Disambiguation of Korean Utterances Using Automatic Intonation Recognition

The paper describes a research on a use of intonation for disambiguating utterance types of Korean spoken sentences. Based on tilt intonation theory (Taylor and Black 1994), two related but separate experiments were performed at speaker independent level, both using the Hidden Markov Model training technique. In the first experiment, a system is established so that rough boundary positions of major intonation events are detected. Subsequently the significant parameters are extracted from the products of the first experiment, which are directly used to train the final models for utterance type disambiguation. Results show that the intonation contour can be used as a significant meaning distinguisher in an automatic speech recognition system of Korean as well as in a natural human communication system

The Grammatical Function Analysis between Korean Adnoun Clause and Noun Phrase by Using Support Vector Machines

This study aims to improve the performance of identifying grammatical functions between an adnoun clause and a noun phrase in Korean. The key task is to determine the relation between the two constituents in terms of such functional categories as subject, object, adverbial, and appositive. The problem is mainly caused by the fact that functional morphemes, which are considered to be crucial for identifying the relation, are frequently omitted in the noun phrases. To tackle this problem, we propose to employ the Support Vector Machines(SVM) in determining the grammatical functions

DISAMBIGUATION OF KOREAN UTTERANCES USING AUTOMATIC INTONATION RECOGNITION

The paper describes a research on a use of intonation for disambiguating utterance types of Korean 1 spoken sentences. Based on tilt intonation theory [8], two related but separate experiments were performed, both using the Hidden Markov Model training technique. In the first experiment, a system is established so that rough boundary positions of major intonation events are detected. Subsequently the significant parameters are extracted from the products of the first experiment, which are directly used to train the final models for utterance type disambiguation. Results show that the intonation contour can be used as a significant meaning distinguisher in an automatic speech recognition system of Korean as well as in a natural human communication system. 1