Generalized Minimal Distortion Segmentation for ANN-based Speech Recognition

Sin-Horng Chen, Wen Yuan Chen

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

A generalized minimal distortion segmentation algorithm is proposed to solve the time alignment problem for ANN-based speech recognition. By modeling dynamics of spectral information of an acoustic segment with smooth curves obtained by orthonormal polynomial expansion, a speech signal is optimally divided into segments and then recognized by an MLP recognizer. Experimental results showed that the proposed method outperforms the standard CDHMM method.

Original languageEnglish
Pages (from-to)141-145
Number of pages5
JournalIEEE Transactions on Speech and Audio Processing
Volume3
Issue number2
DOIs
StatePublished - 1 Jan 1995

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