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» Automatic speech recognition system channel modeling
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ICASSP
2011
IEEE
13 years 1 months ago
Learning non-parametric models of pronunciation
As more data becomes available for a given speech recognition task, the natural way to improve recognition accuracy is to train larger models. But, while this strategy yields mode...
Brian Hutchinson, Jasha Droppo
ICASSP
2011
IEEE
13 years 1 months ago
Robust speech recognition using dynamic noise adaptation
Dynamic noise adaptation (DNA) [1, 2] is a model-based technique for improving automatic speech recognition (ASR) performance in noise. DNA has shown promise on artificially mixe...
Steven J. Rennie, Pierre L. Dognin, Petr Fousek
CSL
2007
Springer
13 years 10 months ago
Discriminative semi-parametric trajectory model for speech recognition
Hidden Markov Models (HMMs) are the most commonly used acoustic model for speech recognition. In HMMs, the probability of successive observations is assumed independent given the ...
K. C. Sim, M. J. F. Gales
NGC
2010
Springer
116views Communications» more  NGC 2010»
13 years 8 months ago
Speech Structure and Its Application to Robust Speech Processing
Speech communication consists of three steps: production, transmission, and hearing. Every step inevitably involves acoustic distortions due to gender differences, age, microphone...
Nobuaki Minematsu, Satoshi Asakawa, Masayuki Suzuk...
ACSC
2004
IEEE
14 years 1 months ago
Learning Models for English Speech Recognition
This paper reports on an experiment to determine the optimal parameters for a speech recogniser that is part of a computer aided instruction system for assisting learners of Engli...
Huayang Xie, Peter Andreae, Mengjie Zhang, Paul Wa...