Source: https://patents.google.com/patent/US8457961B2/en
Timestamp: 2020-01-26 05:15:43
Document Index: 738393830

Matched Legal Cases: ['application No. 2', 'Application No. 06721766', 'Application No. 2010', 'Application No. 2007', 'Application No. 2007', 'Application No. 200680000746', 'Application No. 2007', 'Application No. 10', 'Application No. 10']

US8457961B2 - System for detecting speech with background voice estimates and noise estimates - Google Patents
US8457961B2
US8457961B2 US13/566,603 US201213566603A US8457961B2 US 8457961 B2 US8457961 B2 US 8457961B2 US 201213566603 A US201213566603 A US 201213566603A US 8457961 B2 US8457961 B2 US 8457961B2
US13/566,603
US20120303366A1 (en
Mark Ryan Fallat
2012-08-03 Application filed by QNX Software Systems Ltd filed Critical QNX Software Systems Ltd
2012-08-03 Priority to US13/566,603 priority patent/US8457961B2/en
2012-08-31 Assigned to QNX SOFTWARE SYSTEMS LIMITED reassignment QNX SOFTWARE SYSTEMS LIMITED CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: QNX SOFTWARE SYSTEMS CO.
2012-08-31 Assigned to QNX SOFTWARE SYSTEMS (WAVEMAKERS), INC. reassignment QNX SOFTWARE SYSTEMS (WAVEMAKERS), INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: FALLAT, MARK, HETHERINGTON, PHILLIP A.
2012-08-31 Assigned to QNX SOFTWARE SYSTEMS CO. reassignment QNX SOFTWARE SYSTEMS CO. CONFIRMATORY ASSIGNMENT Assignors: QNX SOFTWARE SYSTEMS (WAVEMAKERS), INC.
2012-11-29 Publication of US20120303366A1 publication Critical patent/US20120303366A1/en
2013-06-04 Publication of US8457961B2 publication Critical patent/US8457961B2/en
A system detects a speech segment that may include unvoiced, fully voiced, or mixed voice content. The system includes a window function that passes signals within a programmed aural frequency range while substantially blocking signals above and below the programmed aural frequency range. 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 maximum of an output of the background voice detector and an output of the noise estimator.
This application is a continuation of U.S. application Ser. No. 12/079,376 filed Mar. 26, 2008, which is a continuation-in-part of U.S. application Ser. No. 11/804,633 filed May 18, 2007, now U.S. Pat. No. 8,165,880, which is a continuation-in-part of U.S. application Ser. No. 11/152,922 filed Jun. 15, 2005, now U.S. Pat. No. 8,170,875. The entire content of these applications are incorporated herein by reference, except that in the event of any inconsistent disclosure from the present disclosure, the disclosure herein shall be deemed to prevail.
Some speech processors operate when voice is present. Such systems are efficient and effective when voice is detected. When noise or other interference is mistaken for voice, the noise may corrupt the data. An end-pointer may isolate voice segments from this noise. The end-pointer may apply one or more static or dynamic (e.g., automatic) rules to determine the beginning or the end of a voice segment based on one or more speech characteristics. The rules may process a portion or an entire aural segment and may include the features and content described in U.S. application Ser. No. 11/804,633 (U.S. Pat. No. 8,165,880) and 11/152,922 (U.S. Pat. No. 8,170,875), both of which are entitled “Speech End-pointer.” Both US applications are incorporated by reference. In the event of an inconsistency between those US applications and this disclosure, this disclosure shall prevail.
1. A process that improves speech detection comprising:
separating an input signal into frequency bins;
estimating a signal strength of a background voice segment or a background signal-to-noise ratio;
estimating a noise level of a background noise of one or more frequency bins;
comparing an instant signal-to-noise ratio to one or more of a maximum of the estimated signal strength of the background voice segment, a maximum of the estimated noise level of the background noise and a background signal-to-noise ratio; and
2. The process that improves speech detection of claim 1, where identifying the speech segment further leads or lags a rising or falling edge of a voice decision window dynamically or by a fixed temporal amount or by a frequency-based amount.
7. The process that improves speech detection of claim 1, further comprising modifying the estimation of the noise level of the background noise through a multiplication with a scalar quantity.
8. The process that improves speech detection of claim 1, further comprising modifying the estimation of the noise level of the background noise through an addition of an offset.
9. A process that improves speech processing comprising:
converting a limited frequency band of a continuously varying input signal into a frequency-domain signal;
estimating a signal strength of a background voice segment of the input signal;
estimating a noise-variance of a segment of the input signal;
comparing an instant signal-to-noise ratio of the input signal to the estimated signal strength of the background voice segment of the input signal and to the estimated noise-variance; and
identifying a speech segment when the instant signal-to-noise ratio of the frequency-domain signal exceeds a maximum of the estimated signal strength of the 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 background voice segment through a multiplication with a scalar quantity.
12. The process that improves speech processing of claim 9, further comprising modifying the estimation of the signal strength of the background voice segment through a subtraction of an offset.
a window function configured to pass input signals within a programmed aural frequency range while substantially blocking signals above and below the programmed aural frequency range;
a frequency converter that converts the input signals passing within the programmed aural frequency range into a plurality of frequency bins;
18. The system of claim 16, where the voice detector is further configured to lead or lag a rising or falling edge of a voice decision window dynamically or by a fixed temporal amount or by a frequency-based amount.
19. The system of claim 16, where the voice detector is further configured with a selector that provides user customization of the comparison of the instant signal-to-noise ratio of the desired speech segment to the maximum of the output of the background voice detector and the output of the noise estimator.
20. The system of claim 16, where the background voice detector is further configured to compute a time smoothed signal before estimating the strength of the background speech segment relative to noise of selected portions of the aural spectrum.
US13/566,603 2005-06-15 2012-08-03 System for detecting speech with background voice estimates and noise estimates Active US8457961B2 (en)
US12/079,376 Continuation US8311819B2 (en) 2005-06-15 2008-03-26 System for detecting speech with background voice estimates and noise estimates
US20120303366A1 US20120303366A1 (en) 2012-11-29
US8457961B2 true US8457961B2 (en) 2013-06-04
JP5459220B2 (en) * 2008-11-27 2014-04-02 日本電気株式会社 Speech detection device
CN107103916A (en) * 2017-04-20 2017-08-29 深圳市蓝海华腾技术股份有限公司 A kind of music beginning and end detection method and system applied to music fountain
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US8311819B2 (en) 2012-11-13
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