IP Library Granted Patent US 8,843,367
Granted Patent B2
US 8,843,367 · App. 13/464,411 · Granted Sep 23, 2014

Adaptive equalization system

Inventors: Phillip Alan Hetherington (Port Moody, CA); Xueman Li (Burnaby, CA)
Assignee: 8758271 Canada Inc.
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Quick Facts
Patent No.
US 8,843,367
App. No.
13/464,411
Granted
Sep 23, 2014
Kind
B2
Abstract

An adaptive equalization system that adjusts the spectral shape of a speech signal based on an intelligibility measurement of the speech signal may improve the intelligibility of the output speech signal. Such an adaptive equalization system may include a speech intelligibility measurement module, a spectral shape adjustment module, and an adaptive equalization module. The speech intelligibility measurement module is configured to calculate a speech intelligibility measurement of a speech signal. The spectral shape adjustment module is configured to generate a weighted long-term speech curve based on a first predetermined long-term average speech curve, a second predetermined long-term average speech curve, and the speech intelligibility measurement. The adaptive equalization module is configured to adapt equalization coefficients for the speech signal based on the weighted long-term speech curve.

Claims (77)

1. An adaptive equalization method, comprising:

calculating a speech intelligibility measurement of a speech signal by a computer processor;

obtaining a first predetermined long-term average speech curve;

obtaining a second predetermined long-term average speech curve;

generating a weighted long-term speech curve by the computer processor based on the first predetermined long-term average speech curve, the second predetermined long-term average speech curve, and the speech intelligibility measurement; and

adapting equalization coefficients for the speech signal by the computer processor based on the weighted long-term speech curve.

2. The method of claim 1 , where the first predetermined long-term average speech curve is a first speech template in quite conditions, and the second predetermined long-term average speech curve is a second speech template in noisy conditions;

where the step of generating the weighted long-term speech curve comprises:

calculating a weight factor from the speech intelligibility measurement; and

averaging the first speech template in quite conditions with the second speech template in noisy conditions based on the weight factor to generate the weighted long-term speech curve.

3. The method of claim 1 , where calculating the speech intelligibility measurement comprises calculating a product of a band importance function and a band audibility function, summed over a plurality of bands of the speech signal.

4. The method of claim 1 , where calculating the speech intelligibility measurement comprises:

calculating a signal power measurement for a frequency band of the speech signal;

estimating a background noise level for the frequency band of the speech signal; and

calculating the speech intelligibility measurement from the signal power measurement, the background noise level, and a band importance value associated with the frequency band of the speech signal.

5. The method of claim 1 , where adapting the equalization coefficients comprises:

applying a prior version of the equalization coefficients to a power spectrum of the speech signal to generate an equalized signal; and

adapting the equalization coefficients to generate an adapted version of the equalization coefficients based on a difference between the equalized signal and the weighted long-term speech curve.

6. The method of claim 5 , further comprising applying the adapted version of the equalization coefficients to the speech signal to transform one or more aspects of the speech signal and produce an output speech signal.

7. The method of claim 1 , where adapting the equalization coefficients comprises:

normalizing the weighted long-term speech curve based on a power measurement of the speech signal to generate a normalized speech curve;

applying a prior version of the equalization coefficients to a power spectrum of the speech signal to generate an equalized signal;

estimating a background noise level of the speech signal;

summing the background noise level and the normalized speech curve to generate a summed signal;

calculating an error signal based on a difference between the summed signal and the equalized signal; and

adapting the equalization coefficients based on the error signal to generate an adapted version of the equalization coefficients.

8. The method of claim 1 , where adapting the equalization coefficients comprises:

calculating a signal-to-noise ratio of the speech signal;

comparing the signal-to-noise ratio to a predetermined upper threshold or a predetermined lower threshold; and

limiting a boosting gain of the equalization coefficients in response to a determination that the signal-to-noise ratio is above the predetermined upper threshold or below the predetermined lower threshold.

9. The method of claim 1 , where adapting the equalization coefficients comprises:

determining whether an adaptation of the equalization coefficients based on the weighted long-term speech curve would increase or decrease the speech intelligibility measurement of the speech signal; and

constraining the adaptation of the equalization coefficients in response to a determination that the adaptation of the equalization coefficients would decrease the speech intelligibility measurement.

10. The method of claim 1 , further comprising generating a set of sub-bands of the speech signal through a subband filter or a Fast Fourier Transform.

11. The method of claim 1 , further comprising generating a set of sub-bands of the speech signal according to a critical, octive, mel, or bark band spacing technique.

12. An adaptive equalization system, comprising:

a computer processor;

a speech intelligibility measurement module executable by the computer processor to calculate a speech intelligibility measurement of a speech signal;

a spectral shape adjustment module executable by the computer processor to generate a weighted long-term speech curve based on a first predetermined long-term average speech curve, a second predetermined long-term average speech curve, and the speech intelligibility measurement; and

an adaptive equalization module executable by the computer processor to adapt equalization coefficients for the speech signal based on the weighted long-term speech curve.

13. The system of claim 12 , where the first predetermined long-term average speech curve is a first speech template in quite conditions, and the second predetermined long-term average speech curve is a second speech template in noisy conditions;

where the spectral shape adjustment module is configured to calculate a weight factor from the speech intelligibility measurement; and

where the spectral shape adjustment module is configured to average the first speech template in quite conditions with the second speech template in noisy conditions based on the weight factor to generate the weighted long-term speech curve.

