• DocumentCode
    2880977
  • Title

    Application of automatic speech recognition in call classification

  • Author

    Das, Sharmistha Sarkar ; Chan, Norman ; Wages, Danny ; Hansen, John H L

  • Author_Institution
    Avaya Labs., 1300 W 120-th Avenue, Westminster, CO 80234, US
  • Volume
    4
  • fYear
    2002
  • fDate
    13-17 May 2002
  • Abstract
    Call classification is the process of characterizing the audio signals encountered when a phone call is placed. The signal can be a live person, an answering machine, a call progress tone (ringback, busy, etc.), a fax modem tone or an announcement message. Call processing system uses the output of the call classifier to perform automated call routing. Traditionally, in-band signaling between communication system endpoints and users are in the form of audible tones. With the advent of technology, these signals have been augmented by synthesized and recorded human speech. A “busy tone”, for example, may be replaced by recorded speech. Traditional call classifiers, which are mainly tone detectors, have become increasingly ineffective. This paper proposes a new generation call classifier employing Automatic Speech Recognition (ASR). Modifications of the ASR paradigm are suggested to incorporate signal recognition, and results presented for two call classifier scenarios.
  • Keywords
    Classification algorithms; Decoding; Energy states; Markov processes; Speech; Speech recognition; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
  • Conference_Location
    Orlando, FL, USA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7402-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2002.5745508
  • Filename
    5745508