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ICASSP
2009
IEEE

An auditory-based feature for robust speech recognition

8 years 11 months ago
An auditory-based feature for robust speech recognition
A conventional automatic speech recognizer does not perform well in the presence of noise, while human listeners are able to segregate and recognize speech in noisy conditions. We study a novel feature based on an auditory periphery model for robust speech recognition. Specifically, gammatone frequency cepstral coefficients are derived by applying a cepstral analysis on gammatone filterbank responses. Our evaluations show that the proposed feature performs considerably better than conventional acoustic features. We further demonstrate that integrating the proposed feature with a computational auditory scene analysis system yields promising recognition performance.
Yang Shao, Zhaozhang Jin, DeLiang Wang, Soundarara
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Yang Shao, Zhaozhang Jin, DeLiang Wang, Soundararajan Srinivasan
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