SYSTEMS, METHODS, AND APPARATUS FOR SIGNAL SEPARATION

• US 20090022336A1
• Filed: 08/25/2008
• Published: 01/22/2009
• Est. Priority Date: 02/26/2007
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Visser, Erik, Chan, Kwokleung, Park, Hyun Jin
• Granted Patent: US 8,160,273 B2
• Time in Patent Office: Days
• US Class Current: 381/94.700
• CPC Class Codes: G10L 21/0272 Voice signal separating

Abstract

Methods, apparatus, and systems for source separation include a converged plurality of coefficient values that is based on each of a plurality of M-channel signals. Each of the plurality of M-channel signals is based on signals produced by M transducers in response to at least one information source and at least one interference source. In some examples, the converged plurality of coefficient values is used to filter an M-channel signal to produce an information output signal and an interference output signal.

Claims

1. A method of signal processing, said method comprising:

based on a plurality of M-channel training signals, training a plurality of coefficient values of a source separation filter structure to obtain a converged source separation filter structure, where M is an integer greater than one; and

deciding whether the converged source separation filter structure sufficiently separates each of the plurality of M-channel training signals into at least an information output signal and an interference output signal,

wherein at least one of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a first spatial configuration, and

wherein another of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a second spatial configuration different than the first spatial configuration.

2. The method of signal processing according to claim 1, wherein said training a plurality of coefficient values comprises updating the plurality of coefficient values of the source separation filter structure based on each of the plurality of M-channel training signals.

3. The method of signal processing according to claim 1, wherein said deciding comprises comparing information from said at least one information source with an output of the converged source separation filter structure.

4. The method of signal processing according to claim 1, wherein at least one of the plurality of M-channel training signals includes interference from an interference source having a first spectral signature, and

wherein another of the plurality of M-channel training signals includes interference from an interference source having a second spectral signature different than the first spectral signature.

5. The method of signal processing according to claim 1, wherein at least one of the plurality of M-channel training signals includes information from an information source having a first spectral signature, and

wherein another of the plurality of M-channel training signals includes information from an information source having a second spectral signature different than the first spectral signature.

6. The method of signal processing according to claim 1, wherein, within the first spatial configuration, the M microphones are disposed in an array that is oriented in a first spatial orientation relative to the at least one information source, and

wherein, within the second spatial configuration, the M microphones are disposed in an array that is oriented in a second spatial orientation relative to the at least one information source, and

wherein the second spatial orientation is different than the first spatial orientation.

7. The method of signal processing according to claim 1, wherein said training a plurality of coefficient values of a source separation filter structure includes calculating an update to the plurality of coefficient values based on a nonlinear bounded function.

8. The method of signal processing according to claim 1, wherein said deciding comprises:

based on a trained plurality of coefficient values of the converged source separation filter structure, calculating a corresponding beam pattern; and

comparing the calculated beam pattern to information relating to the relative dispositions of microphones and sources in at least one among the first and second spatial configurations.

9. The method of signal processing according to claim 1, wherein said method comprises, based on a trained plurality of coefficient values of the converged source separation filter structure, filtering an M-channel signal in real time to obtain a real-time information output signal.

10. The method of signal processing according to claim 9, wherein, within the first spatial configuration, the M microphones are arranged relative to one another in a third spatial configuration, and

wherein the M-channel signal is based on signals produced by an array of M microphones that are arranged relative to one another in the third spatial configuration.

11. The method of signal processing according to claim 9, wherein said filtering an M-channel signal includes reassigning a frequency bin of one among (A) an information output channel and (B) an interference output channel to the other among the two channels.

12. The method of signal processing according to claim 9, said method comprising performing an echo cancellation operation on at least one among (A) the M-channel signal and (B) a signal that is based on the real-time information output signal.

13. The method of signal processing according to claim 9, said method comprising:

based on a trained plurality of coefficient values of the converged source separation filter structure, generating initial conditions for an adaptive filter;

initializing the adaptive filter according to the initial conditions; and

subsequent to said initializing, using the adaptive filter to filter a signal that is based on the real-time information output signal,

wherein said initial conditions include at least one among (A) an initial plurality of tap weights of the adaptive filter and (B) an initial history of the adaptive filter.

