• DocumentCode
    454753
  • Title

    Detecting High Level Dialog Structure Without Lexical Information

  • Author

    Aylett, Matthew P.

  • Author_Institution
    ICSI UC
  • Volume
    1
  • fYear
    2006
  • fDate
    14-19 May 2006
  • Abstract
    The potentially enormous audio resources now available to both organizations, and on the Internet, present a serious challenge to audio browsing technology. In this paper we outline a set of techniques that can be used to determine high level dialog structure without the requirement of resource intensive automatic speech recognition (ASR). Using syllable finding algorithms based on band pass energy together with prosodic feature extraction, we show that a sub-lexical approach to prosodic analysis can outperform results based on ASR and even those based on a word alignment which requires a complete transcription. We consider how these techniques could be integrated into ASR technology and suggest a framework for extending this type of sub-lexical prosodic analysis
  • Keywords
    audio signal processing; signal detection; speech recognition; audio browsing technology; automatic speech recognition; band pass energy; high level dialog structure; prosodic feature extraction; sub-lexical prosodic analysis; syllable finding algorithms; Algorithm design and analysis; Automatic speech recognition; Character recognition; Continuous-stirred tank reactor; Enterprise resource planning; Feature extraction; Humans; Internet; Natural languages; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
  • Conference_Location
    Toulouse
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0469-X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2006.1660252
  • Filename
    1660252