• DocumentCode
    113732
  • Title

    Noise management in mobile speech based health tools

  • Author

    Yadav, Nikhil ; Daudet, Louis ; Poellabauer, Christian ; Flynn, Patrick

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Notre Dame, Notre Dame, IN, USA
  • fYear
    2014
  • fDate
    8-10 Oct. 2014
  • Firstpage
    335
  • Lastpage
    338
  • Abstract
    Noise impacts speech recognition and processing capabilities on mobile devices. The Signal-to-Noise Ratio (SNR) is a good indicator of noise in the acoustic environment where the speech is recorded and processed. In this paper, SNR and its impact on speech recognition and processing capabilities on a mobile device are studied for a relatively small text corpus of 50 words. The speech recognition accuracy is quantified using a word accuracy metric for different levels of SNR. Future mobile health tools that detect speech disorders caused by illness can benefit from this study and the resulting tool developed to give appropriate feedback to a user about their acoustic environment. Corrective measures can be suggested based on this to alleviate the potential problem, e.g., adjusting a microphone or relocating to a quieter environment.
  • Keywords
    health care; medical disorders; microphones; smart phones; speech; speech recognition; telemedicine; acoustic environment; microphone; mobile devices; mobile health tools; mobile speech; noise management; signal-to-noise ratio; speech disorder detector; speech processing capabilities; speech recognition accuracy; word accuracy; Accuracy; Acoustics; Mobile communication; Signal to noise ratio; Speech; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Healthcare Innovation Conference (HIC), 2014 IEEE
  • Conference_Location
    Seattle, WA
  • Type

    conf

  • DOI
    10.1109/HIC.2014.7038943
  • Filename
    7038943