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» Signal Processing for Robust Speech Recognition
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NIPS
2003
15 years 5 months ago
One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech Signals
Speech dereverberation is desirable with a view to achieving, for example, robust speech recognition in the real world. However, it is still a challenging problem, especially when...
Tomohiro Nakatani, Masato Miyoshi, Keisuke Kinoshi...
ICMI
2004
Springer
281views Biometrics» more  ICMI 2004»
15 years 9 months ago
Articulatory features for robust visual speech recognition
Visual information has been shown to improve the performance of speech recognition systems in noisy acoustic environments. However, most audio-visual speech recognizers rely on a ...
Kate Saenko, Trevor Darrell, James R. Glass
ICASSP
2011
IEEE
14 years 8 months ago
Delta-spectral cepstral coefficients for robust speech recognition
Almost all current automatic speech recognition (ASR) systems conventionally append delta and double-delta cepstral features to static cepstral features. In this work we describe ...
Kshitiz Kumar, Chanwoo Kim, Richard M. Stern
ICASSP
2011
IEEE
14 years 8 months ago
Maximum likelihood adaptation of histogram equalization with constraint for robust speech recognition
In this paper, we propose a novel feature space adaptation technique to improve the robustness of speech recognition in noisy environments. Histogram equalization (HEQ) is an effe...
Xiong Xiao, Jinyu Li, Engsiong Chng, Haizhou Li
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ICASSP
2011
IEEE
14 years 8 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