Methods for generating comfort noise during discontinuous transmission

• US 6,606,593 B1
• Filed: 08/10/1999
• Issued: 08/12/2003
• Est. Priority Date: 11/15/1996
• Status: Expired due to Term

• Current Assignee: Nokia Technologies Oy (Nokia Corporation)
• Original Assignee: Nokia Mobile Phones UK Limited (Nokia Corporation)
• Inventors: Ruoppila, Vesa, Kapanen, Pekka, Jarvinen, Kari, Rotola-Pukkila, Jani
• Primary Examiner(s): ABEBE, DANIEL DEMELASH
• Application Number:
  US09/371,332
• Time in Patent Office: 1,463 Days
• Field of Search: 704/223, 704/226, 704/220, 704/230, 704/233, 704/264, 704/500, 704/225, 704/258, 704/219, 455/501
• US Class Current: 704/223
• CPC Class Codes: G10L 19/012 Comfort noise or silence coding

Abstract

An improved method for generating comfort noise (CN) in a mobile terminal operating in a discontinuous transmission (DTX) mode. In one embodiment the invention provides an improved method for comfort noise generation, in which a random excitation is modified by a spectral control filter so that the frequency content of comfort noise and background noise become similar. In another embodiment the transmitter identifies speech coding parameters that are not representative of the actual background noise, and replaces the identified parameters with parameters having a median value. In this manner the non-representative parameters do not skew the result of an averaging operation.

Claims

1. A method for producing comfort noise (CN) in a digital mobile terminal that uses a discontinuous transmission, comprising the steps of:

in response to a speech pause, calculating random excitation spectral control (RESC) parameters; and

transmitting the RESC parameters to a receiver together with predetermined ones of CN parameters.

2. A method as in claim 1, wherein the step of calculating RESC parameters includes a step of analyzing a residual signal in a speech coder.

3. A method as in claim 2, wherein the speech coder implements a LPC analysis technique, and wherein the step of analyzing is of lower degree than the LPC analysis technique.

4. A method as in claim 2, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the step of analyzing is performed by first or second order LPC analysis.

5. A method as in claim 1, wherein the step of calculating RESC parameters includes steps of analyzing a residual signal in a speech coder to produce spectral parameters, and averaging the spectral parameters over a plurality of frames to provide RESC parameters.

6. A method as in claim 3, wherein the plurality of frames is equal to about 10 or greater.

7. A method as in claim 1, wherein the step of calculating RESC parameters includes steps of applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

8. A method as in claim 7, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . , R.

9. A method as in claim 7, and further comprising a step of determining an excitation gain from the spectrally flattened residual signal.

10. A method as in claim 1, wherein the step of shaping includes steps of:

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

11. A method as in claim 1, wherein the step of calculating RESC parameters include a step of:

applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein the step of shaping includes steps of,

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein the RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

12. A method as in claim 1, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the predetermined one of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

13. Apparatus for generating comfort noise (CN) in a system that uses a discontinuous transmission to a network, comprising:

means in said digital mobile terminal that is responsive to a speech pause for calculating random excitation spectral control (RESC) parameters and for transmitting the RESC parameters together with predetermined ones of CN parameters to a receiver in said network.

14. Apparatus as in claim 13, wherein said calculating means analyses a residual signal in a speech coder.

15. Apparatus as in claim 14, wherein the speech coder implements a LPC analysis technique, and wherein the analysis is of lower degree than the LPC analysis technique.

16. Apparatus as in claim 14, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the analysis is performed by first or second order LPC analysis.

17. Apparatus as in claim 13, wherein said calculating means analyses a residual signal in a speech coder to produce spectral parameters, and further comprising means for averaging the spectral parameters over a plurality of frames to provide RESC parameters.

18. Apparatus as in claim 17, wherein the plurality of frames is equal to about 10 or greater.

19. Apparatus as in claim 13, wherein said calculating means applies an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

20. Apparatus as in claim 19, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1. . . , R.

21. Apparatus as in claim 19, and further comprising means for determining an excitation gain from the spectrally flattened residual signal.

22. Apparatus as in claim 13, wherein said shaping means is comprised of:

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

23. Apparatus as in claim 13, wherein said calculating means is comprised of:

means for applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter HRESC(Z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein said shaping means is comprised of,

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

24. Apparatus as in claim 23, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the predetermined ones of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

25. A method for producing comfort noise (CN) in a digital mobile terminal receiver that uses a discontinuous transmission, comprising the steps of:

receiving random excitation spectral (RESC) parameters;

and

shaping the spectral content of an excitation using the received RESC parameters prior to applying the excitation to a synthesis filter.

