comparing the weighted average SNR against a threshold to detect the presence or absence of signal or voice activity comprises:

determining a difference between the weighted average SNR and the threshold in each band;

applying a weight to each difference;

adding the weighted differences together; and

determining whether or not there is voice activity by comparing the added weighted differences with another threshold.

12. The method of claim 11, wherein the threshold is zero, and if the added weighted differences are greater than zero, then determining there is voice activity and otherwise determining that there is no voice activity.

13. The method of claim 8, further comprising performing SNR outlier filtering comprising:

sorting the modified instantaneous SNR values in the bands in a monotonic order;

determining which of the bands are the outlier bands; and

updating the adaptive weighting function by setting the weight associated with the outlier bands to zero.

14. An apparatus for detecting voice activity in the presence of background noise, comprising:

means for receiving one or more input frames of sound;

means for determining at least one noise characteristic of each of the input frames;

means for determining a plurality of bands based on the noise characteristics;

means for determining a signal-to-noise ratio (SNR) value per band based on the noise characteristics;

means for determining at least one outlier band;

means for determining a weighting based on the at least one outlier band;

means for applying the weighting on the SNRs per band; and

means for detecting the presence or absence of voice activity using the weighted SNRs per band.

15. The apparatus of claim 14, further comprising means for performing SNR outlier filtering.

16. The apparatus of claim 14, wherein each noise characteristic comprises at least one of a noise level variation, a noise type, or an instantaneous SNR value.

17. The apparatus of claim 16, wherein the means for determining the plurality of bands based on the noise characteristics comprises means for determining the plurality of bands based on at least one of the noise level variations or the noise types.

18. The apparatus of claim 16, wherein the means for determining the SNR value per band comprises means for determining a modified instantaneous SNR value per band based on at least one of the noise level variations or the noise types.

19. The apparatus of claim 18, wherein the means for determining the modified instantaneous SNR value per band comprises:

means for selectively smoothing present estimates of signal energies per band using past estimates of signal energies per band based on at least the instantaneous SNR of the input frame;

means for selectively smoothing present estimates of noise energies per band using past estimates of noise energies per band based on at least the noise level variations and the noise types; and

means for determining ratios of smoothed estimates of signal energies and smoothed estimates of noise energies per band.

20. The apparatus of claim 19, wherein a modified instantaneous SNR in any one of the bands is greater than a sum of modified instantaneous SNRs in a remainder of the bands.

21. The apparatus of claim 18, wherein the means for determining the weighting based on the at least one outlier band comprises means for determining an adaptive weighting function based on at least one of the noise level variations, the noise types, the locations of the outlier bands, or the modified instantaneous SNR value per band.

22. The apparatus of claim 21, wherein the means for applying the weighting on the SNRs per band comprises means for applying the adaptive weighting function on the modified instantaneous SNRs per band.

23. The apparatus of claim 22, further comprising:

means for determining a weighted average SNR per input frame by adding the weighted modified instantaneous SNRs across the bands; and

means for comparing the weighted average SNR against a threshold to detect the presence or absence of signal or voice activity.

24. The apparatus of claim 23, wherein the means for comparing the weighted average SNR against a threshold to detect the presence or absence of signal or voice activity comprises:

means for determining a difference between the weighted average SNR and the threshold in each band;

means for applying a weight to each difference;

means for adding the weighted differences together; and

means for determining whether or not there is voice activity by comparing the added weighted differences with another threshold.

25. The apparatus of claim 24, wherein the threshold is zero, and if the added weighted differences are greater than zero, then determining there is voice activity and otherwise determining that there is no voice activity.

26. The apparatus of claim 21, further comprising means for performing SNR outlier filtering comprising:

means for sorting the modified instantaneous SNR values in the bands in a monotonic order;

means for determining which of the bands are the outlier bands; and

means for updating the adaptive weighting function by setting the weight associated with the outlier bands to zero.

27. A computer-readable medium comprising instructions that cause a computer to:

receive one or more input frames of sound;

determine at least one noise characteristic of each of the input frames;

determine a plurality of bands based on the noise characteristics;

determine a signal-to-noise ratio (SNR) value per band based on the noise characteristics;

determine at least one outlier band;

determine a weighting based on the at least one outlier band;

apply the weighting on the SNRs per band; and

detect the presence or absence of voice activity using the weighted SNRs per band.

28. The computer-readable medium of claim 27, further comprising computer-executable instructions that cause the computer to perform SNR outlier filtering.

29. The computer-readable medium of claim 27, wherein each noise characteristic comprises at least one of a noise level variation, a noise type, or an instantaneous SNR value.

30. The computer-readable medium of claim 29, wherein the instructions that cause the computer to determine the plurality of bands based on the noise characteristics comprise instructions that cause the computer to determine the plurality of bands based on at least one of the noise level variations or the noise types.

31. The computer-readable medium of claim 29, wherein the instructions that cause the computer to determine the SNR value per band comprise instructions that cause the computer to determine a modified instantaneous SNR value per band based on at least one of the noise level variations or the noise types.

