Paper: Improving Korean Speech Acts Analysis by Using Shrinkage and Discourse Stack

ACL ID I05-1064
Title Improving Korean Speech Acts Analysis by Using Shrinkage and Discourse Stack
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2005
Authors

A speech act is a linguistic action intended by a speaker. It is impor- tant to analyze the speech act for the dialogue understanding system because the speech act of an utterance is closely tied with the user’s intention in the utter- ance. This paper proposes to use a speech acts hierarchy and a discourse stack for improving the accuracy of classifiers in speech acts analysis. We first adopt a hierarchical statistical technique called shrinkage to solve the data sparseness problem. In addition, we use a discourse stack in order to easily apply discourse structure information to the speech acts analysis. From the results of experi- ments, we observed that the proposed model made a significant improvement for Korean speech acts analysis. Moreover, we found that it can be more usef...