Noisy acoustic signal enhancement

• US 6,910,011 B1
• Filed: 08/16/1999
• Issued: 06/21/2005
• Est. Priority Date: 08/16/1999
• Status: Expired due to Term

• Current Assignee: Malikie Innovations Limited (Key Patent Innovations Limited)
• Original Assignee: Haman Becker Automotive Systems - Wavemakers Incorporated
• Inventors: Zakarauskas, Pierre
• Primary Examiner(s): Dorvil, Richemond
• Assistant Examiner(s): ARMSTRONG, ANGELA A
• Application Number:
  US09/375,309
• Time in Patent Office: 2,136 Days
• Field of Search: 704/201, 704/205, 704/226, 704/233, 381/94.1, 381/94.2
• US Class Current: 704/233
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 21/0232 Processing in the frequency domain
• CPC Class Codes: G10L 21/0264 characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques
• CPC Class Codes: H04R 2225/43 Signal processing in hearing aids to enhance the speech intelligibility

Abstract

A system and method for enhancing acoustic signal buried in noise. The invention matches the acoustic input to a signal model and produces a corresponding output that has very low noise. Input data are digitized, transformed to a time-frequency representation, background noise is estimated, and transient sounds are isolated. A signal detector is applied to the transient. Long transients without signal content, and the background between the transients, are included in the noise estimate. If at least some part of the transient contains signal of interest, the spectrum of the signal is compared to the signal model after rescaling, and the signal'"'"'s parameters are fitted to the data. If an existing template is found that resembles the input pattern, the template is averaged with the pattern in such a way that the resulting template is the average of all the spectra that matched that template in the past.

Claims

1. A method for enhancing acoustic signal buried in noise within a digitized acoustic input signal, including:

(a) transforming the digitized acoustic input signal to a time-frequency representation;

(b) detecting transient duration in conjunction with estimating a background noise level in the time-frequency representation;

(c) for each interval of the time-frequency representation containing significant signal levels, performing a signal-to-noise ratio weighted comparison of the time-frequency representation of such interval against a plurality of time-frequency spectrogram templates in a signal model and determining a matching spectrogram template in the signal model that best matches the time-frequency representation of such interval; and

(d) replacing the digitized acoustic input signal with a low-noise output signal comprising a signal-to-noise ratio weighted mix of the time-frequency representation and the matching spectrogram template.

2. The method of claim 1, where the low-noise output signal comprises a low-noise spectrogram.

3. The method of claim 2, further comprising synthesizing a time series output from the low-noise spectrogram.

4. The method of claim 1, where the signal-to-noise ratio weighted mix, C, is determined according to:

C=w*P+(wmax−

w)*T,

where ‘

w’

comprises a signal-to-noise ratio proportional weight, ‘

wmax’

comprises a pre-selected maximum weight, ‘

P’

comprises the time-frequency representation, and ‘

T’

comprises the matching spectrogram template.

5. A system for enhancing acoustic signal buried in noise within a digitized acoustic input signal, including:

(a) means for transforming the digitized acoustic input signal to a time-frequency representation;

(b) means for detecting transient duration in conjunction with estimating a background noise level in the time-frequency representation;

(c) for each interval of the time-frequency representation containing significant signal levels, means for performing a signal-to-noise ratio weighted comparison of the time-frequency representation of such interval against a plurality of time-frequency spectrogram templates in a signal model and determining a matching spectrogram template in the signal model that best matches the time-frequency representation of such interval; and

(d) means for replacing the digitized acoustic input signal with a low-noise output signal comprising a signal-to-noise ratio weighted mix of the time-frequency representation and the matching spectrogram template.

6. The system of claim 5, where the low-noise output signal comprises a low-noise spectrogram, and further comprising means for synthesizing a time series output as a sum of a harmonic part and a non-harmonic part derived from the low-noise spectrogram.

7. The system of claim 5, where the signal-to-noise ratio weighted mix, C, is determined according to:

C=w*P+(wmax−

w)*T,

where ‘

w’

comprises a signal-to-noise ratio proportional weight, ‘

wmax’

comprises a pre-selected maximum weight, ‘

P’

comprises the time-frequency representation, and ‘

T’

comprises the matching spectrogram template.

8. A computer program, stored on a computer-readable medium, for enhancing acoustic signal buried in noise within a digitized acoustic input signal, the computer program comprising instructions for causing a computer to:

(a) transform the digitized acoustic input signal to a time-frequency representation;

(b) detect transient duration in conjunction with estimating a background noise level in the time-frequency representation;

(c) for each interval of the time-frequency representation containing significant signal levels, perform a signal-to-noise ratio weighted comparison of the time-frequency representation of such interval against a plurality of time-frequency spectrogram templates in a signal model and determine a matching spectrogram template in the signal model that best matches the time-frequency representation of such interval; and

(d) replace the digitized acoustic input signal with a low-noise output signal comprising a signal-to-noise ratio weighted mix of the time-frequency representation and the matching spectrogram template.

