Domain action classification using a maximum entropy model in a schedule management domain

Since speaker's intentions can be represented into domain actions (pairs of domain-independent speech acts and domain-dependent concept sequences) in goal-oriented dialogues, domain action classification is an essential part to a dialogue system. In this paper, we propose a domain action classification model to determine speech acts and concept sequences at the same time in a schedule management domain. To avoid biased learning problems, the proposed model uses low-level linguistic features and filters out uninformative features using 2 statistic. Then, the proposed model determines domain actions using a maximum entropy model. In the experiment, the proposed model showed better performances than previous works in speech act classification. In addition, the proposed model showed high performances in concept sequence classification. Based on these experimental results, we believe that the proposed model will be more helpful to a dialogue system than previous speech act classificat...

• Type: Journal
• Year: 2008
• Where: AICOM
• Authors: Hyunjung Lee, Harksoo Kim, Jungyun Seo
• Keywords: AICOM 2008, Domain Actions, Model, Speech Acts