CA2147772A1 - Method of and Apparatus for Signal Recognition that Compensates for Mismatching - Google Patents

Method of and Apparatus for Signal Recognition that Compensates for Mismatching

Info

Publication number
CA2147772A1
CA2147772A1 CA2147772A CA2147772A CA2147772A1 CA 2147772 A1 CA2147772 A1 CA 2147772A1 CA 2147772 A CA2147772 A CA 2147772A CA 2147772 A CA2147772 A CA 2147772A CA 2147772 A1 CA2147772 A1 CA 2147772A1
Authority
CA
Canada
Prior art keywords
signal
stored representations
transform
mismatching
compensates
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CA2147772A
Other languages
French (fr)
Other versions
CA2147772C (en
Inventor
Chin-Hui Lee
Ananth Sankar
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
AT&T Corp
Original Assignee
AT&T Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by AT&T Corp filed Critical AT&T Corp
Publication of CA2147772A1 publication Critical patent/CA2147772A1/en
Application granted granted Critical
Publication of CA2147772C publication Critical patent/CA2147772C/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/065—Adaptation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/08—Speech classification or search
    • G10L15/14—Speech classification or search using statistical models, e.g. Hidden Markov Models [HMMs]
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G10L2015/226—Procedures used during a speech recognition process, e.g. man-machine dialogue using non-speech characteristics
    • G10L2015/228—Procedures used during a speech recognition process, e.g. man-machine dialogue using non-speech characteristics of application context
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique

Abstract

Disclosed is a method for drastically reducing the average error rate for signals under mismatched conditions. The method takes a signal (e.g, speech signal) and a set of stored representations (e.g, stored representations of keyword) and performs at least one transformation that results in the signal more closely emulating the stored representations.
This is accomplished by using one of three techniques. First, one may transform the signal so that the signal may be better approximated by (e.g, is closer to) one of the stored representations. Second, one may transform the set of stored representations so that one of the stored representations better approximates the signal. Third, one may transform both the signal and the set of stored representations.
CA002147772A 1994-06-21 1995-04-25 Method of and apparatus for signal recognition that compensates for mismatching Expired - Fee Related CA2147772C (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US08/263,284 US5727124A (en) 1994-06-21 1994-06-21 Method of and apparatus for signal recognition that compensates for mismatching
US263,284 1994-06-21

Publications (2)

Publication Number Publication Date
CA2147772A1 true CA2147772A1 (en) 1995-12-22
CA2147772C CA2147772C (en) 2000-06-13

Family

ID=23001125

Family Applications (1)

Application Number Title Priority Date Filing Date
CA002147772A Expired - Fee Related CA2147772C (en) 1994-06-21 1995-04-25 Method of and apparatus for signal recognition that compensates for mismatching

Country Status (5)

Country Link
US (1) US5727124A (en)
EP (1) EP0689194B1 (en)
JP (1) JP3457431B2 (en)
CA (1) CA2147772C (en)
DE (1) DE69524994T2 (en)

