Tone recognition for Thai

Author

Tungthangthum, Apichat

Author_Institution

Asian Univ. of Sci. & Technol., Chonburi, Thailand

fYear

1998

fDate

24-27 Nov 1998

Firstpage

157

Lastpage

160

Abstract

This paper describes the tone recognition for Thai language. The autocorrelation method is used to extract the pitch or fundamental frequency (FO) from a speech signal. Hidden Markov models (HMMs) are then used to recognize these pitch contours to determine the tones. Though the tone information is superimposed on the vowel portion of a syllable, recognition experiments show that tones and vowels are independent from each other. Tone information extracted from one vowel can be used on another different vowel

Keywords

correlation methods; hidden Markov models; speech recognition; Thai language; autocorrelation method; fundamental frequency; hidden Markov models; pitch contours; pitch extraction; speech signal; tone recognition; vowel portion; Autocorrelation; Cities and towns; Data mining; Databases; Frequency; Hidden Markov models; Pattern recognition; Sampling methods; Speech recognition; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1998. IEEE APCCAS 1998. The 1998 IEEE Asia-Pacific Conference on

Conference_Location

Chiangmai

Print_ISBN

0-7803-5146-0

Type

conf

DOI

10.1109/APCCAS.1998.743692

Filename

743692

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2533704