• DocumentCode
    3132578
  • Title

    Frame-based phonotactic Language Identification

  • Author

    Han, Ki Jin ; Pelecanos, Jason

  • Author_Institution
    IBM T. J. Watson Res. Center, Yorktown Heights, NY, USA
  • fYear
    2012
  • fDate
    2-5 Dec. 2012
  • Firstpage
    303
  • Lastpage
    306
  • Abstract
    This paper describes a frame-based phonotactic Language Identification (LID) system, which was used for the LID evaluation of the Robust Automatic Transcription of Speech (RATS) program by the Defense Advanced Research Projects Agency (DARPA). The proposed approach utilizes features derived from frame-level phone log-likelihoods from a phone recognizer. It is an attempt to capture not only phone sequence information but also short-term timing information for phone N-gram events, which is lacking in conventional phonotactic LID systems that simply count phone N-gram events. Based on this new method, we achieved 26% relative improvement in terms of Cavg for the RATS LID evaluation data compared to phone N-gram counts modeling. We also observed that it had a significant impact on score combination with our best acoustic system based on Mel-Frequency Cepstral Coefficients (MFCCs).
  • Keywords
    military computing; natural language processing; speech recognition; DARPA; Defense Advanced Research Projects Agency; MFCC; N-gram count modeling; RATS LID evaluation data; acoustic system; frame-based phonotactic language identification; frame-level phone log likelihoods; mel-frequency cepstral coefficients; phone N-gram events; phone recognizer; phone sequence information; robust automatic transcription; short-term timing information; speech program; Acoustics; Principal component analysis; Rats; Speech; Support vector machines; Timing; Vectors; DARPA RATS; language identification; phone event modeling with timing information; phonotactic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spoken Language Technology Workshop (SLT), 2012 IEEE
  • Conference_Location
    Miami, FL
  • Print_ISBN
    978-1-4673-5125-6
  • Electronic_ISBN
    978-1-4673-5124-9
  • Type

    conf

  • DOI
    10.1109/SLT.2012.6424240
  • Filename
    6424240