Phoneme Classification Using Naïve Bayes Classifier in Reconstructed Phase Space

Authors

Jinjin Ye, Marquette UniversityFollow
Richard J. Povinelli, Marquette UniversityFollow
Michael T. Johnson, Marquette UniversityFollow

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

Accepted version. Published as part of Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, and the 2nd Signal Processing Education Workshop, 2002: 37-40. DOI. © 2002 Institute of Electrical and Electronic Engineers (IEEE). Used with permission.

Recommended Citation

Ye, Jinjin; Povinelli, Richard J.; and Johnson, Michael T., "Phoneme Classification Using Naïve Bayes Classifier in Reconstructed Phase Space" (2002). Electrical and Computer Engineering Faculty Research and Publications. 165.
https://epublications.marquette.edu/electric_fac/165