Noise Robust Speaker-Independent Speech Recognition with Invariant-Integration Features Using Power-Bias Subtraction

被引：0

作者：

Mueller, Florian ^{[1
]}

Mertins, Alfred ^{[1
]}

机构：

[1] Med Univ Lubeck, Inst Signal Proc, Lubeck, Germany

来源：

12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5 | 2011年

关键词：

speech recognition; speaker independency; noise robustness; invariant integration; power normalization;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents new results about the robustness of invariant-integration features (IIF) in noisy conditions. Furthermore, it is shown that a feature-enhancement method known as "power-bias subtraction" for noisy conditions can be combined with the IIF approach to improve its performance in noisy environments while keeping the robustness of the IIFs to mismatching vocal-tract length training-testing conditions. Results of experiments with training on clean speech only as well as experiments with matched-condition training are presented.

引用

页码：1688 / 1691

页数：4

共 32 条

[1] Contextual invariant-integration features for improved speaker-independent speech recognition
Mueller, Florian
Mertins, Alfred
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[2] Invariant-integration method for robust feature extraction in speaker-independent speech recognition
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Mertins, Alfred
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[3] SPECTRO-TEMPORAL FEATURES FOR NOISE-ROBUST SPEECH RECOGNITION USING POWER-LAW NONLINEARITY AND POWER-BIAS SUBTRACTION
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[4] Speaker-Independent Speech Recognition using Visual Features
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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (11) : 616 - 620
[5] ON USING THE AUDITORY IMAGE MODEL AND INVARIANT-INTEGRATION FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
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2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2012, : 4905 - 4908
[6] ON USING THE AUDITORY IMAGE MODEL AND INVARIANT-INTEGRATION FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
Mueller, Florian
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2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2012, : 4905 - 4908
[7] Feature Extraction for Robust Speech Recognition using a Power-Law Nonlinearity and Power-Bias Subtraction
Kim, Chanwoo
Stern, Richard M.
INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5, 2009, : 28 - 31
[8] Robust Features for Speaker-Independent Speech Recognition Based on a Certain Class of Translation-Invariant Transformations
Mueller, Florian
Mertins, Alfred
ADVANCES IN NONLINEAR SPEECH PROCESSING, 2010, 5933 : 111 - 119
[9] An integrated study of speaker normalisation and HMM adaptation for noise robust speaker-independent speech recognition
Hariharan, R
Viikki, O
SPEECH COMMUNICATION, 2002, 37 (3-4) : 349 - 361
[10] SPEAKER-INDEPENDENT ISOLATED WORD RECOGNITION USING DYNAMIC FEATURES OF SPEECH SPECTRUM
FURUI, S
IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1986, 34 (01): : 52 - 59

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