Interactional style detection for versatile dialogue response using prosodic and semantic features

Wei Bin Liang, Chung Hsien Wu, Chih Hung Wang, Jhing Fa Wang

研究成果: Conference article同行評審

2 引文 斯高帕斯(Scopus)

摘要

This work presents an approach to interactional style (IS) detection for versatile responses in spoken dialogue systems (SDSs). Since speakers generally express their intents in different styles, the responses of an SDS should be versatile instead of invariable, planned responses. Moreover, the IS of dialogue turns can be affected by dialogue topics and speakers' emotional states. In this study, three base-level classifiers are employed for preliminary detection, including latent Dirichlet allocation for dialogue topic categorization, support vector machine for prosody-based emotional state identification and maximum entropy for semantic label-based emotional state identification. Finally, an artificial neural network is adopted for IS detection considering the scores estimated from the aforementioned classifiers. To evaluate the proposed approach, an SDS in a chatting domain was constructed for evaluation. The performance of IS detection can achieve 82.67%.

原文English
頁(從 - 到)1345-1348
頁數4
期刊Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
出版狀態Published - 2011
事件12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy
持續時間: 2011 8月 272011 8月 31

All Science Journal Classification (ASJC) codes

  • 語言與語言學
  • 人機介面
  • 訊號處理
  • 軟體
  • 建模與模擬

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