• DocumentCode
    2263030
  • Title

    Syllable-level desynchronisation of phonetic features for speech recognition

  • Author

    Kirchhoff, Katrin

  • Author_Institution
    Tech. Fakultat, Bielefeld Univ., Germany
  • Volume
    4
  • fYear
    1996
  • fDate
    3-6 Oct 1996
  • Firstpage
    2274
  • Abstract
    Describes a novel approach to speech recognition which is based on phonetic features as basic recognition units and the delayed synchronisation of these features within a higher-level prosodic domain, viz. the syllable. The object of this approach is to avoid a rigid segmentation of the speech signal as it is usually carried out by standard segment-based recognition systems. The architectural setup of the system is described, as well as evaluation tests carried out on a medium-sized corpus of spontaneous speech (German). Syllable and phoneme recognition results are given and compared to recognition rates obtained by a standard triphone-based HMM recogniser trained and tested on the same data set
  • Keywords
    hidden Markov models; speech recognition; synchronisation; German spontaneous speech corpus; architectural setup; delayed synchronisation; evaluation tests; hidden Markov method; high-level prosodic domain; phoneme recognition; phonetic features; recognition rates; segment-based recognition systems; speech recognition; speech signal segmentation; syllable recognition; syllable-level desynchronisation; training; triphone-based HMM recogniser; Acoustic testing; Computer vision; Context modeling; Delay; Hidden Markov models; Speech recognition; Stochastic processes; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    0-7803-3555-4
  • Type

    conf

  • DOI
    10.1109/ICSLP.1996.607260
  • Filename
    607260