Phoneme classification using naive Bayes classifier in reconstructed phase space

Jinjin Ye; R. J. Povinelli; M. T. Johnson

doi:10.1109/DSPWS.2002.1231072

Phoneme classification using naive Bayes classifier in reconstructed phase space

Jinjin Ye, R. J. Povinelli, M. T. Johnson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

16 Scopus citations

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.

Original language	English
Title of host publication	Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002
Pages	37-40
Number of pages	4
ISBN (Electronic)	0780381165, 9780780381162
DOIs	https://doi.org/10.1109/DSPWS.2002.1231072
State	Published - 2002
Event	10th IEEE Digital Signal Processing Workshop, DSP 2002 and the 2nd IEEE Workshop on Signal Processing Education, SPE 2002 - Pine Mountain, United States Duration: Oct 13 2002 → Oct 16 2002

Publication series

Name	Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002

Conference

Conference	10th IEEE Digital Signal Processing Workshop, DSP 2002 and the 2nd IEEE Workshop on Signal Processing Education, SPE 2002
Country/Territory	United States
City	Pine Mountain
Period	10/13/02 → 10/16/02

Bibliographical note

Publisher Copyright:
© 2002 IEEE.

ASJC Scopus subject areas

Signal Processing

Access to Document

10.1109/DSPWS.2002.1231072

Cite this

Ye, J., Povinelli, R. J., & Johnson, M. T. (2002). Phoneme classification using naive Bayes classifier in reconstructed phase space. In Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002 (pp. 37-40). Article 1231072 (Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002). https://doi.org/10.1109/DSPWS.2002.1231072

Ye, Jinjin ; Povinelli, R. J. ; Johnson, M. T. / Phoneme classification using naive Bayes classifier in reconstructed phase space. Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002. 2002. pp. 37-40 (Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002).

@inproceedings{0fa9c5952ccc4059b3cc3a6446f8ecaa,

title = "Phoneme classification using naive Bayes classifier in reconstructed phase space",

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.",

author = "Jinjin Ye and Povinelli, {R. J.} and Johnson, {M. T.}",

note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; 10th IEEE Digital Signal Processing Workshop, DSP 2002 and the 2nd IEEE Workshop on Signal Processing Education, SPE 2002 ; Conference date: 13-10-2002 Through 16-10-2002",

year = "2002",

doi = "10.1109/DSPWS.2002.1231072",

language = "English",

series = "Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002",

pages = "37--40",

booktitle = "Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002",

}

Ye, J, Povinelli, RJ & Johnson, MT 2002, Phoneme classification using naive Bayes classifier in reconstructed phase space. in Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002., 1231072, Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002, pp. 37-40, 10th IEEE Digital Signal Processing Workshop, DSP 2002 and the 2nd IEEE Workshop on Signal Processing Education, SPE 2002, Pine Mountain, United States, 10/13/02. https://doi.org/10.1109/DSPWS.2002.1231072

Phoneme classification using naive Bayes classifier in reconstructed phase space. / Ye, Jinjin; Povinelli, R. J.; Johnson, M. T.
Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002. 2002. p. 37-40 1231072 (Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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Ye J, Povinelli RJ, Johnson MT. Phoneme classification using naive Bayes classifier in reconstructed phase space. In Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002. 2002. p. 37-40. 1231072. (Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002). doi: 10.1109/DSPWS.2002.1231072

Phoneme classification using naive Bayes classifier in reconstructed phase space

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