26. A method as in claim 25, wherein the step of calculating RESC parameters includes a step of analyzing a residual signal in a speech coder.

27. A method as in claim 26, wherein the speech coder implements a LPC analysis technique, and wherein the step of analyzing is of lower degree than the LPC analysis technique.

28. A method as in claim 26, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the step of analyzing is performed by first or second order LPC analysis.

29. A method as in claim 25, wherein the step of calculating RESC parameters includes steps of analyzing a residual signal in a speech coder to produce spectral parameters, and averaging the spectral parameters over a plurality of frames to provide RESC parameters.

30. A method as in claim 29, wherein the plurality of frames is equal to about 10 or greater.

31. A method as in claim 25, wherein the step of calculating RESC parameters includes steps of applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

32. A method as in claim 31, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R.

33. A method as in claim 31, and further comprising a step of determining an excitation gain from the spectrally flattened residual signal.

34. A method as in claim 25, wherein the step of shaping includes steps of:

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

35. A method as in claims 25, wherein the step of calculating RESC parameters include a step of:

applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein the step of shaping includes steps of,

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein the RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

36. A method as in claim 35, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the predetermined one of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

37. Mobile terminal apparatus for generating comfort noise (CN) in a system that uses a discontinuous transmission to a network, comprising:

means in said mobile terminal for shaping the spectral content of an excitation using received excitation spectral control (RESC) parameters prior to applying the excitation to a synthesis filter.

38. Apparatus as in claim 37, wherein said calculating means analyses a residual signal in a speech coder.

39. Apparatus as in claim 38, wherein the speech coder implements a LPC analysis technique, and wherein the analysis is of lower degree than the LPC analysis technique.

40. Apparatus as in claim 38, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the analysis is performed by first or second order LPC analysis.

41. Apparatus as in claim 37, wherein said calculating means analyses a residual signal in a speech coder to produce spectral parameters, and further comprising means for averaging the spectral parameters over a plurality of frames to provide RESC parameters.

42. Apparatus as in claim 41, wherein the plurality of frames is equal to about 10 or greater.

43. Apparatus as in claim 37, wherein said calculating means applies an LPC residual signal from a speech coder inverse filter to a RESC inverse filter Hhd HESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

44. Apparatus as in claim 43, wherein the RESC inverse filter H_RESC(z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R.

45. Apparatus as in claim 43, and further comprising means for determining an excitation gain from the spectrally flattened residual signal.

46. Apparatus as in claim 37, wherein said shaping means is comprised of:

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

47. Apparatus as in claim 37, wherein said calculating means is comprised of:

means for applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein said shaping means is comprised of,

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

48. Apparatus as in claim 47, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the predetermined ones of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

49. A method for producing comfort noise (CN) in a network element that uses a discontinuous transmission, comprising the steps of:

receiving excitation spectral control (RESC) parameters; and

shaping the spectral content of an excitation using the received RESC parameters prior to applying the excitation to a synthesis filter.

50. A method as in claim 49, wherein the step of calculating RESC parameters includes a step of analyzing a residual signal in a speech coder.

51. A method as in claim 50, wherein the speech coder implements a LPC analysis technique, and wherein the step of analyzing is of lower degree than the LPC analysis technique.

52. A method as in claim 50, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the step of analyzing is performed by first or second order LPC analysis.

53. A method as in claim 49, wherein the step of calculating RESC parameters includes steps of analyzing a residual signal in a speech coder to produce spectral parameters, and averaging the spectral parameters over a plurality of frames to provide RESC parameters.

54. A method as in claim 53, wherein the plurality of frames is equal to about 10 or greater.

55. A method as in claim 49, wherein the step of calculating RESC parameters includes steps of applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

56. A method as in claim 55, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>\text{\hspace{1em}<br><br>}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R.

57. A method as in claim 55, and further comprising a step of determining an excitation gain from the spectrally flattened residual signal.

58. A method as in claim 49, wherein the step of shaping includes steps of:

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

59. A method as in claim 49, wherein the step of calculating RESC parameters include a step of:

applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein the step of shaping includes steps of,

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein the RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

60. A method as in claim 59, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the predetermined one of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

61. Apparatus for generating comfort noise (CN) in a system having a digital mobile terminal that uses a discontinuous transmission to a network, comprising:

means in said network for shaping the spectral content of an excitation using received excitation spectral control (RESC) parameters prior to applying the excitation to a synthesis filter.

