Title

Phoneme Classification Using Naïve Bayes Classifier in Reconstructed Phase Space

Document Type

Conference Proceeding

Language

eng

Format of Original

4 p.

Publication Date

10-13-2002

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Source Publication

Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, and the 2nd Signal Processing Education Workshop

Source ISSN

0-7803-8116-5

Abstract

A novel method for classifying speech phonemes is presented. Unlike traditional cepstral based methods, this approach uses histograms of reconstructed phase spaces. A naive Bayes classifier uses the probability mass estimates for classification. The approach is verified using isolated fricative, vowel, and nasal phonemes from the TIMIT corpus. The results show that a reconstructed phase space approach is a viable method for classification of phonemes, with the potential for use in a continuous speech recognition system.

Comments

Published as part of Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, and the 2nd Signal Processing Education Workshop, 2002: 37-40. DOI.