14. The method of signal processing according to claim 13, wherein said using an adaptive filter includes, based on a characteristic of the real-time information output signal, attenuating the signal that is based on the real-time information output signal.

15. The method of signal processing according to claim 13, wherein said using the adaptive filter to filter a signal that is based on the information output signal includes using the adaptive filter to produce a interference reference signal, and

wherein said method comprises, based on the interference reference signal, performing a noise reduction operation on a signal that is based on the real-time information output signal.

16. The method of signal processing according to claim 13, wherein said generating initial conditions comprises:

subsequent to said deciding, and based on a trained plurality of coefficient values of the converged source separation filter structure, filtering a second plurality of M-channel training signals to obtain a filtered training signal; and

based on the filtered training signal, training a second plurality of coefficient values of a second source separation filter structure to obtain said initial conditions.

17. The method of signal processing according to claim 16, wherein said method comprises, based on information from the real-time information output signal, updating the trained second plurality of coefficient values.

18. The method of signal processing according to claim 9, said method comprising:

using a plurality of microphones to capture an M-channel captured signal, wherein the M-channel signal is based on the M-channel captured signal; and

subsequent to said filtering an M-channel signal in real time, recalibrating a gain of at least one of the plurality of microphones.

19. The method of signal processing according to claim 9, said method comprising, subsequent to said filtering an M-channel signal in real time, and based on a plurality of M-channel training signals, training a plurality of coefficient values of a source separation filter structure to obtain a second converged source separation filter structure.

20. The method of signal processing according to claim 1, wherein said deciding comprises deciding whether the converged source separation filter structure sufficiently concentrates a directional component of each of the plurality of M-channel training signals.

21. An apparatus for signal processing, said apparatus comprising:

an array of M microphones, where M is an integer greater than one; and

a source separation filter structure having a trained plurality of coefficient values,

wherein said source separation filter structure is configured to receive an M-channel signal that is based on signals produced by the array of M microphones and to filter the M-channel signal in real time to obtain a real-time information output signal, and

wherein the trained plurality of coefficient values is based on a plurality of M-channel training signals, and

wherein one of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a first spatial configuration, and

wherein another of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a second spatial configuration different than the first spatial configuration.

22. The apparatus for signal processing according to claim 21, wherein said apparatus comprises a mobile user terminal that includes said array and said source separation filter structure.

23. The apparatus for signal processing according to claim 21, wherein said apparatus comprises a wireless headset that includes said array and said source separation filter structure.

24. The apparatus for signal processing according to claim 21, wherein the M microphones of the array are arranged relative to one another in a third spatial configuration, and

wherein, within the first spatial configuration, the M microphones are arranged relative to one another in the third spatial configuration.

25. The apparatus for signal processing according to claim 21, wherein, within the first spatial configuration, the array is oriented in a first direction relative to the at least one information source, and

wherein, within the second spatial configuration, the array is oriented in a second direction relative to the at least one information source, and

wherein the second direction is different than the first direction.

26. The apparatus for signal processing according to claim 21, wherein the trained plurality of coefficient values is calculated, based on a nonlinear bounded function, from a plurality of coefficient values.

27. The apparatus for signal processing according to claim 21, wherein said source separator filter structure is configured to filter the M-channel signal by reassigning a frequency bin of one among (A) an information output channel and (B) an interference output channel to the other among the two channels.

28. The apparatus for signal processing according to claim 21, said apparatus comprising an adaptive filter arranged to filter a signal that is based on the real-time information output signal,

wherein said adaptive filter is initialized according to initial conditions that are based on a trained plurality of coefficient values of the converged source separation filter structure, said initial conditions including at least one among (A) an initial plurality of tap weights of the adaptive filter and (B) an initial history of the adaptive filter.

29. The apparatus for signal processing according to claim 28, wherein said adaptive filter is configured to perform a scaling operation, based on a characteristic of the information output signal, on the signal that is based on the real-time information output signal.

30. The apparatus for signal processing according to claim 28, wherein said adaptive filter is configured to produce an interference reference signal, and

wherein said apparatus includes a noise reduction filter configured to perform a noise reduction operation, based on the interference reference signal, on a signal that is based on the real-time information output signal.