62. Apparatus as in claim 61, wherein said calculating means analyses a residual signal in a speech coder.

64. Apparatus as in claim 62, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the analysis is performed by first or second order LPC analysis.

65. Apparatus as in claim 61, wherein said calculating means analyses a residual signal in a speech coder to produce spectral parameters, and further comprising means for averaging the spectral parameters over a plurality of frames to provide RESC parameters.

66. Apparatus as in claim 65, wherein the plurality of frames is equal to about 10 or greater.

67. Apparatus as in claim 61, wherein said calculating means applies an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

68. Apparatus as in claim 67, wherein the RESC inverse filter H_RESC(z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R.

69. Apparatus as in claim 67, and further comprising means for determining an excitation gain from the spectrally flattened residual signal.

70. Apparatus as in claim 61, wherein said shaping means is comprised of:

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

71. Apparatus as in claim 61, wherein said calculating means is comprised of:

means for applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter H_RESC(Z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein said shaping means is comprised of,

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

72. Apparatus as in claim 71, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the predetermined ones of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

63. Apparatus as in claim 63, wherein the speech coder implements a LPC analysis technique, and wherein the analysis is of lower degree than the LPC analysis technique.

73. A method for producing comfort noise (CN) in a digital network element that uses a discontinuous transmission, comprising the steps of:

in response to a speech pause, calculating random excitation spectral control (RESC) parameters; and

transmitting the RESC parameters to a receiver together with predetermined ones of CN parameters.

74. A method as in claim 73, wherein the step of calculating RESC parameters includes a step of analyzing a residual signal in a speech coder.

75. A method as in claim 74, wherein the speech coder implements a LPC analysis technique, and wherein the step of analyzing is of lower degree than the LPC analysis technique.

76. A method as in claim 74, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the step of analyzing is performed by first or second order LPC analysis.

77. A method as in claim 73, wherein the step of calculating RESC parameters includes steps of analyzing a residual signal in a speech coder to produce spectral parameters, and averaging the spectral parameters over a plurality of frames to provide RESC parameters.

78. A method as in claim 77, wherein the plurality of frames is equal to about 10 or greater.

79. A method as in claim 73, wherein the step of calculating RESC parameters includes steps of applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(Z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

80. A method as in claim 79, wherein the RESC inverse filter H_RESC(z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R.

81. A method as in claim 79, and further comprising a step of determining an excitation gain from the spectrally flattened residual signal.

82. A method as in claim 73, wherein the step of shaping includes steps of:

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

83. A method as in claim 73, wherein the step of calculating RESC parameters include a step of:

applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter H_RESC(z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein the step of shaping includes steps of,

forming an excitation by generating a white noise excitation sequence;

scaling the generated white noise sequence to produce a scaled noise sequence; and

processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein the RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

84. A method as in claim 83, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

85. Apparatus for generating comfort noise (CN) in a system having a network element that uses a discontinuous transmission, comprising:

means in said network element that is responsive to a speech pause for calculating random excitation spectral control (RESC) parameters and for transmitting the RESC parameters together with predetermined ones of CN parameters to a receiver in said network.

86. Apparatus as in claim 85, wherein said calculating means analyses a residual signal in a speech coder.

87. Apparatus as in claim 86, wherein the speech coder implements a LPC analysis technique, and wherein the analysis is of lower degree than the LPC analysis technique.

88. Apparatus as in claim 86, wherein the speech coder implements a LPC analysis technique of order greater than two, and wherein the analysis is performed by first or second order LPC analysis.

89. Apparatus as in claim 85, wherein said calculating means analyses a residual signal in a speech coder to produce spectral parameters, and further comprising means for averaging the spectral parameters over a plurality of frames to provide RESC parameters.

90. Apparatus as in claim 89, wherein the plurality of frames is equal to about 10 or greater.

91. Apparatus as in claim 85, wherein said calculating means applies an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal.

92. Apparatus as in claim 91, wherein the RESC inverse filter H_RESC(z) has the form of an all-zero filter described by:

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R.

93. Apparatus as in claim 91, and further comprising means for determining an excitation gain from the spectrally flattened residual signal.

94. Apparatus as in claim 85, wherein said shaping means is comprised of:

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content.

