• DocumentCode
    1185931
  • Title

    Pervasive speech recognition

  • Author

    Alewine, Neal ; Ruback, Harvey ; Deligne, Sabine

  • Volume
    3
  • Issue
    4
  • fYear
    2004
  • Firstpage
    78
  • Lastpage
    81
  • Abstract
    As mobile computing devices grow smaller and as in-car computing platforms become more common, we must augment traditional methods of human-computer interaction. Although speech interfaces have existed for years, the constrained system resources of pervasive devices, such as limited memory and processing capabilities, present new challenges. We provide an overview of embedded automatic speech recognition (ASR) on the pervasive device and discuss its ability to help us develop pervasive applications that meet today´s marketplace needs. ASR recognizes spoken words and phrases. State-of-the-art ASR uses a phoneme-based approach for speech modeling: it gives each phoneme (or elementary speech sound) in the language under consideration a statistical representation expressing its acoustic properties.
  • Keywords
    human computer interaction; natural language interfaces; speech processing; speech recognition; speech-based user interfaces; ubiquitous computing; acoustic properties; automatic speecb recognition; constrained system resources; elementary speech sound; embedded automatic speech recognition; human-computer interaction; in-car computing platforms; mobile computing devices; pervasive speech recognition; phoneme-based approach; speech modeling; spoken word recognition; statistical representation; Acoustic measurements; Books; Computational modeling; Decoding; Fluid flow measurement; Hidden Markov models; Loudspeakers; Resource management; Speech recognition; Viterbi algorithm; ASR; automatic speech recognition;
  • fLanguage
    English
  • Journal_Title
    Pervasive Computing, IEEE
  • Publisher
    ieee
  • ISSN
    1536-1268
  • Type

    jour

  • DOI
    10.1109/MPRV.2004.16
  • Filename
    1369165