Typed Dependency Relations for Syntactic Analysis of Thai Sentences

Abstract. This paper describes a preliminary effort in identifying many different types of relations among words in Thai sentences based on dependency grammar. The relation is represented as a triple containing the pair of words and their relation. So far, the current representation contains 35 grammatical relations. The dependencies are all binary relations. That is, a grammatical relation holds between a governor and a dependent. The analysis makes use of the Thai “Orchid ” corpus part-of-speech tags and the Stanford typed dependencies definitions

Prosodic Annotation in a Thai Text-to-speech System

PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 200

A Lexicalized Tree Adjoining Grammar for Thai

PACLIC 23 / City University of Hong Kong / 3-5 December 200

Integrating Prosodics into a Language Model for Spoken Language Understanding of Thai

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

Prosodic disambiguation in automatic speech understanding of Thai

This research is aimed at studying the role of prosody in automatic speech understanding systems. It is believed that incorporating prosodic information into the current speech recognition scheme will improve performance. Prosody can be defined as changes in F\sb0, timing and intensity of speech, and it is used to signal linguistic and affective information. Linguistic prosody which is used to signal grammatical information at the syllable, word, or sentence level, such as stress or intonation, is of primary interest. The language chosen for this investigation is Thai. Thai belongs to the class of tone languages, for which variations in F\sb0 at the syllable level signal differences in lexical meaning. Every Thai syllable carries a lexically-contrastive F\sb0 contour, or tone, and Thai has five tones: mid, low, falling, high, and rising. Three specific issues are addressed: (1) automatic stress detection; (2) automatic tone classification; and (3) constraint dependency parsing with prosodic disambiguation. Two experiments were designed to empirically study the acoustic characteristics of stressed and unstressed syllables in terms of the vowel length distinction and the relative importance of each acoustic correlate in signaling stress. We then developed a stress classification algorithm based on a Bayesian classifier with linear discriminant scores. A duration normalization procedure based on the mean rhyme duration for each syllable type was used to neutralize durational differences due to differences in segmental composition. Our classifier achieved a 97% classification accuracy. Next, coarticulatory effects among tones were examined through an acoustic experiment using trisyllabic sequences. We then developed an analysis-by-synthesis method of tone classification based on our extension to Fujisaki\u27s model of F\sb0 contour synthesis. We also developed an F\sb0 normalization procedure using an equivalent-rectangular-bandwidth (ERB) scale conversion and z-score normalization to account for intra- and interspeaker variability and a time-varying mean-scaling procedure to account for declination effect. Our tone classifier achieved an 89.1% classification accuracy. Finally, prosodic constraints were incorporated into the language model for Thai. We extended PARSEC, a constraint-based language parser, to include prosodic constraints for ambiguity resolution. Prosodic constraints determined whether the input prosodic structure agrees with that of each of the competing sentence hypotheses of an ambiguous utterance

Prosodic Annotation in a Thai Text-to-speech System

Abstract. This paper describes a preliminary work on prosody modeling aspect of a text-to-speech system for Thai. Specifically, the model is designed to predict symbolic markers from text (i.e., prosodic phrase boundaries, accent, and intonation boundaries), and then using these markers to generate pitch, intensity, and durational patterns for the synthesis module of the system. In this paper, a novel method for annotating the prosodic structure of Thai sentences based on dependency representation of syntax is presented. The goal of the annotation process is to predict from text the rhythm of the input sentence when spoken according to its intended meaning. The encoding of the prosodic structure is established by minimizing speech disrhythmy while maintaining the congruency with syntax. That is, each word in the sentence is assigned a prosodic feature called strength dynamic which is based on the dependency representation of syntax. The strength dynamics assigned are then used to obtain rhythmic groupings in terms of a phonological unit called foot. Finally, the foot structure is used to predict the durational pattern of the input sentence. The aforementioned process has been tested on a set of ambiguous sentences, which represents various structural ambiguities involving five types of compounds in Thai