About combining forward and backward-based decoders for selecting data for unsupervised training of acoustic models

Mapping Intimacies ◽

10.21437/interspeech.2014-208 ◽

2014 ◽

Author(s):

Denis Jouvet ◽

Dominique Fohr

Keyword(s):

Acoustic Models ◽

Unsupervised Training

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Towards unsupervised training of speaker independent acoustic models

10.21437/interspeech.2011-184 ◽

2011 ◽

Author(s):

Aren Jansen ◽

Kenneth Church

Keyword(s):

Acoustic Models ◽

Speaker Independent ◽

Unsupervised Training

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The use of sense in unsupervised training of acoustic models for ASR systems

10.21437/interspeech.2010-23 ◽

2010 ◽

Author(s):

Rita Singh ◽

Benjamin Lambert ◽

Bhiksha Raj

Keyword(s):

Acoustic Models ◽

Unsupervised Training

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Unsupervised training of acoustic models for large vocabulary continuous speech recognition

IEEE Transactions on Speech and Audio Processing ◽

10.1109/tsa.2004.838537 ◽

2005 ◽

Vol 13 (1) ◽

pp. 23-31 ◽

Cited By ~ 44

Author(s):

F. Wessel ◽

H. Ney

Keyword(s):

Speech Recognition ◽

Continuous Speech ◽

Continuous Speech Recognition ◽

Large Vocabulary ◽

Acoustic Models ◽

Unsupervised Training

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Exploiting large quantities of spontaneous speech for unsupervised training of acoustic models

10.21437/interspeech.2005-532 ◽

2005 ◽

Author(s):

Bhuvana Ramabhadran

Keyword(s):

Spontaneous Speech ◽

Acoustic Models ◽

Unsupervised Training

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Unsupervised training of acoustic models for large vocabulary continuous speech recognition

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. ◽

10.1109/asru.2001.1034648 ◽

2005 ◽

Cited By ~ 15

Author(s):

F. Wessel ◽

H. Ney

Keyword(s):

Speech Recognition ◽

Continuous Speech ◽

Continuous Speech Recognition ◽

Large Vocabulary ◽

Acoustic Models ◽

Unsupervised Training

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How Neural Network Depth Compensates for HMM Conditional Independence Assumptions in DNN-HMM Acoustic Models

10.21437/interspeech.2016-283 ◽

2016 ◽

Cited By ~ 1

Author(s):

Suman Ravuri ◽

Steven Wegmann

Keyword(s):

Neural Network ◽

Conditional Independence ◽

Acoustic Models ◽

Independence Assumptions

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Impact of Aliasing on Deep CNN-Based End-to-End Acoustic Models

10.21437/interspeech.2018-1371 ◽

2018 ◽

Cited By ~ 2

Author(s):

Yuan Gong ◽

Christian Poellabauer

Keyword(s):

Acoustic Models ◽

Deep Cnn ◽

End To End

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Supervised Learning of Acoustic Models in a Zero Resource Setting to Improve DPGMM Clustering

10.21437/interspeech.2016-988 ◽

2016 ◽

Cited By ~ 5

Author(s):

Michael Heck ◽

Sakriani Sakti ◽

Satoshi Nakamura

Keyword(s):

Supervised Learning ◽

Acoustic Models ◽

Resource Setting

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Domain Adaptation of CNN Based Acoustic Models Under Limited Resource Settings

10.21437/interspeech.2016-1161 ◽

2016 ◽

Cited By ~ 5

Author(s):

Masayuki Suzuki ◽

Ryuki Tachibana ◽

Samuel Thomas ◽

Bhuvana Ramabhadran ◽

George Saon

Keyword(s):

Domain Adaptation ◽

Limited Resource ◽

Acoustic Models

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Ensembles of Multi-Scale VGG Acoustic Models

10.21437/interspeech.2017-920 ◽

2017 ◽

Author(s):

Michael Heck ◽

Masayuki Suzuki ◽

Takashi Fukuda ◽

Gakuto Kurata ◽

Satoshi Nakamura

Keyword(s):

Acoustic Models ◽

Multi Scale

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