95. Apparatus as in claim 85, wherein said calculating means is comprised of:

means for applying an LPC residual signal from a speech coder inverse filter to a RESC inverse filter H_RESC(z) to produce a spectrally controlled residual signal which generally has a flatter spectrum than the LPC residual signal, wherein the RESC inverse filter H_RESC(z) has the form of an all-zero filter described by;

$H_{\mathrm{RESC}}<br><br>\left(z\right)=1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i},$

where b(i) represents filter coefficients, with i=1, . . . ,R; and

wherein said shaping means is comprised of,

means for forming an excitation by generating a white noise excitation sequence;

means for scaling the generated white noise sequence to produce a scaled noise sequence; and

means for processing the scaled noise sequence in a RESC filter to produce an excitation having a desired spectral content;

wherein RESC filter performs an inverse operation to the RESC inverse filter and is of the form;

$1/H_{\mathrm{RESC}}<br><br>\left(z\right)=\frac{1}{1-\underset{i=1}{\overset{R}{\sum <br><br>}}<br><br>b<br><br>\left(i\right)<br><br>z^{-i}}.$

96. Apparatus as in claim 95, wherein RESC parameters r_mean(i), i=1, . . . ,R define the filter coefficients b(i), i=1, . . . , R, are transmitted as part of the predetermined ones of the CN parameters, and are used in the RESC filter to spectrally weight the excitation for the synthesis filter.

97. A method for generating comfort noise (CN) in an element of a mobile communications network that uses a discontinuous transmission, comprising the steps of:

in response to a speech pause, buffering a set of speech coding parameters;

within an averaging period, replacing speech coding parameters of the set that are not representative of background noise with speech coding parameters that are representative of the background noise; and

averaging the set of speech coding parameters.

98. A method as in claim 97, wherein the step of replacing includes the steps of:

measuring distances of the speech coding parameters from one another between individual frames within the averaging period;

identifying those speech coding parameters which have the largest distances to the other parameters within the averaging period; and

if the distances exceed a predetermined threshold, replacing an identified speech coding parameter with a speech coding parameter which has a smallest measured distance to the other speech coding parameters within the averaging period.

99. A method as in claim 97, wherein the step of replacing includes the steps of:

measuring distances of the speech coding parameters from one another between individual frames within the averaging period;

identifying those speech coding parameters which have the largest distances to the other parameters within the averaging period; and

if the distances exceed a predetermined threshold, replacing an identified speech coding parameter with a speech coding parameter having a median value.

100. A method as in claim 97, wherein the step of averaging includes a step of computing an average excitation gain g_mean and average short term spectral coefficients f_mean(i).

101. A method as in claim 97, wherein the step of replacing includes steps of:

forming a set of buffered excitation gain values over the averaging period;

ordering the set of buffered excitation gain values; and

performing a median replacement operation in which those L excitation gain values differing the most from the median value, where the difference exceeds a predetermined threshold value, are replaced by the median value of the set.

102. A method as in claim 101, wherein a length N of the averaging period is an odd number, and wherein the median of the ordered set is the ((N+1)/2)th element of the set.

103. A method as in claim 97, and further comprising a step of:

forming a set of buffered Line Spectral Pair (LSP) coefficients f(k), k=1, . . . ,M over the averaging period; and

determining a spectral distance of the LSP coefficients f_i(k) of the ith frame in the averaging period, to the LSP coefficients f_j(k) of the jth frame in the averaging period.

104. A method as in claim 103, where the step of determining the spectral distance is accomplished in accordance with the expression $\Delta$



 



Rij=∑

k=1M

(fi

(k)-fj

(k))2,

where M is the degree of the LPC model, and f_i(k) is the kth LSP parameter of the ith frame in the averaging period.

105. A method as in claim 103, and further comprising a step of determining the spectral distance Δ

S_i of the LSP coefficients f_i(k) of frame i to the LSP coefficients of all the other frames j=1, . . . ,N, i≠

j, within the averaging period of length N.

106. A method as in claim 105, wherein the step of determining the spectral distance is accomplished by determining the sum of the spectral distances Δ

R_ij in accordance with $\mathrm{\Delta <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>S_i=\underset{j=1,j\ne <br><br>i}{\overset{N}{\sum <br><br>}}<br><br>\mathrm{\Delta <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>R_{\mathrm{ij}},$

for all i=1, . . . ,N.

107. A method as in claim 105, and further comprising steps of:

after the spectral distances Δ

S_i have been found for each of the LSP vectors f_i within the averaging period, ordering the spectral distances according to their values;

considering a vector f_i with the smallest distance Δ

S_i within the averaging period i=1, 2,. . . ,N to be a median vector f_med of the averaging period having a distance denoted as Δ

S_med; and

performing a median replacement of P (0≦

P≦

N-1) LSP vectors f_i with the median vector f_med.

