Dialogue-act tagging using smart feature selection: results on multiple corpora

Daan Verbree, R.J. Rienks, Dirk K.J. Heylen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    26 Citations (Scopus)
    159 Downloads (Pure)

    Abstract

    This paper presents an overview of our on-going work on dialogueact classification. Results are presented on the ICSI, Switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27%, 65.68% and 59.76%, respectively. We introduce a smart compression technique for feature selection and compare the performance from a subset of the AMI transcriptions with AMI-ASR output for the same subset.
    Original languageUndefined
    Title of host publicationFirst International IEEE Workshop on Spoken Language Technology SLT 2006
    EditorsB. Raorke
    Place of PublicationPalm Beach
    PublisherIEEE Computer Society
    Pages70-73
    Number of pages4
    ISBN (Print)1-4244-0873-3
    DOIs
    Publication statusPublished - Dec 2006

    Publication series

    Name
    PublisherIEEE Computer Society
    Number10

    Keywords

    • EC Grant Agreement nr.: FP6/506811
    • EWI-9501
    • IR-67003
    • METIS-237662
    • HMI-CI: Computational Intelligence

    Cite this

    Verbree, D., Rienks, R. J., & Heylen, D. K. J. (2006). Dialogue-act tagging using smart feature selection: results on multiple corpora. In B. Raorke (Ed.), First International IEEE Workshop on Spoken Language Technology SLT 2006 (pp. 70-73). Palm Beach: IEEE Computer Society. https://doi.org/10.1109/SLT.2006.326819
    Verbree, Daan ; Rienks, R.J. ; Heylen, Dirk K.J. / Dialogue-act tagging using smart feature selection: results on multiple corpora. First International IEEE Workshop on Spoken Language Technology SLT 2006. editor / B. Raorke. Palm Beach : IEEE Computer Society, 2006. pp. 70-73
    @inproceedings{c2a7d4f29d144c70b1b9c31b7b43b9b3,
    title = "Dialogue-act tagging using smart feature selection: results on multiple corpora",
    abstract = "This paper presents an overview of our on-going work on dialogueact classification. Results are presented on the ICSI, Switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27{\%}, 65.68{\%} and 59.76{\%}, respectively. We introduce a smart compression technique for feature selection and compare the performance from a subset of the AMI transcriptions with AMI-ASR output for the same subset.",
    keywords = "EC Grant Agreement nr.: FP6/506811, EWI-9501, IR-67003, METIS-237662, HMI-CI: Computational Intelligence",
    author = "Daan Verbree and R.J. Rienks and Heylen, {Dirk K.J.}",
    year = "2006",
    month = "12",
    doi = "10.1109/SLT.2006.326819",
    language = "Undefined",
    isbn = "1-4244-0873-3",
    publisher = "IEEE Computer Society",
    number = "10",
    pages = "70--73",
    editor = "B. Raorke",
    booktitle = "First International IEEE Workshop on Spoken Language Technology SLT 2006",
    address = "United States",

    }

    Verbree, D, Rienks, RJ & Heylen, DKJ 2006, Dialogue-act tagging using smart feature selection: results on multiple corpora. in B Raorke (ed.), First International IEEE Workshop on Spoken Language Technology SLT 2006. IEEE Computer Society, Palm Beach, pp. 70-73. https://doi.org/10.1109/SLT.2006.326819

    Dialogue-act tagging using smart feature selection: results on multiple corpora. / Verbree, Daan; Rienks, R.J.; Heylen, Dirk K.J.

    First International IEEE Workshop on Spoken Language Technology SLT 2006. ed. / B. Raorke. Palm Beach : IEEE Computer Society, 2006. p. 70-73.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    T1 - Dialogue-act tagging using smart feature selection: results on multiple corpora

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    AU - Rienks, R.J.

    AU - Heylen, Dirk K.J.

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    Y1 - 2006/12

    N2 - This paper presents an overview of our on-going work on dialogueact classification. Results are presented on the ICSI, Switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27%, 65.68% and 59.76%, respectively. We introduce a smart compression technique for feature selection and compare the performance from a subset of the AMI transcriptions with AMI-ASR output for the same subset.

    AB - This paper presents an overview of our on-going work on dialogueact classification. Results are presented on the ICSI, Switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27%, 65.68% and 59.76%, respectively. We introduce a smart compression technique for feature selection and compare the performance from a subset of the AMI transcriptions with AMI-ASR output for the same subset.

    KW - EC Grant Agreement nr.: FP6/506811

    KW - EWI-9501

    KW - IR-67003

    KW - METIS-237662

    KW - HMI-CI: Computational Intelligence

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    DO - 10.1109/SLT.2006.326819

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    BT - First International IEEE Workshop on Spoken Language Technology SLT 2006

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    Verbree D, Rienks RJ, Heylen DKJ. Dialogue-act tagging using smart feature selection: results on multiple corpora. In Raorke B, editor, First International IEEE Workshop on Spoken Language Technology SLT 2006. Palm Beach: IEEE Computer Society. 2006. p. 70-73 https://doi.org/10.1109/SLT.2006.326819