• DocumentCode
    148073
  • Title

    Feature enhancement for robust speech recognition on smartphones with dual-microphone

  • Author

    Lopez-Espejo, Ivan ; Gomez, Angel M. ; Gonzalez, Jose A. ; Peinado, Antonio M.

  • Author_Institution
    Dept. of Signal Theor., Univ. of Granada, Granada, Spain
  • fYear
    2014
  • fDate
    1-5 Sept. 2014
  • Firstpage
    21
  • Lastpage
    25
  • Abstract
    Latest smartphones often have more than one microphone in order to perform noise reduction. Although research on speech enhancement is already exploiting this new feature, robust speech recognition is not still benefiting from it. In this paper we propose two feature enhancement methods especially developed for the case of a smartphone with a dual-microphone operating in an adverse acoustic environment. In order to test these proposals, we have already developed a new experimental framework which includes a noisy speech database (based on AURORA2) which emulates the acquisition of dual-microphone data. Our experimental results show a clear improvement in terms of word accuracy in comparison with both using a power level difference-based speech enhancement algorithm and a single channel feature compensation approach.
  • Keywords
    microphones; smart phones; speech enhancement; speech recognition; AURORA2; adverse acoustic environment; dual-microphone data acquisition; dual-microphone smartphone; feature enhancement; feature enhancement method; noise reduction; noisy speech database; power level difference-based speech enhancement algorithm; robust speech recognition; single-channel feature compensation approach; speech enhancement; word accuracy; Microphones; Noise; Noise measurement; Smart phones; Speech; Speech enhancement; Speech recognition; AURORA2-2C; Dual-microphone; Feature enhancement; Robust speech recognition; Smartphone;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
  • Conference_Location
    Lisbon
  • Type

    conf

  • Filename
    6951963