14. The system of claim 12 , where the speech intelligibility measurement module is configured to calculate the speech intelligibility measurement by determining a product of a band importance function and a band audibility function, summed over a plurality of bands of the speech signal.

15. The system of claim 12 , further comprising:

a signal power calculation module executable by the computer processor to calculate a signal power measurement for a frequency band of the speech signal; and

a background noise level estimation module executable by the computer processor to estimate a background noise level for the frequency band of the speech signal;

where the speech intelligibility measurement module is configured to calculate the speech intelligibility measurement from the signal power measurement, the background noise level, and a band importance value associated with the frequency band of the speech signal.

16. The system of claim 12 , where the adaptive equalization module is configured to apply a prior version of the equalization coefficients to a power spectrum of the speech signal to generate an equalized signal;

where the adaptive equalization module is configured to adapt the equalization coefficients to generate an adapted version of the equalization coefficients based on a difference between the equalized signal and the weighted long-term speech curve; and

where the adaptive equalization module is configured to apply the adapted version of the equalization coefficients to the speech signal to transform one or more aspects of the speech signal and produce an output speech signal.

17. The system of claim 12 , further comprising:

a background noise level estimation module executable by the computer processor to calculate a background noise level of the speech signal; and

a normalization module executable by the computer processor to normalize the weighted long-term speech curve based on a power measurement of the speech signal to generate a normalized speech curve;

where the adaptive equalization module is configured to apply a prior version of the equalization coefficients to a power spectrum of the speech signal to generate an equalized signal;

where the adaptive equalization module is configured to sum the background noise level and the normalized speech curve to generate a summed signal;

where the adaptive equalization module is configured to calculate an error signal based on a difference between the summed signal and the equalized signal; and

where the adaptive equalization module is configured to adapt the equalization coefficients based on the error signal to generate an adapted version of the equalization coefficients.

18. The system of claim 12 , further comprising an adaptation constraint module executable by the computer processor to compare a signal-to-noise ratio of the speech signal to a predetermined upper threshold or a predetermined lower threshold, where the adaptation constraint module is configured to limit a boosting gain of the equalization coefficients in response to a determination that the signal-to-noise ratio is above the predetermined upper threshold or below the predetermined lower threshold.

19. The system of claim 12 , further comprising an adaptation constraint module executable by the computer processor to determine whether an adaptation of the equalization coefficients based on the weighted long-term speech curve would increase or decrease the speech intelligibility measurement of the speech signal, where the adaptation constraint module is configured to constrain the adaptation of the equalization coefficients in response to a determination that the adaptation of the equalization coefficients would decrease the speech intelligibility measurement.

20. A non-transitory computer-readable medium with instructions stored thereon, where the instructions are executable by a computer processor to cause the computer processor to perform the steps of:

calculating a speech intelligibility measurement of a speech signal;

obtaining a first predetermined long-term average speech curve;

obtaining a second predetermined long-term average speech curve;

generating a weighted long-term speech curve based on the first predetermined long-term average speech curve, the second predetermined long-term average speech curve, and the speech intelligibility measurement; and

adapting equalization coefficients for the speech signal based on the weighted long-term speech curve.

21. The non-transitory computer-readable medium of claim 18 , where the instructions executable by the computer processor to cause the computer processor to calculate the speech intelligibility measurement comprise instructions executable by the computer processor to cause the computer processor to perform the steps of:

calculating a signal power measurement for a frequency band of the speech signal;

estimating a background noise level for the frequency band of the speech signal; and

calculating the speech intelligibility measurement from the signal power measurement, the background noise level, and a band importance value associated with the frequency band of the speech signal.

22. The non-transitory computer-readable medium of claim 18 , where the instructions executable by the computer processor to cause the computer processor to adapt the equalization coefficients comprise instructions executable by the computer processor to cause the computer processor to perform the steps of:

normalizing the weighted long-term speech curve based on a power measurement of the speech signal to generate a normalized speech curve;

applying a prior version of the equalization coefficients to a power spectrum of the speech signal to generate an equalized signal;

estimating a background noise level of the speech signal;

summing the background noise level and the normalized speech curve to generate a summed signal;

calculating an error signal based on a difference between the summed signal and the equalized signal; and

adapting the equalization coefficients based on the error signal to generate an adapted version of the equalization coefficients.

Assignments (6)
NUNC PRO TUNC ASSIGNMENT Recorded Jun 19, 2023
From: BLACKBERRY LIMITED
To: MALIKIE INNOVATIONS LIMITED
Reel/Frame 064271/0199 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 16, 2023
From: BLACKBERRY LIMITED
To: MALIKIE INNOVATIONS LIMITED
Reel/Frame 064104/0103 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 22, 2020
From: 2236008 ONTARIO INC.
To: BLACKBERRY LIMITED
Reel/Frame 053313/0315 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 4, 2014
From: 8758271 CANADA INC.
To: 2236008 ONTARIO INC.
Reel/Frame 032607/0674 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 4, 2014
From: QNX SOFTWARE SYSTEMS LIMITED
To: 8758271 CANADA INC.
Reel/Frame 032607/0943 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 7, 2012
From: HETHERINGTON, PHILLIP ALAN; LI, XUEMAN
To: QNX SOFTWARE SYSTEMS LIMITED
Reel/Frame 028167/0307 →
Continuity (1)
Related Publication 20130297306A1 · Nov 7, 2013