108. A method as in claim 107, wherein the steps of identifying and replacing are performed independently for excitation gain values g and Line Spectral Pair (LSP) vectors f_i.

109. A method as in claim 98, wherein the steps of identifying and replacing are combined together for excitation gain values g and Line Spectral Pair (LSP) vectors f_i.

110. A method as in claim 109, comprising steps of:

in response to determining that the speech coding parameters in an individual frame are to be replaced by median values of the parameters, replacing both the excitation gain value g and the LSP vector f_i of that frame by the respective parameters of the frame containing the median parameters.

111. A method as in claim 110, and comprising initial steps of:

determining a distance Δ

T_ij between the parameters of the ith frame and the jth frame of the averaging period in accordance with the expression $\mathrm{\Delta <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>T_{\mathrm{ij}}=\underset{k=1}{\overset{M}{\sum <br><br>}}<br><br>{\left(f_i<br><br>\left(k\right)-f_j<br><br>\left(k\right)\right)}^2+{w<br><br>\left(g_i-g_j\right)}^2,$

where M is the degree of the LPC model, f_i(k) is the kth LSP parameter of the ith frame of the averaging period, and g_i is the excitation gain parameter of the ith frame.

112. A method as in claim 111, and further comprising a step of:

determining a distance Δ

S_i of the speech coding parameters of frame i, for all i=1, . . . ,N, to the speech coding parameters of all the other frames j=1, . . . ,N, i≠

j within the averaging period of length N, in accordance with $\mathrm{\Delta <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>S_i=\underset{j=1,j\ne <br><br>i}{\overset{N}{\sum <br><br>}}<br><br>\mathrm{\Delta <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>T_{\mathrm{ij}},$

for all i=1, . . . ,N.

113. A method as in claim 112, wherein after the distances Δ

S_i have been determined for each of the frames within the averaging period, further comprising steps of;

ordering the distances according to their values; and

considering a frame with the smallest distance Δ

S_i within the averaging period i=1,2, . . . ,N as a median frame, having distance Δ

S_med, of the averaging period, the median frame having speech coder parameters g_med and f_med.

114. A method as in claim 113, and comprising a step of performing median replacement on the speech coding parameter frames within the averaging period i=1,2, . . . ,N wherein parameters g_i and f_i of L (0≦

L≦

N-1) frames are replaced by the parameters g_med and f_med of the median frame.

115. A method as in claim 113, wherein differences between each individual distance and the median distance are determined by dividing an individual distance by the median distance in accordance with Δ

S_i/Δ

S_med.

116. A method as in claim 107, wherein differences between each individual distance and the median distance are determined by dividing an individual distance by the median distance in accordance with Δ

S_i/Δ

S_med.

117. Apparatus for generating comfort noise (CN) in an element of a mobile communication network that uses a discontinuous transmission to a network, comprising:

data processing means in network element that is responsive to a speech pause for buffering a set of speech coding parameters and, within an averaging period, for replacing speech coding parameters of the set that are not representative of background noise with speech coding parameters that are representative of the background noise, said data processing means averaging the set of speech coding parameters and transmitting the averaged set of speech coding parameters to the mobile terminal.

118. Apparatus as in claim 117, wherein said data processor replaces speech coding parameters of the set by ordering the set and measuring distances of the speech coding parameters from one another between individual frames within the averaging period, by identifying those speech coding parameters which have the largest distances to the other parameters within the averaging period;

and, if the distances exceed a predetermined threshold, by replacing the identified speech coding parameters with a speech coding parameter which has a smallest measured distance to the other speech coding parameters within the averaging period.

119. Apparatus as in claim 117, wherein said data processor replaces speech coding parameters of the set by ordering the set and measuring distances of the speech coding parameters from one another between individual frames within the averaging period;

by identifying those speech coding parameters which have the largest distances to the other parameters within the averaging period; and

, if the distances exceed a predetermined threshold, by replacing an identified speech coding parameter with a speech coding parameter having a median value.

120. Apparatus as in claim 117, wherein said data processing means identifies and replaces speech coding parameters independently for excitation gain values g and Line Spectral Pair (LSP) vector f_i.

121. Apparatus as in claim 117, wherein said data processing means identifies and replaces speech coding parameters together for excitation gain values g and Line Spectral Pair (LSP) vector f_i.