Prosody based attitude recognition with feature selection and its application to spoken dialog system as para-linguistic information

Shinya Fujie, Daizo Yagi, Hideaki Kikuchi, Tetsunori Kobayashi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    5 Citations (Scopus)

    Abstract

    In this paper, prosody-based attitude recognition and its application to a spoken dialog system are proposed. Paralinguistic information plays a important role in the human communication. We aimed to recognize the user's attitude by prosody, and apply it to a spoken dialog system as para-linguistic information. In order to find important features to recognize the attitude from automatically extracted features, we applied some feature selection methods. Experimental results show the stepwise method, a combination of the forward selection method and the backward selection method, achieved the best recognition rate. Finally, the dialog system using the recognition results as para-linguistic information is shown.

    Original languageEnglish
    Title of host publication8th International Conference on Spoken Language Processing, ICSLP 2004
    PublisherInternational Speech Communication Association
    Pages2841-2844
    Number of pages4
    Publication statusPublished - 2004
    Event8th International Conference on Spoken Language Processing, ICSLP 2004 - Jeju, Jeju Island, Korea, Republic of
    Duration: 2004 Oct 42004 Oct 8

    Other

    Other8th International Conference on Spoken Language Processing, ICSLP 2004
    CountryKorea, Republic of
    CityJeju, Jeju Island
    Period04/10/404/10/8

    ASJC Scopus subject areas

    • Language and Linguistics
    • Linguistics and Language

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  • Cite this

    Fujie, S., Yagi, D., Kikuchi, H., & Kobayashi, T. (2004). Prosody based attitude recognition with feature selection and its application to spoken dialog system as para-linguistic information. In 8th International Conference on Spoken Language Processing, ICSLP 2004 (pp. 2841-2844). International Speech Communication Association.