• DocumentCode
    672346
  • Title

    The second ‘CHiME’ speech separation and recognition challenge: An overview of challenge systems and outcomes

  • Author

    Vincent, Emmanuel ; Barker, J. ; Watanabe, Shigetaka ; Le Roux, Jonathan ; Nesta, Francesco ; Matassoni, Marco

  • Author_Institution
    Inria, Villers-lès-Nancy, France
  • fYear
    2013
  • fDate
    8-12 Dec. 2013
  • Firstpage
    162
  • Lastpage
    167
  • Abstract
    Distant-microphone automatic speech recognition (ASR) remains a challenging goal in everyday environments involving multiple background sources and reverberation. This paper reports on the results of the 2nd `CHiME´ Challenge, an initiative designed to analyse and evaluate the performance of ASR systems in a real-world domestic environment. We discuss the rationale for the challenge and provide a summary of the datasets, tasks and baseline systems. The paper overviews the systems that were entered for the two challenge tracks: small-vocabulary with moving talker and medium-vocabulary with stationary talker. We present a summary of the challenge findings including novel results produced by challenge system combination. Possible directions for future challenges are discussed.
  • Keywords
    Gaussian processes; hidden Markov models; mixture models; speech recognition; ASR systems; CHiME speech separation and recognition challenge; GMM; Gaussian mixture model; HMM; distant-microphone automatic speech recognition; hidden Markov model; medium-vocabulary; moving talker; real-world domestic environment; small-vocabulary; stationary talker; Hidden Markov models; Noise measurement; Signal to noise ratio; Speech; Training; Vocabulary; ‘CHiME’ Challenge; Noise-robust ASR;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Speech Recognition and Understanding (ASRU), 2013 IEEE Workshop on
  • Conference_Location
    Olomouc
  • Type

    conf

  • DOI
    10.1109/ASRU.2013.6707723
  • Filename
    6707723