Adaptation Methods for Non-native Speech

نویسندگان

  • Laura May
  • Alex Waibel
چکیده

LVCSR performance is consistently poor on low-pro ciency non-native speech. While gains from speaker adaptation can often bring recognizer performance on highpro ciency non-native speakers close to that seen for native speakers [12], recognition for lower-pro ciency speakers remains low even after individual speaker adaptation [2]. The challenge for accent adaptation is to maximize recognizer performance without collecting large amounts of acoustic data for each native-language/targetlanguage pair. In this paper, we focus on adaptation for lower-pro ciency speakers, exploring how acoustic data from up to 15 adaptation speakers can be put to its most e ective use.

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تاریخ انتشار 2001