Automatic question detection: prosodic-lexical features and crosslingual experiments

نویسندگان

  • Minh-Quang Vu
  • Laurent Besacier
  • Eric Castelli
چکیده

In this paper, we present our work on automatic question detection from the speech signal. We are interested in developing automatic detection system and investigate the portability of such system to a new language. The first goal of this paper is to propose and evaluate a combined approach for automatic question detection where prosodic features are augmented by the use of lexical features. It is shown that both early and late integration of theses features in a decision treebased classifier improves the question detection performance compared to a baseline system using prosodic features only. The second goal of this paper is to conduct a crosslingual (French / Vietnamese) evaluation concerning the use of prosodic features. It is shown that our first system developed for French which uses an initial prosodic feature set can be improved using a new feature set that takes into account some specific prosodic characteristics of the Vietnamese tonal language. Both Vietnamese and French question detection systems obtain Fratio performance around 80% on pre-segmented meeting and dialog utterances.

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تاریخ انتشار 2007