C4.5: programs for machine learning
C4.5: programs for machine learning
Regular models of phonological rule systems
Computational Linguistics - Special issue on computational phonology
An introduction to text-to-speech synthesis
An introduction to text-to-speech synthesis
Meta-Learning for Phonemic Annotation of Corpora
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Regular expressions for language engineering
Natural Language Engineering
Data-oriented methods for grapheme-to-phoneme conversion
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
Transducers from rewrite rules with backreferences
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Dialogue act tagging with Transformation-Based Learning
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Inducing probabilistic syllable classes using multivariate clustering
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Diphone-based concatenative speech synthesis systems for arabic language
CSECS'11/MECHANICS'11 Proceedings of the 10th WSEAS international conference on Circuits, Systems, Electronics, Control & Signal Processing, and Proceedings of the 7th WSEAS international conference on Applied and Theoretical Mechanics
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A finite-state method, based on leftmost longestmatch replacement, is presented for segmenting words into graphemes, and for converting graphemes into phonemes. A small set of hand-crafted conversion rules for Dutch achieves a phoneme accuracy of over 93%. The accuracy of the system is further improved by using transformation-based learning. The phoneme accuracy of the best system (using a large rule and a 'lazy' variant of Brill's algoritm), trained on only 40K words, reaches 99%.