31. The apparatus for signal processing according to claim 28, wherein said initial conditions are based on a filtered training signal, and

wherein said filtered training signal is based on a second plurality of M-channel training signals as filtered using a trained plurality of coefficient values of the source separation filter structure.

32. The apparatus for signal processing according to claim 31, wherein said adaptive filter is configured to adapt the trained second plurality of coefficient values based on information from the real-time information output signal.

33. The apparatus for signal processing according to claim 21, wherein said source separation filter structure is configured to concentrate a directional component of the M-channel signal.

34. The apparatus for signal processing according to claim 21, said apparatus comprising an echo canceller configured to perform an echo cancellation operation on at least one among (A) the M-channel signal and (B) a signal that is based on the real-time information output signal.

35. A computer-readable medium comprising instructions which when executed by a processor cause the processor to:

train a plurality of coefficient values of a source separation filter structure, based on a plurality of M-channel training signals, to obtain a converged source separation filter structure, where M is an integer greater than one; and

decide whether the converged source separation filter structure sufficiently separates each of the plurality of M-channel training signals into at least an information output signal and an interference output signal,

wherein at least one of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a first spatial configuration, and

wherein another of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a second spatial configuration different than the first spatial configuration.

36. The computer-readable medium according to claim 35, wherein said instructions which when executed by a processor cause the processor to train a plurality of coefficient values comprise instructions which when executed by a processor cause the processor to update the plurality of coefficient values of the source separation filter structure based on each of the plurality of M-channel training signals.

37. The computer-readable medium according to claim 35, wherein said instructions which when executed by a processor cause the processor to decide comprise instructions which when executed by a processor cause the processor to compare information from said at least one information source with an output of the converged source separation filter structure.

38. The computer-readable medium according to claim 35, wherein at least one of the plurality of M-channel training signals includes interference from an interference source having a first spectral signature, and

wherein another of the plurality of M-channel training signals includes interference from an interference source having a second spectral signature different than the first spectral signature.

39. The computer-readable medium according to claim 35, wherein at least one of the plurality of M-channel training signals includes information from an information source having a first spectral signature, and

wherein another of the plurality of M-channel training signals includes information from an information source having a second spectral signature different than the first spectral signature.

40. The computer-readable medium according to claim 35, wherein, within the first spatial configuration, the M microphones are disposed in an array that is oriented in a first spatial orientation relative to the at least one information source, and

wherein, within the second spatial configuration, the M microphones are disposed in an array that is oriented in a second spatial orientation relative to the at least one information source, and

wherein the second spatial orientation is different than the first spatial orientation.

41. The computer-readable medium according to claim 35, wherein said instructions which when executed by a processor cause the processor to train a plurality of coefficient values of a source separation filter structure include instructions which when executed by a processor cause the processor to calculate an update to the plurality of coefficient values based on a nonlinear bounded function.

42. The computer-readable medium according to claim 35, wherein said instructions which when executed by a processor cause the processor to decide include instructions which when executed by a processor cause the processor to:

calculate, based on a trained plurality of coefficient values of the converged source separation filter structure, a corresponding beam pattern; and

compare the calculated beam pattern to information relating to the relative dispositions of microphones and sources in at least one among the first and second spatial configurations.

43. The computer-readable medium according to claim 35, wherein said medium comprises instructions which when executed by a processor cause the processor to filter an M-channel signal in real time, based on a trained plurality of coefficient values of the converged source separation filter structure, to obtain a real-time information output signal.

44. The computer-readable medium according to claim 43, wherein, within the first spatial configuration, the M microphones are arranged relative to one another in a third spatial configuration, and

wherein the M-channel signal is based on signals produced by an array of M microphones that are arranged relative to one another in the third spatial configuration.

45. The method of signal processing according to claim 43, wherein said instructions which when executed by a processor cause the processor to filter an M-channel signal include instructions which when executed by a processor cause the processor to reassign a frequency bin of one among (A) an information output channel and (B) an interference output channel to the other among the two channels.

