• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.241-248
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• 2007

In this paper, we propose a Transformation-Based Learning (TBL) method on generating the Korean standard pronunciation. Previous studies on the phonological processing have been focused on the phonological rule applications and the finite state automata (Johnson 1984; Kaplan and Kay 1994; Koskenniemi 1983; Bird 1995). In case of Korean computational phonology, some former researches have approached the phonological rule based pronunciation generation system (Lee et al. 2005; Lee 1998). This study suggests a corpus-based and data-oriented rule learning method on generating Korean standard pronunciation. In order to substituting rule-based generation with corpus-based one, an aligned corpus between an input and its pronunciation counterpart has been devised. We conducted an experiment on generating the standard pronunciation with the TBL algorithm, based on this aligned corpus.

• Proceedings of the Korean Society for Language and Information Conference
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• 2001.06a
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• pp.231-235
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• 2001

Language is not abstract. We use language to communicate out thoughts and emotions. Films are the most public form of arts, where language is all essential part; however, there have been, if any, few films the main theme of which is language. Although language may not be the main theme of films, we can find many kinds of information relating to language and linguistics by careful examination. In reference to some films, we can talk about subjects in the fields of theoretical linguistics such as phonetics, phonology, morphology, syntax, semantics, and pragmatics. In addition, subjects in applied linguistics such as sociolinguistics and computational linguistics may be discussed with reference to other films.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.280-287
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• 1997

The introduction of phonological knowledge, prosodic information to speech recognition and synthesis systems is very important to build successful spoken language systems. First, related works of computational phonology is overviewed and the theoretical and experimental studies of prosodic structures and boundaries in Korean are summarized. The main focus of this study is to decide which prosodic phrasing trained on a simple recurrent network. The results show information other than phonetic features. This method can be combined with other useful information to predict the boundaries more correctly and to help segmentation, which are vital for the successful speech recognition and synthesis systems.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.41-48
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• 2005

This paper presents the development of a morphological processor for the Mongolian language, based on the two-level morphological model which was introduced by Koskenniemi. The aim of the study is to provide Mongolian syntactic parsers with more effective information on word structure of Mongolian words. First hand written rules that are the core of this model are compiled into finite-state transducers by a rule tool. Output of the compiler was edited to clarity by hand whenever necessary. The rules file and lexicon presented in the paper describe the morphology of Mongolian nouns, adjectives and verbs. Although the rules illustrated are not sufficient for accounting all the processes of Mongolian lexical phonology, other necessary rules can be easily added when new words are supplemented to the lexicon file. The theoretical consideration of the paper is concluded in representation of the morphological phenomena of Mongolian by the general, language-independent framework of the two-level morphological model.