Analyzing user utterances in barge-in-able spoken dialogue system for improving identification accuracy

In our barge-in-able spoken dialogue system, the user's behaviors such as barge-in timing and utterance expressions vary according to his/her characteristics and situations. The system adapts to the behaviors by modeling them. We analyzed 1584 utterances collected by our systems of quiz and news-listing tasks and showed that ratio of using referential expressions depends on individual users and average lengths of listed items. This tendency was incorporated as a prior probability into our method and improved the identification accuracy of the user's intended items.

• Type: Journal
• Year: 2010
• Where: INTERSPEECH
• Authors: Kyoko Matsuyama, Kazunori Komatani, Ryu Takeda, Toru Takahashi, Tetsuya Ogata, Hiroshi G. Okuno
• Keywords: Barge-in Timing, INTERSPEECH 2010, Signal Processing, Spoken Dialogue System, Utterance Expressions