46. The computer-readable medium according to claim 43, said medium comprising instructions which when executed by a processor cause the processor to perform an echo cancellation operation on at least one among (A) the M-channel signal and (B) a signal that is based on the real-time information output signal.

47. The computer-readable medium according to claim 43, said medium comprising instructions which when executed by a processor cause the processor to:

generate initial conditions, based on a trained plurality of coefficient values of the converged source separation filter structure, for an adaptive filter;

initialize the adaptive filter according to the initial conditions; and

subsequent to said initializing, use the adaptive filter to filter a signal that is based on the real-time information output signal,

wherein said initial conditions include at least one among (A) an initial plurality of tap weights of the adaptive filter and (B) an initial history of the adaptive filter.

48. The computer-readable medium according to claim 47, wherein said instructions which when executed by a processor cause the processor to use an adaptive filter include instructions which when executed by a processor cause the processor to, attenuate, based on a characteristic of the real-time information output signal, the signal that is based on the real-time information output signal.

49. The computer-readable medium according to claim 47, wherein said instructions which when executed by a processor cause the processor to use the adaptive filter to filter a signal that is based on the real-time information output signal include instructions which when executed by a processor cause the processor to use the adaptive filter to produce a interference reference signal, and

wherein said medium comprises instructions which when executed by a processor cause the processor to perform a noise reduction operation, based on the interference reference signal, on a signal that is based on the real-time information output signal.

50. The computer-readable medium according to claim 47, wherein said instructions which cause the processor to generate initial conditions comprise instructions which when executed by a processor cause the processor to:

filter a second plurality of M-channel training signals, subsequent to said deciding and based on a trained plurality of coefficient values of the converged source separation filter structure, to obtain a filtered training signal; and

train a second plurality of coefficient values of a second source separation filter structure, based on the filtered training signal, to obtain said initial conditions.

51. The computer-readable medium according to claim 50, wherein said medium comprises instructions which when executed by a processor cause the processor to update the trained second plurality of coefficient values based on information from the real-time information output signal.

52. The computer-readable medium according to claim 35, wherein said instructions which when executed by a processor cause the processor to decide comprise instructions which when executed by a processor cause the processor to decide whether the converged source separation filter structure sufficiently concentrates a directional component of each of the plurality of M-channel training signals.

53. An apparatus for signal processing, said apparatus comprising:

an array of M microphones, where M is an integer greater than one; and

means for performing a source separation filtering operation according to a trained plurality of coefficient values,

wherein said means for performing a source separation filtering operation is configured to receive an M-channel signal that is based on signals produced by the array of M microphones and to filter the M-channel signal in real time to obtain a real-time information output signal, and

wherein the trained plurality of coefficient values is based on a plurality of M-channel training signals, and

wherein one of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a first spatial configuration, and

wherein another of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source while the microphones and sources are arranged in a second spatial configuration different than the first spatial configuration.

54. The apparatus for signal processing according to claim 53, wherein said apparatus comprises a mobile user terminal that includes said array and said means for performing a source separation filtering operation.

55. The apparatus for signal processing according to claim 53, wherein said apparatus comprises a wireless headset that includes said array and said means for performing a source separation filtering operation.

56. The apparatus for signal processing according to claim 53, wherein the M microphones of the array are arranged relative to one another in a third spatial configuration, and

wherein, within the first spatial configuration, the M microphones are arranged relative to one another in the third spatial configuration.

57. The apparatus for signal processing according to claim 53, wherein, within the first spatial configuration, the array is oriented in a first direction relative to the at least one information source, and

wherein, within the second spatial configuration, the array is oriented in a second direction relative to the at least one information source, and

wherein the second direction is different than the first direction.

58. The apparatus for signal processing according to claim 53, wherein the trained plurality of coefficient values is calculated, based on a nonlinear bounded function, from a plurality of coefficient values.

59. The apparatus for signal processing according to claim 53, wherein said means for performing a source separation filtering operation is configured to filter the M-channel signal by reassigning a frequency bin of one among (A) an information output channel and (B) an interference output channel to the other among the two channels.

