Publication details [#432]

Lee, Jae-Won, Jungyun Seo and Gil Chang Kim. 1998. A statistical dialogue analysis model based on speech acts for dialogue machine translation. Machine Translation 13 (4) : 269–286.
Publication type
Article in jnl/bk
Publication language
Source language
Target language


In some cases, to make a proper translation of an utterance in a dialogue, different pieces of contextual information are needed. Interpreting such utterances often requires dialogue analysis including speech acts and discourse analysis. In this paper, a statistical dialogue analysis model for Korean–English dialogue machine translation based on speech acts is proposed. The model uses syntactic patterns and n-grams of speech acts. The syntactic patterns include surface syntactic features, which are related to the language-dependent expressions of speech acts. Speech-act n-grams are used to approximate the context of utterances. The key feature is the use of speech-act n-grams based on hierarchical recency. Experimental results with trigrams show that the proposed model achieves an accuracy of 66.87% for the top candidate and 82.35% for the top three candidates. It indicates that the proposed model based on hierarchical recency outperforms the model based on linear recency.
Source : Abstract in journal