Generalized Minimal Distortion Segmentation for ANN-based Speech Recognition

Sin-Horng Chen, Wen Yuan Chen

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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
Article number366545
Pages (from-to)141-145
Number of pages5
JournalIEEE Transactions on Speech and Audio Processing
Issue number2
StatePublished - Mar 1995


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