Simple noise suppression model

• US 7,379,866 B2
• Filed: 03/11/2004
• Issued: 05/27/2008
• Est. Priority Date: 03/15/2003
• Status: Active Grant

• Current Assignee: Nytell Software LLC (Intellectual Ventures LLC)
• Original Assignee: Mindspeed Technologies Inc. (MACOM Technology Solutions Holdings, Inc.)
• Inventors: Gao, Yang
• Primary Examiner(s): CHAWAN, VIJAY B
• Application Number:
  US10/799,505
• Publication Number:
  US 20050065792A1
• Time in Patent Office: 1,538 Days
• Field of Search: 704226-228, 704/233, 704/220, 704/240, 704/243, 704/224, 704/225
• US Class Current: 704/220
• CPC Class Codes: G10L 19/005 Correction of errors induced by the transmission channel, if related to the coding algorithm
• CPC Class Codes: G10L 19/087 using mixed excitation models, e.g. MELP, MBE, split band LPC or HVXC
• CPC Class Codes: G10L 19/09 Long term prediction, i.e. removing periodical redundancies, e.g. by using adaptive codebook or pitch predictor
• CPC Class Codes: G10L 19/12 the excitation function being a code excitation, e.g. in code excited linear prediction [CELP] vocoders
• CPC Class Codes: G10L 19/20 using sound class specific coding, hybrid encoders or object based coding
• CPC Class Codes: G10L 19/265 Pre-filtering, e.g. high frequency emphasis prior to encoding
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 21/0232 Processing in the frequency domain
• CPC Class Codes: G10L 21/038 using band spreading techniques
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals

Abstract

An approach for efficiently reducing background noise from speech signal in real-time applications is presented. A noisy input speech signal is processed through an inverse filter when the spectrum tilt of the input signal is not that of a pure background noise model the noisy input signal is also filtered in order to reduce the spectrum valley areas of the noisy input signal when the background noise is present.

Claims

1. A method for suppressing background noise from a speech signal, said method comprising:

obtaining an input speech signal;

performing linear predictive coding (LPC) analysis on said input speech signal to obtain a z-domain representation of said input speech signal;

computing a spectrum tilt and a noise-to-signal ratio (NSR) of said z-domain representation of said input speech signal;

obtaining a spectrum tilt of a background noise model;

applying a gain to reduce energy of said input speech signal when said NSR is high;

reducing a spectral valley energy of said input speech signal when said spectrum tilt of said input speech signal is equivalent to said spectrum tilt of said background noise model; and

applying an inverse filter to said input speech signal when said spectrum tilt of said input speech signal is not equivalent to said spectrum tilt of said background noise model, wherein said inverse filter is an inverse of a z-domain representation of said background noise model.

2. The method of claim 1, wherein said input speech signal comprises a plurality of sub-frames processed in sequence.

3. The method of claim 1, wherein said gain is adaptively based on characteristics of said input speech.

4. The method of claim 1, wherein said background noise model is a first order model.

5. The method of claim 1, wherein applying said gain, reducing said spectral valley energy and applying said inverse filter are performed using g.[1/Fn(z/a)].Fs(z/b)/Fs(z/c), wherein parameters a (0<

=a<

1), b (0<

b<

1), and c (0<

c<

1) are adaptive coefficients, and parameter g is an adaptive gain.

6. The method of claim 5, wherein said parameters a, b, c, and g are controlled by said NSR.

7. A computer program product comprising:

a computer usable medium having computer readable program code embodied therein for suppressing background noise from a speech signal;

said computer readable program code configured to cause a computer to;

obtain an input speech signal;

perform linear predictive coding (LPC) analysis on said input speech signal to obtain a z-domain representation of said input speech signal;

compute a spectrum tilt and a noise-to-signal ratio (NSR) of said z-domain representation of said input signal;

obtain a spectrum tilt of a background noise model;

apply a gain to reduce energy of said input speech signal when said NSR is high;

reduce a spectral valley energy of said input speech signal when said spectrum tilt of said input speech signal is equivalent to said spectrum tilt of said background noise model; and

apply an inverse filter to said input speech signal when said spectrum tilt of said input speech signal is not equivalent to said spectrum tilt of said background noise model, wherein said inverse filter is an inverse of a z-domain representation of said background noise model.

8. The computer program product of claim 7, wherein said input speech signal comprises a plurality of sub-frames processed in sequence.

9. The computer program product of claim 7, wherein said gain is adaptively based on characteristics of said input speech.

10. The computer program product of claim 7, wherein said background noise model is a first order model.

11. The computer program product of claim 7, wherein said computer readable program code to apply said gain, reduce said spectral valley energy and apply said inverse filter are performed using g.[1/Fn(z/a)].Fs(z/b)/Fs(z/c), wherein parameters a (0<

=a<

1), b (0<

b<

1), and c (0<

c<

1) are adaptive coefficients, and parameter g is an adaptive gain.

12. The computer program product of claim 11, wherein said parameters a, b, c, and g are controlled by said NSR.

13. An apparatus for suppressing background noise from a speech signal, said apparatus comprising:

an object for receiving an input speech signal;

an object for performing linear predictive coding (LPC) analysis on said input speech signal to obtain a z-domain representation of said input speech signal;

an object for computing a spectrum tilt and a noise-to-signal ratio (NSR) of said z-domain representation of said input signal;

an object for obtaining a spectrum tilt of a background noise model;

an object for applying a gain to reduce energy of said input speech signal when said NSR is high;

an object for reducing a spectral valley energy of said input speech signal when said spectrum tilt of said input speech signal is equivalent to said spectrum tilt of said background noise model; and

an object for applying an inverse filter to said input speech signal when said spectrum tilt of said input speech signal is not equivalent to said spectrum tilt of said background noise model, wherein said inverse filter is an inverse of a z-domain representation of said background noise model.

14. The apparatus of claim 13, wherein said input speech signal comprises a plurality of sub-frames processed in sequence.

15. The apparatus of claim 13, wherein said gain is adaptive based on characteristics of said input speech.

16. The apparatus of claim 13, wherein said background noise model is a first order model.

17. The apparatus of claim 13, wherein said objects for applying said gain, reducing said spectral valley energy and applying said inverse filter are performed using g.[1/Fn(z/a)].Fs(z/b)/Fs(z/c), wherein parameters a (0<

=a<

1), (0<

b<

1), and c (0<

c<

1) are adaptive coefficients, and parameter g is an adaptive gain.

18. The apparatus of claim 17, wherein said parameters a, b, c, and g are controlled by said NSR.