PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Robustness of phoneme recognition using Support Vector Machines
Lena Khoo, Zoran Cvetkovic and Peter Sollich
In: ICASSP 2006, 14-19 May 2006, Toulouse, France.

Abstract

The robustness of phoneme recognition using support vector machines to additive noise is investigated for three kinds of speech representation. The representations considered are PLP, PLP with RASTA processing, and a high-dimensional principal component approximation of acoustic waveforms. While the classification in the PLP and PLP/RASTA domains attains superb accuracy on clean data, the classification in the high-dimensional space proves to be much more robust to additive noise.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Speech
ID Code:1779
Deposited By:Peter Sollich
Deposited On:28 November 2005