• DocumentCode
    2181465
  • Title

    Experiments in context-independent recognition of non-lexical ‘yes’ or ‘no’ responses

  • Author

    Sundaram, Shiva ; Schleicher, Robert ; Diehl, Nathalie

  • Author_Institution
    Deutsche Telekom Labs., Berlin, Germany
  • fYear
    2011
  • fDate
    22-27 May 2011
  • Firstpage
    5696
  • Lastpage
    5699
  • Abstract
    We present our experiments in context-free recognition of non-lexical responses. Non-lexical verbal responses such as mmm-hmm or uh-huh are used by listeners to signal confirmation, uncertainty in understanding, agreement or disagreement in speech-based interaction between humans. Correct recognition of these utterances by speech interfaces can lead to a more natural interaction paradigm with computers. We present our study on both human and automatic recognition of positive (yes) and negative (no) non-lexical utterances. Approximately 3000 isolated utterances from 26 German native speakers were collected in a human-human spoken interaction setting. Our experiments indicate that human recognition accuracy is close to 99% and up to 90% accuracy can be obtained by standard automatic recognition techniques.
  • Keywords
    human computer interaction; natural languages; speech recognition; German native speakers; automatic recognition techniques; context-free recognition; context-independent recognition; human-human spoken interaction; nonlexical responses; signal confirmation; speech interfaces; speech-based interaction; Cepstral analysis; Computers; Feature extraction; Hidden Markov models; Humans; Speech; Speech recognition; Speech interfaces; automatic recognition; back-channel responses; feature extraction; human-computer interaction; interjections; non-lexical responses;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • Conference_Location
    Prague
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5947653
  • Filename
    5947653