9. The computer-readable medium of claim 8, where the low-noise output signal comprises a low-noise spectrogram, and where the instructions further cause the computer to synthesize a time series output from the low-noise spectrogram.

10. The computer-readable medium of claim 8, where the signal-to-noise ratio weighted mix, C, is determined according to:

C=w*P+(wmax−

w)*T,

where ‘

w’

comprises a signal-to-noise ratio proportional weight, ‘

wmax’

comprises a pre-selected maximum weight, ‘

P’

comprises the time-frequency representation, and ‘

T’

comprises the matching spectrogram template.

11. A method for enhancing acoustic signal buried in noise within a digitized acoustic input signal, including:

(a) transforming the digitized acoustic input signal to a time-frequency representation;

(b) detecting transient duration in conjunction with estimating background noise and including long transients without signal content and background noise between transients in such estimating;

determining signal strength in the time-frequency representation;

updating a background noise statistic based on the time-frequency representation when the signal strength is under a pre-selected threshold;

(c) performing a signal-to-noise ratio weighted comparison, when the signal strength is greater than the pre-selected threshold, of the time-frequency representation against a plurality of time-frequency spectrogram templates in a signal model;

(d) determining a matching spectrogram template in the signal model that best matches such representation; and

(e) replacing the digitized acoustic input signal with a low-noise output signal comprising a signal-to-noise ratio weighted mix of the time-frequency representation and the matching spectrogram template.

12. The method of claim 11, where the low-noise output signal comprises a low-noise spectrogram.

13. The method of claim 12, further comprising synthesizing a time series output from the low-noise spectrogram.

14. The method of claim 11, where the signal-to-noise ratio weighted mix, C, is determined according to:

C=w*P+(wmax−

w)*T,

where ‘

w’

comprises a signal-to-noise ratio proportional weight, ‘

wmax’

comprises a pre-selected maximum weight, ‘

P’

comprises the time-frequency representation, and ‘

T’

comprises the matching spectrogram template.

15. A system for enhancing acoustic signal buried in noise within a digitized acoustic input signal, including:

(a) means for transforming the digitized acoustic input signal to a time-frequency representation;

(b) means for detecting transient duration in conjunction with estimating background noise and including long transients without signal content and background noise between transients in such estimating;

(c) means for determining signal strength in the time-frequency representation;

(d) means for updating a background noise statistic based on the time-frequency representation when the signal strength is under a pre-selected threshold;

(e) means for performing a signal-to-noise ratio weighted comparison, when the signal strength is greater than the pre-selected threshold, of the time-frequency representation against a plurality of time-frequency spectrogram templates in a signal model;

(f) means for determining a matching spectrogram template in the signal model that best matches such representation; and

(g) means for replacing the digitized acoustic input signal with a low-noise output signal comprising a signal-to-noise ratio weighted mix of the time-frequency representation and the matching spectrogram template.

16. The system of claim 15, where the low-noise output signal is a low-noise spectrogram, and further comprising means for synthesizing a time series output from the low-noise spectrogram.

17. The system of claim 15, where the signal-to-noise ratio weighted mix, C, is determined according to:

C=w*P+(wmax−

w)*T,

where ‘

w’

comprises a signal-to-noise ratio proportional weight, ‘

wmax’

comprises a pre-selected maximum weight, ‘

P’

comprises the time-frequency representation, and ‘

T’

comprises the matching spectrogram template.

18. A computer program, stored on a computer-readable medium, for enhancing acoustic signal buried in noise within a digitized acoustic input signal, the computer program comprising instructions for causing a computer to:

(a) transform the digitized acoustic input signal to a time-frequency representation;

(b) detect transient duration in conjunction with estimating background noise and including long transients without signal content and background noise between transients in such estimating;

determine signal strength in the time-frequency representation;

update a background noise statistic based on the time-frequency representation, when the signal strength is under a pre-selected threshold;

(c) rescale the time-frequency representation of the estimated background noise;

(d) perform a signal-to-noise ratio weighted comparison, when the signal strength is greater than the pre-selected threshold, of the time-frequency representation against a plurality of time-frequency spectrogram templates in a signal model;

(e) determine a matching spectrogram template in the signal model that best matches such representation; and

(f) replace the digitized acoustic input signal with a low-noise output signal comprising a signal-to-noise ratio weighted mix of the time-frequency representation and the matching spectrogram template.

19. The computer-readable medium of claim 18, where the low-noise output signal comprises a low-noise spectrogram, and where the instructions further cause the computer to synthesize a time series output from the low-noise spectrogram.

20. The computer-readable medium of claim 18, where the signal-to-noise ratio weighted mix, C, is determined according to:

C=x*P+(wmax−

w)*T,

where ‘

w’

comprises a signal-to-noise ratio proportional weight, ‘

wmax’

comprises e pre-selected maximum weight, ‘

P’

comprises the time-frequency representation and ‘

T’

comprises the matching spectrogram template.