Automatic training of phoneme dictionary based on mutual information criterion

Shigeki Okawa, Tetsunori Kobayashi, Katsuhiko Shirai

研究成果: Conference article査読

2 被引用数 (Scopus)

抄録

Proposes an automatic training mechanism for phoneme recognition using labelless speech data under the condition that only its orthographical phonemic symbol sequence is given. For the purpose of obtaining better recognition performance the authors attempt to realize an automatic labeling procedure based on a phoneme classification method by mutual information criterion. By iterative training of a phoneme dictionary for a large amount of speech data, one can investigate the performance and convergence properties of the dictionary. From experimental results, the percent correct of the labeling is over 98% after three iterations, and for the phoneme recognition, a very high accuracy is also obtained.

本文言語English
論文番号389310
ページ(範囲)I241-I244
ジャーナルICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
1
DOI
出版ステータスPublished - 1994
イベントProceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing. Part 2 (of 6) - Adelaide, Aust
継続期間: 1994 4 191994 4 22

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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