Context-dependent acoustic modeling using graphemes for large vocabulary speech recognition
暂无分享,去创建一个
[1] Robert L. Mercer,et al. An information theoretic approach to the automatic determination of phonemic baseforms , 1984, ICASSP.
[2] Lalit R. Bahl,et al. Continuous parameter acoustic processing for recognition of a natural speech corpus , 1981, ICASSP.
[3] Franz Kummert,et al. Grapheme based speech recognition for large vocabularies , 2000, INTERSPEECH.
[4] K. Kohler. Einführung in die Phonetik des Deutschen , 1981 .
[5] Hermann Ney,et al. The RWTH large vocabulary continuous speech recognition system , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[6] Hermann Ney,et al. State tying for context dependent phoneme models , 1997, EUROSPEECH.
[7] Hsiao-Wuen Hon,et al. Vocabulary-independent speech recognition: the Vocind System , 1992 .
[8] Heinrich Niemann,et al. Automatic speech recognition without phonemes , 1993, EUROSPEECH.
[9] Richard M. Stern,et al. Automatic generation of phone sets and lexical transcriptions , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[10] Hermann Ney,et al. Automatic question generation for decision tree based state tying , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[11] Juha Häkkinen,et al. Decision tree based text-to-phoneme mapping for speech recognition , 2000, INTERSPEECH.
[12] Paul Mermelstein,et al. Experiments in syllable-based recognition of continuous speech , 1980, ICASSP.
[13] Kari Torkkola. An efficient way to learn English grapheme-to-phoneme rules automatically , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.