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US5924065A (en) * 1997-06-16 1999-07-13 Digital Equipment Corporation Environmently compensated speech processing
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US6202047B1 (en) * 1998-03-30 2001-03-13 At&T Corp. Method and apparatus for speech recognition using second order statistics and linear estimation of cepstral coefficients
US6381571B1 (en) * 1998-05-01 2002-04-30 Texas Instruments Incorporated Sequential determination of utterance log-spectral mean by maximum a posteriori probability estimation
US6980952B1 (en) * 1998-08-15 2005-12-27 Texas Instruments Incorporated Source normalization training for HMM modeling of speech
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US6658385B1 (en) * 1999-03-12 2003-12-02 Texas Instruments Incorporated Method for transforming HMMs for speaker-independent recognition in a noisy environment
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US6539351B1 (en) * 2000-02-04 2003-03-25 International Business Machines Corporation High dimensional acoustic modeling via mixtures of compound gaussians with linear transforms
US20020049586A1 (en) * 2000-09-11 2002-04-25 Kousuke Nishio Audio encoder, audio decoder, and broadcasting system
US7400712B2 (en) * 2001-01-18 2008-07-15 Lucent Technologies Inc. Network provided information using text-to-speech and speech recognition and text or speech activated network control sequences for complimentary feature access
US7966177B2 (en) * 2001-08-13 2011-06-21 Hans Geiger Method and device for recognising a phonetic sound sequence or character sequence
US6778957B2 (en) * 2001-08-21 2004-08-17 International Business Machines Corporation Method and apparatus for handset detection
US7139704B2 (en) * 2001-11-30 2006-11-21 Intel Corporation Method and apparatus to perform speech recognition over a voice channel
US7139336B2 (en) * 2002-04-05 2006-11-21 Nokia Corporation Method and system for channel estimation using iterative estimation and detection
US7139703B2 (en) * 2002-04-05 2006-11-21 Microsoft Corporation Method of iterative noise estimation in a recursive framework
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FR2848715B1 (en) * 2002-12-11 2005-02-18 France Telecom METHOD AND SYSTEM FOR MULTI-REFERENCE CORRECTION OF SPECTRAL VOICE DEFORMATIONS INTRODUCED BY A COMMUNICATION NETWORK
US7165026B2 (en) * 2003-03-31 2007-01-16 Microsoft Corporation Method of noise estimation using incremental bayes learning
US7729908B2 (en) * 2005-03-04 2010-06-01 Panasonic Corporation Joint signal and model based noise matching noise robustness method for automatic speech recognition
US7680656B2 (en) * 2005-06-28 2010-03-16 Microsoft Corporation Multi-sensory speech enhancement using a speech-state model
US20070033027A1 (en) * 2005-08-03 2007-02-08 Texas Instruments, Incorporated Systems and methods employing stochastic bias compensation and bayesian joint additive/convolutive compensation in automatic speech recognition
US7877255B2 (en) * 2006-03-31 2011-01-25 Voice Signal Technologies, Inc. Speech recognition using channel verification
US7630950B2 (en) * 2006-08-18 2009-12-08 International Business Machines Corporation System and method for learning models from scarce and skewed training data
JP5089295B2 (en) * 2007-08-31 2012-12-05 インターナショナル・ビジネス・マシーンズ・コーポレーション Speech processing system, method and program
JP2010020273A (en) * 2007-12-07 2010-01-28 Sony Corp Information processing device, information processing method and computer program
US8615397B2 (en) * 2008-04-04 2013-12-24 Intuit Inc. Identifying audio content using distorted target patterns
KR101238731B1 (en) * 2008-04-18 2013-03-06 돌비 레버러토리즈 라이쎈싱 코오포레이션 Method and apparatus for maintaining speech audibility in multi-channel audio with minimal impact on surround experience
US8239195B2 (en) * 2008-09-23 2012-08-07 Microsoft Corporation Adapting a compressed model for use in speech recognition
US8214215B2 (en) * 2008-09-24 2012-07-03 Microsoft Corporation Phase sensitive model adaptation for noisy speech recognition
US8306819B2 (en) * 2009-03-09 2012-11-06 Microsoft Corporation Enhanced automatic speech recognition using mapping between unsupervised and supervised speech model parameters trained on same acoustic training data
JP5150542B2 (en) * 2009-03-26 2013-02-20 株式会社東芝 Pattern recognition apparatus, pattern recognition method, and program
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JP5982297B2 (en) * 2013-02-18 2016-08-31 日本電信電話株式会社 Speech recognition device, acoustic model learning device, method and program thereof
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Also Published As

Publication number Publication date
EP0689194A1 (en) 1995-12-27
US5727124A (en) 1998-03-10
JPH0850499A (en) 1996-02-20
CA2147772C (en) 2000-06-13
DE69524994T2 (en) 2002-08-29
EP0689194B1 (en) 2002-01-16
DE69524994D1 (en) 2002-02-21
JP3457431B2 (en) 2003-10-20

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