Techniques for handling convolutional distortion with `missing data' automatic speech recognition

Kalle J Palomäki; Guy J Brown; Jon P Barker

doi:10.1016/j.specom.2004.02.005

Techniques for handling convolutional distortion with `missing data' automatic speech recognition

Speech Communication ◽

10.1016/j.specom.2004.02.005 ◽

2004 ◽

Vol 43 (1-2) ◽

pp. 123-142 ◽

Cited By ~ 47

Author(s):

Kalle J Palomäki ◽

Guy J Brown ◽

Jon P Barker

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Automatic Speech Recognition

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Automatic Speech Recognition Using Missing Data Techniques: Handling of Real-World Data

Robust Speech Recognition of Uncertain or Missing Data ◽

10.1007/978-3-642-21317-5_7 ◽

2011 ◽

pp. 157-185 ◽

Cited By ~ 4

Author(s):

Jort F. Gemmeke ◽

Maarten Van Segbroeck ◽

Yujun Wang ◽

Bert Cranen ◽

Hugo Van hamme

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Automatic Speech Recognition ◽

Real World ◽

Real World Data ◽

World Data ◽

Missing Data Techniques

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Missing data techniques using voicing probability for robust automatic speech recognition

Electronics Letters ◽

10.1049/el:20010470 ◽

2001 ◽

Vol 37 (11) ◽

pp. 723

Author(s):

L.Y. Kim ◽

H.Y. Cho ◽

Y.H. Oh

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Automatic Speech Recognition ◽

Missing Data Techniques

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A Missing Data-based Feature Fusion Strategy for Noise-Robust Automatic Speech Recognition Using Noisy Sensors

2007 IEEE International Symposium on Circuits and Systems ◽

10.1109/iscas.2007.378087 ◽

2007 ◽

Cited By ~ 2

Author(s):

Cenk Demiroglu ◽

David V. Anderson ◽

Mark. A. Clements

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Automatic Speech Recognition ◽

Feature Fusion ◽

Fusion Strategy ◽

Noise Robust

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Handling convolutional noise in missing data automatic speech recognition

10.21437/interspeech.2006-642 ◽

2006 ◽

Author(s):

Maarten Van Segbroeck ◽

Hugo Van hamme

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Automatic Speech Recognition

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Handling derivative filterbank features in bounded-marginalization-based missing data automatic speech recognition

10.21437/interspeech.2015-707 ◽

2015 ◽

Author(s):

Marco Kühne

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Automatic Speech Recognition

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Handling Time-Derivative Features in a Missing Data Framework for Robust Automatic Speech Recognition

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings ◽

10.1109/icassp.2006.1660015 ◽

2006 ◽

Cited By ~ 1

Author(s):

H. Van Hamme

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Automatic Speech Recognition ◽

Time Derivative ◽

Handling Time ◽

Data Framework

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Vector-quantization based mask estimation for missing data automatic speech recognition

10.21437/interspeech.2007-330 ◽

2007 ◽

Cited By ~ 1

Author(s):

Maarten Van Segbroeck ◽

Hugo Van hamme

Keyword(s):

Speech Recognition ◽

Missing Data ◽

Vector Quantization ◽

Automatic Speech Recognition ◽

Mask Estimation

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Automatic speech recognition at the University of Paris

PsycEXTRA Dataset ◽

10.1037/e506252009-002 ◽

1975 ◽

Keyword(s):

Speech Recognition ◽

Automatic Speech Recognition ◽

University Of Paris ◽

The University

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Multichannel Spatial Clustering for Robust Far-Field Automatic Speech Recognition in Mismatched Conditions

10.21437/interspeech.2016-1275 ◽

2016 ◽

Cited By ~ 4

Author(s):

Michael I. Mandel ◽

Jon Barker

Keyword(s):

Speech Recognition ◽

Automatic Speech Recognition ◽

Spatial Clustering ◽

Far Field

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Using Clinician Annotations to Improve Automatic Speech Recognition of Stuttered Speech

10.21437/interspeech.2016-1388 ◽

2016 ◽

Cited By ~ 4

Author(s):

Peter A. Heeman ◽

Rebecca Lunsford ◽

Andy McMillin ◽

J. Scott Yaruss

Keyword(s):

Speech Recognition ◽

Automatic Speech Recognition

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