IP Library Granted Patent US 8,311,819
Granted Patent B2
US 8,311,819 · App. 12/079,376 · Granted Nov 13, 2012

System for detecting speech with background voice estimates and noise estimates

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Quick Facts
Patent No.
US 8,311,819
App. No.
12/079,376
Granted
Nov 13, 2012
Kind
B2
Abstract

A system detects a speech segment that may include unvoiced, fully voiced, or mixed voice content. The system includes a digital converter that converts a time-varying input signal into a digital-domain signal. A window function passes signals within a programmed aural frequency range while substantially blocking signals above and below the programmed aural frequency range when multiplied by an output of the digital converter. A frequency converter converts the signals passing within the programmed aural frequency range into a plurality of frequency bins. A background voice detector estimates the strength of a background speech segment relative to the noise of selected portions of the aural spectrum. A noise estimator estimates a maximum distribution of noise to an average of an acoustic noise power of some of the plurality of frequency bins. A voice detector compares the strength of a desired speech segment to a criterion based on an output of the background voice detector and an output of the noise estimator.

Claims (35)

1. A process that improves speech detection by processing a limited frequency band comprising:

encoding a limited frequency band of an input into a signal by varying an amplitude of a pulse width modulated signal that is limited to a plurality of predefined values;

separating the signal into frequency bins in which each frequency bin identifies an amplitude and a phase;

estimating a signal strength of a background voice segment in time;

estimating a distribution of noise to an average acoustic power of one or a plurality of frequency bins;

comparing a signal-to-noise ratio of each frequency bin to a maximum of the estimated signal strength of the background voice segment and the estimated distribution of noise to the average acoustic power; and

identifying a speech segment from noise that surrounds the speech segment based on the comparison.

2. The process that improves speech detection of claim 1 , where a Fast Fourier transform separates the signal into frequency bins.

3. The process that improves speech detection of claim 1 , where the act of estimating of the signal strength of the background voice segment comprises an estimate of a time smoothed signal.

4. The process that improves speech detection of claim 3 , where the act of estimating of the signal strength of the background voice segment comprises measuring a signal-to-noise ratio of the time smoothed signal.

5. The process that improves speech detection of claim 4 , further comprising modifying the estimation of the signal strength of the background voice segment through a multiplication with a scalar quantity.

6. The process that improves speech detection of claim 4 , further comprising modifying the estimation of the signal strength of the background voice segment through a subtraction of an offset.

7. The process that improves speech detection of claim 1 , further comprising modifying the estimation of the distribution of noise the average acoustic power through a multiplication with a scalar quantity.

8. The process that improves speech detection of claim 1 , further comprising modifying the estimation of the distribution of noise to the average acoustic power through an addition of an offset.

9. A process that improves speech processing by processing a limited frequency band comprising:

converting a limited frequency band of a continuously varying input into a digital-domain signal;

converting the digital-domain signal into a frequency-domain signal;

estimating a signal strength of a smoothed background voice segment in time of the digital-domain signal relative to noise;

estimating a noise-variance of a segment of the digital-domain signal;

comparing an instant signal-to-noise ratio of the digital-domain signal to the estimated signal strength of the smoothed background voice segment in time of the digital domain signal relative to noise and the estimated noise-variance; and

identifying a speech segment when the instant signal-to-noise ratio of the digital-domain signal exceeds a maximum of the estimated signal strength of the smoothed background voice segment relative to noise and the estimated noise variance.

10. The process that improves speech processing of claim 9 , further comprising modifying the estimation of the signal strength of the smooth background voice segment through a multiplication with a scalar quantity.

11. The process that improves speech processing of claim 10 , where the scalar quantity is less than one.

12. The process that improves speech processing of claim 9 , further comprising modifying the estimation of the signal strength of the smoothed background voice segment through a subtraction of an offset.

13. The process that improves speech processing of claim 9 , further comprising modifying the estimation of the noise-variance through a multiplication with a scalar quantity.

14. The process that improves speech processing of claim 13 , where the scalar quantity is greater than about one.

15. The process that improves speech processing of claim 9 , further comprising modifying the estimation of the noise-variance through an addition of an offset.

16. A system that detects a speech segment that includes an unvoiced, a fully voiced, or a mixed voice content comprising:

a digital converter that converts a time-varying input signal into a digital-domain signal;

a window function configured to pass signals within a programmed aural frequency range while substantially blocking signals above and below the programmed aural frequency range when multiplied by an output of the digital converter;

a frequency converter that converts the signals passing within the programmed aural frequency range into a plurality of frequency bins;

a background voice detector configured to estimate a strength of a background speech segment relative to noise of selected portions of an aural spectrum;

a noise estimator configured to estimate a maximum distribution of noise to an average of an acoustic noise power of some of the plurality of frequency bins; and

a voice detector configured to compare an instant signal-to-noise ratio of a desired speech segment to a maximum of an output of the background voice detector and an output of the noise estimator.

17. The system of claim 16 further comprising an end-pointer that applies one or more static or dynamic rules to determine a beginning or an end of the desired speech segment processed by the voice detector.

Assignments (5)
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 →
CHANGE OF NAME Recorded Feb 27, 2012
From: QNX SOFTWARE SYSTEMS CO.
To: QNX SOFTWARE SYSTEMS LIMITED
Reel/Frame 027768/0863 →
SECURITY AGREEMENT Recorded May 8, 2009
From: HARMAN INTERNATIONAL INDUSTRIES, INCORPORATED; BECKER SERVICE-UND VERWALTUNG GMBH; CROWN AUDIO, INC.; HARMAN BECKER AUTOMOTIVE SYSTEMS (MICHIGAN), INC.; HARMAN BECKER AUTOMOTIVE SYSTEMS HOLDING GMBH; HARMAN BECKER AUTOMOTIVE SYSTEMS, INC.; HARMAN CONSUMER GROUP, INC.; HARMAN DEUTSCHLAND GMBH; HARMAN FINANCIAL GROUP LLC; HARMAN HOLDING GMBH & CO. KG; HARMAN MUSIC GROUP, INCORPORATED; HARMAN SOFTWARE TECHNOLOGY INTERNATIONAL BETEILIGUNGS GMBH; HARMAN SOFTWARE TECHNOLOGY MANAGEMENT GMBH; HBAS INTERNATIONAL GMBH; HBAS MANUFACTURING, INC.; INNOVATIVE SYSTEMS GMBH NAVIGATION-MULTIMEDIA; JBL INCORPORATED; LEXICON, INCORPORATED; MARGI SYSTEMS, INC.; QNX SOFTWARE SYSTEMS (WAVEMAKERS), INC.; QNX SOFTWARE SYSTEMS CANADA CORPORATION; QNX SOFTWARE SYSTEMS CO.; QNX SOFTWARE SYSTEMS GMBH; QNX SOFTWARE SYSTEMS GMBH & CO. KG; QNX SOFTWARE SYSTEMS INTERNATIONAL CORPORATION; QNX SOFTWARE SYSTEMS, INC.; XS EMBEDDED GMBH (F/K/A HARMAN BECKER MEDIA DRIVE TECHNOLOGY GMBH)
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 022659/0743 →