Gilchang Kim

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In some cases, to make a proper translation of an utterance in a dialogue, the system needs various information about context. In this paper, we propose a statistical dialogue analysis model based on speech acts for Korean-English dialogue machine translation. The model uses syntactic patterns and N-grams reflecting the hierarchical discourse structures of(More)
This paper presents a system for unsupervised verb sense disambiguation using small corpus and a machine-readable dictionary (MRD) in Korean. The system learns a set of typical usages listed in the MRD usage examples for each of the senses of a polysemous verb in the MRD definitions using verb-object co-occurrences acquired from the corpus. This paper(More)
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