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» Signal processing tools for speech recognition
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ICASSP
2009
IEEE
14 years 2 months ago
The use of acoustically detected filled and silent pauses in spontaneous speech recognition
In recognizing spontaneous speech, the performance of typical speech recognizers tends to be degraded by filled and silent pauses, which are hesitation phenomena frequently occur...
Jun Ogata, Masataka Goto, Katunobu Itou
ICASSP
2010
IEEE
13 years 7 months ago
Noise robust exemplar-based connected digit recognition
This paper proposes a noise robust exemplar-based speech recognition system where noisy speech is modeled as a linear combination of a set of speech and noise exemplars. The metho...
Jort F. Gemmeke, Tuomas Virtanen
TSD
2005
Springer
14 years 28 days ago
Why Is the Recognition of Spontaneous Speech so Hard?
Although speech, derived from reading texts, and similar types of speech, e.g. that from reading newspapers or that from news broadcast, can be recognized with high accuracy, recog...
Sadaoki Furui, Masanobu Nakamura, Tomohisa Ichiba,...
ICASSP
2010
IEEE
13 years 7 months ago
Optimizing spectral subtraction and wiener filtering for robust speech recognition in reverberant and noisy conditions
Speech enhancement is a common approach to address the effects of degradation due to noise and channel contamination. This approach is intended to suppress unwanted signal and rec...
Randy Gomez, Tatsuya Kawahara
ICASSP
2009
IEEE
14 years 2 months ago
Minimum variance modulation filter for robust speech recognition
This paper describes a way of designing modulation filter by datadriven analysis which improves the performance of automatic speech recognition systems that operate in real envir...
Yu-Hsiang Bosco Chiu, Richard M. Stern