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

    27 Citations (Scopus)
    240 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