Speaker-independent automatic classification of Thai tones in connected speech by analysis-synthesis method

Tone classification is a crucial component of any automatic speech recognition system for tone languages. It is imperative that tonal information be incorporated into the word hypothesization process because patterns of pitch (or tones) contribute to the lexical identification of the individual words. In this paper, we present a novel algorithm for automatically classifying Thai tones in connected speech using an analysis-synthesis method based on an extension to Fujisaki's model. We have successfully incorporated into the model two major factors affecting the phonetic realization of tones in connected speech: tonal coarticulation and declination. Also addressed is an F₀ normalization procedure for achieving speaker-independence. In our preliminary experiment, we were able to achieve 89.1% classification accuracy