32. The computer-readable medium of claim 31, wherein the instructions that cause the computer to determine the modified instantaneous SNR value per band comprise instructions that cause the computer to:

selectively smooth present estimates of signal energies per band using past estimates of signal energies per band based on at least the instantaneous SNR of the input frame;

selectively smooth present estimates of noise energies per band using past estimates of noise energies per band based on at least the noise level variations and the noise types; and

determine ratios of smoothed estimates of signal energies and smoothed estimates of noise energies per band.

33. The computer-readable medium of claim 32, wherein a modified instantaneous SNR in any one of the bands is greater than a sum of modified instantaneous SNRs in a remainder of the bands.

34. The computer-readable medium of claim 31, wherein the instructions that cause the computer to determine the weighting based on the at least one outlier band comprise instructions that cause the computer to determine an adaptive weighting function based on at least one of the noise level variations, the noise types, the locations of the outlier bands, or the modified instantaneous SNR value per band.

35. The computer-readable medium of claim 34, wherein the instructions that cause the computer to apply the weighting on the SNRs per band comprise instructions that cause the computer to apply the adaptive weighting function on the modified instantaneous SNRs per band.

36. The computer-readable medium of claim 35, further comprising computer-executable instructions that cause the computer to:

determine a weighted average SNR per input frame by adding the weighted modified instantaneous SNRs across the bands; and

compare the weighted average SNR against a threshold to detect the presence or absence of signal or voice activity.

37. The computer-readable medium of claim 36, wherein the instructions that cause the computer to compare the weighted average SNR against a threshold to detect the presence or absence of signal or voice activity comprise instructions that cause the computer to:

determine a difference between the weighted average SNR and the threshold in each band;

apply a weight to each difference;

add the weighted differences together; and

determine whether or not there is voice activity by comparing the added weighted differences with another threshold.

38. The computer-readable medium of claim 37, wherein the threshold is zero, and if the added weighted differences are greater than zero, then determining there is voice activity and otherwise determining that there is no voice activity.

39. The computer-readable medium of claim 34, further comprising computer-executable instructions that cause the computer to perform SNR outlier filtering comprising:

sorting the modified instantaneous SNR values in the bands in a monotonic order;

determining which of the bands are the outlier bands; and

updating the adaptive weighting function by setting the weight associated with the outlier bands to zero.

40. A voice activity detector for detecting voice activity in the presence of background noise, comprising:

a receiver that receives one or more input frames of sound;

a processor that determines at least one noise characteristic of each of the input frames, and determines a plurality of bands based on the noise characteristics;

a signal-to-noise ratio (SNR) module that determines a SNR value per band based on the noise characteristics;

an outlier filter that determines at least one outlier band;

a weighting module that determines a weighting based on the at least one outlier band, and applies the weighting on the SNRs per band; and

a decision module that detects the presence or absence of voice activity using the weighted SNRs per band.

41. The voice activity detector of claim 40, wherein the outlier filter performs SNR outlier filtering.

42. The voice activity detector of claim 40, wherein each noise characteristic comprises at least one of a noise level variation, a noise type, or an instantaneous SNR value.

43. The voice activity detector of claim 42, wherein the processor determines the plurality of bands based on at least one of the noise level variations or the noise types.

44. The voice activity detector of claim 42, wherein the SNR computation module determines a modified instantaneous SNR value per band based on at least one of the noise level variations or the noise types.

45. The voice activity detector of claim 44, wherein the SNR computation module:

selectively smoothes present estimates of signal energies per band using past estimates of signal energies per band based on at least the instantaneous SNR of the input frame;

selectively smoothes present estimates of noise energies per band using past estimates of noise energies per band based on at least the noise level variations and the noise types; and

determines ratios of smoothed estimates of signal energies and smoothed estimates of noise energies per band.

46. The voice activity detector of claim 45, wherein a modified instantaneous SNR in any one of the bands is greater than a sum of modified instantaneous SNRs in a remainder of the bands.

47. The voice activity detector of claim 44, wherein the weighting module determines an adaptive weighting function based on at least one of the noise level variations, the noise types, the locations of the outlier bands, or the modified instantaneous SNR value per band.

48. The voice activity detector of claim 47, wherein the weighting module applies the adaptive weighting function on the modified instantaneous SNRs per band.

49. The voice activity detector of claim 48, wherein the SNR computation module determines a weighted average SNR per input frame by adding the weighted modified instantaneous SNRs across the bands, and the decision module compares the weighted average SNR against a threshold to detect the presence or absence of signal or voice activity.

50. The voice activity detector of claim 49, wherein the decision module determines a difference between the weighted average SNR and the threshold in each band, applies a weight to each difference, adds the weighted differences together, and determines whether or not there is voice activity by comparing the added weighted differences with another threshold.

51. The voice activity detector of claim 50, wherein the threshold is zero, and if the added weighted differences are greater than zero, then the decision module determines there is voice activity and otherwise determines that there is no voice activity.

52. The voice activity detector of claim 47, wherein the outlier filter sorts the modified instantaneous SNR values in the bands in a monotonic order, determines which of the bands are the outlier bands, and updates the adaptive weighting function by setting the weight associated with the outlier bands to zero.