From text to speech: the MITalk system
From text to speech: the MITalk system
C4.5: programs for machine learning
C4.5: programs for machine learning
The acquisition of stress: a data-oriented approach
Computational Linguistics - Special issue on computational phonology
Progress in speech synthesis
Machine Learning
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Grapheme-to-phoneme conversion based on a fast TBL algorithm in mandarin TTS systems
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
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In this paper, we present a new phrase break prediction architecture that integrates probabilistic approach with decision-tree based error correction. The probabilistic method alone usually suffers from performance degradation due to inherent data sparseness problems and it only covers a limited range of contextual information. Moreover, the module can not utilize the selective morpheme tag and relative distance to the other phrase breaks. The decision-tree based error correction was tightly integrated to overcome these limitations.The initially phrase break tagged morpheme sequence is corrected with the error correcting decision tree which was induced by C4.5 from the correctly tagged corpus with the output of the probabilistic predictor. The decision tree-based post error correction provided improved results even with the phrase break predictor that has poor initial performance. Moreover, the system can be flexibly tuned to new corpus without massive retraining.