Unsupervised accent classification for deep data fusion of accent and language information

  title={Unsupervised accent classification for deep data fusion of accent and language information},
  author={John H. L. Hansen and Gang Liu},
  journal={Speech Communication},
Automatic Dialect Identification (DID) has recently gained substantial interest in the speech processing community. Studies have shown that the variation in speech due to dialect is a factor which significantly impacts speech system performance. Dialects differ in various ways such as acoustic traits (phonetic realization of vowels and consonants, rhythmical characteristics, prosody) and content based word selection (grammar, vocabulary, phonetic distribution, lexical distribution, semantics… CONTINUE READING
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