• DocumentCode
    2452343
  • Title

    Multichannel speech recognition using distributed microphone signal fusion strategies

  • Author

    Trawicki, Marek B. ; Johnson, Michael T. ; Ji, An ; Osiejuk, Tomasz S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
  • fYear
    2012
  • fDate
    16-18 July 2012
  • Firstpage
    1146
  • Lastpage
    1150
  • Abstract
    Multichannel fusion strategies are presented for the distributed microphone recognition environment, for the task of song-type recognition in a multichannel songbird dataset. The signals are first fused together based on various heuristics, including their amplitudes, variances, physical distance, or squared distance, before passing the enhanced single-channel signal into the speech recognition system. The intensity-weighted fusion strategy achieved the highest overall recognition accuracy of 94.4%. By combining the noisy distributed microphone signals in an intelligent way that is proportional to the information contained in the signals, speech recognition systems can achieve higher recognition accuracies.
  • Keywords
    microphones; speech recognition; distributed microphone signal fusion strategies; multichannel songbird dataset; multichannel speech recognition; noisy distributed microphone signals; song type recognition; Accuracy; Array signal processing; Microphone arrays; Noise measurement; Speech; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Audio, Language and Image Processing (ICALIP), 2012 International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-0173-2
  • Type

    conf

  • DOI
    10.1109/ICALIP.2012.6376789
  • Filename
    6376789