• DocumentCode
    3752219
  • Title

    On a robust ASR based on complex AR speech analysis

  • Author

    Keita Higa;Keiichi Funaki

  • Author_Institution
    Graduate School of Science and Engineering, University of the Ryukyus, Okinawa, Japan
  • fYear
    2015
  • Firstpage
    1232
  • Lastpage
    1235
  • Abstract
    The advanced front-end (AFE) for automatic speech recognition (ASR) was standardized by the European Telecommunications Standards Institute (ETSI). The AFE provides speech enhancement realized by an iterative Wiener filter (IWF) in which a smoothed FFT spectrum over adjacent frames is used to design the filter. We have previously proposed robust time-varying complex AR (TV-CAR) speech analysis and evaluated the performance of speech processing such as F0 estimation and speech enhancement. TV-CAR analysis can estimate more accurate spectrum than FFT, especially in low frequencies because of the nature of the analytic signal. In addition, the TV-CAR can estimate more accurate speech spectrum against additive noise. In this paper, the time-invariant version of wide-band TV-CAR analysis is introduced to the IWF in the AFE and is evaluated using the CENSREC-2 database.
  • Keywords
    "Speech","Speech enhancement","Speech recognition","Additive noise","Robustness","Frequency estimation","Hidden Markov models"
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2015 Asia-Pacific
  • Type

    conf

  • DOI
    10.1109/APSIPA.2015.7415470
  • Filename
    7415470