60. The apparatus for signal processing according to claim 53, said apparatus comprising means for adaptively filtering arranged to filter a signal that is based on the real-time information output signal,

wherein said means for adaptively filtering is initialized according to initial conditions that are based on a trained plurality of coefficient values of the converged source separation filter structure, said initial conditions including at least one among (A) an initial plurality of tap weights of the adaptive filter and (B) an initial history of the adaptive filter.

61. The apparatus for signal processing according to claim 60, wherein said means for adaptively filtering is configured to perform a scaling operation, based on a characteristic of the real-time information output signal, on the signal that is based on the real-time information output signal.

62. The apparatus for signal processing according to claim 60, wherein said means for adaptively filtering is configured to produce an interference reference signal, and

wherein said apparatus includes means for reducing noise configured to perform a noise reduction operation, based on the interference reference signal, on a signal that is based on the real-time information output signal.

63. The apparatus for signal processing according to claim 60, wherein said initial conditions are based on a filtered training signal, and

wherein said filtered training signal is based on a second plurality of M-channel training signals as filtered using a trained plurality of coefficient values of the source separation filter structure.

64. The apparatus for signal processing according to claim 63, wherein said means for adaptively filtering is configured to adapt the trained second plurality of coefficient values based on information from the real-time information output signal.

65. The apparatus for signal processing according to claim 53, wherein said means for performing a source separation filtering operation is configured to concentrate a directional component of the M-channel signal.

66. The apparatus for signal processing according to claim 53, said apparatus comprising means for echo cancellation configured to perform an echo cancellation operation on at least one among (A) the M-channel signal and (B) a signal that is based on the real-time information output signal.

67. A method of signal processing, said method comprising:

based on a plurality of M-channel training signals, training a plurality of coefficient values of a source separation filter structure to obtain a converged source separation filter structure, where M is an integer greater than one; and

deciding whether the converged source separation filter structure sufficiently separates each of the plurality of M-channel training signals into at least an information output signal and an interference output signal,

wherein each of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source, and

wherein at least two of the plurality of M-channel training signals differ with respect to at least one of (A) a spatial feature of the at least one information source, (B) a spatial feature of the at least one interference source, (C) a spectral feature of the at least one information source, and (D) a spectral feature of the at least one interference source, and wherein said training a plurality of coefficient values of a source separation filter structure includes updating the plurality of coefficient values according to at least one among an independent vector analysis algorithm and a constrained independent vector analysis algorithm.

68. The method of signal processing according to claim 67, wherein said method comprises, based on a trained plurality of coefficient values of the converged source separation filter structure, filtering an M-channel signal in real time to obtain a real-time information output signal.

69. The method of signal processing according to claim 68, said method comprising:

based on a trained plurality of coefficient values of the converged source separation filter structure, generating initial conditions for an adaptive filter;

initializing the adaptive filter according to the initial conditions; and

subsequent to said initializing, using the adaptive filter to filter a signal that is based on the real-time information output signal,

wherein said initial conditions include at least one among (A) an initial plurality of tap weights of the adaptive filter and (B) an initial history of the adaptive filter.

70. The method of signal processing according to claim 68, wherein said deciding comprises deciding whether the converged source separation filter structure sufficiently concentrates a directional component of each of the plurality of M-channel training signals.

71. An apparatus for signal processing, said apparatus comprising:

an array of M microphones, where M is an integer greater than one; and

a source separation filter structure having a trained plurality of coefficient values,

wherein said source separation filter structure is configured to receive an M-channel signal that is based on signals produced by the array of M microphones and to filter the M-channel signal in real time to obtain a real-time information output signal, and

wherein the trained plurality of coefficient values is based on a plurality of M-channel training signals, and

wherein each of the plurality of M-channel training signals is based on signals produced by M microphones in response to at least one information source and at least one interference source, and

wherein at least two of the plurality of M-channel training signals differ with respect to at least one of (A) a spatial feature of the at least one information source, (B) a spatial feature of the at least one interference source, (C) a spectral feature of the at least one information source, and (D) a spectral feature of the at least one interference source, and

wherein the trained plurality of coefficient values is based on updating a plurality of coefficient values according to at least one among an independent vector analysis algorithm and a constrained independent vector analysis algorithm.