A Noise Robust Multilingual Reference Recogniser Based on Speechdat(II)

نویسندگان

  • Børge Lindberg
  • Finn Tore Johansen
  • Narada D. Warakagoda
  • Gunnar Lehtinen
  • Zdravko Kacic
  • Andrej Zgank
  • Kjell Elenius
  • Giampiero Salvi
چکیده

An important aspect of noise robustness of automatic speech recognisers (ASR) is the proper handling of non-speech acoustic events. The present paper describes further improvements of an already existing reference recogniser towards achieving such kind of robustness. The reference recogniser applied is the COST 249 SpeechDat reference recogniser, which is a fully automatic, language-independent training procedure for building a phonetic recogniser (http://www.telenor.no/fou/prosjekter/taletek/refrec). The reference recogniser relies on the HTK toolkit and a SpeechDat(II) compatible database, and is designed to serve as a reference system in multilingual speech recognition research. The paper describes version 0.96 of the reference recogniser which take into account labelled non-speech acoustic events during training and provides robustness against these during testing. Results are presented on small and medium vocabulary recognition for six languages.

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تاریخ انتشار 2000