• DocumentCode
    3400708
  • Title

    Using HMMs in audio-to-visual conversion

  • Author

    Rao, R. ; Mersereau, R. ; Chen, T.

  • Author_Institution
    Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA
  • fYear
    1997
  • fDate
    23-25 Jun 1997
  • Firstpage
    19
  • Lastpage
    24
  • Abstract
    One emerging application which exploits the correlation between audio and video is speech driven facial animation. The goal of speech driven facial animation is to synthesize realistic video sequences from acoustic speech. Much of the previous research has implemented this audio to visual conversion strategy with existing techniques such as vector quantization and neural networks. We examine how this conversion process can be accomplished with hidden Markov models
  • Keywords
    audio-visual systems; computer animation; hidden Markov models; speech recognition; video signal processing; HMMs; acoustic speech; audio to visual conversion strategy; conversion process; hidden Markov models; neural networks; realistic video sequences; speech driven facial animation; vector quantization; Facial animation; Hidden Markov models; Image converters; Mouth; Multilayer perceptrons; Signal processing; Speech recognition; Speech synthesis; Streaming media; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Signal Processing, 1997., IEEE First Workshop on
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    0-7803-3780-8
  • Type

    conf

  • DOI
    10.1109/MMSP.1997.602607
  • Filename
    602607
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3400708