PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Subband Acoustic Waveform Front-End for Robust Speech Recognition Using Support Vector Machines
J K Yousafzai, Z Cvetkovic and P Sollich
In: IEEE Workshop on Spoken Language Technology, 12-15 Dec 2010, Berkeley, California, USA.

Abstract

A subband acoustic waveform front-end for robust speech recognition using support vector machines (SVMs) is developed. The primary issues of kernel design for subband components of acoustic waveforms and combination of the individual subband classifiers using stacked generalization are addressed. Experiments performed on the TIMIT phoneme classification task demonstrate the benefits of classification in frequency subbands; the subband classifier outperforms the cepstral classifiers in the presence of noise for signal-to-noise ratio (SNR) below 12dB.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Speech
ID Code:7687
Deposited By:Jibran Yousafzai
Deposited On:17 March 2011