A data-driven grapheme-to-phoneme conversion method using dynamic contextual converting rules for Korean TTS systems

Authors:
Jinsik Lee;Gary Geunbae Lee
Affiliations:
Intelligent Software Laboratory, Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja-dong, Nam-gu, Pohang 790-784, Republic of Kore ...;Intelligent Software Laboratory, Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja-dong, Nam-gu, Pohang 790-784, Republic of Kore ...
Venue:
Computer Speech and Language
Year:
2009

Citing 4
Cited 0

Progress in speech synthesis

Progress in speech synthesis
Statistical methods for speech recognition

Statistical methods for speech recognition
Morpheme-based grapheme to phoneme conversion using phonetic patterns and morphophonemic connectivity information

ACM Transactions on Asian Language Information Processing (TALIP)
Joint-sequence models for grapheme-to-phoneme conversion

Speech Communication

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Abstract

This paper presents a data-driven Korean grapheme-to-phoneme conversion method including alignment, rule extraction, and rule pruning procedures. Novel rule extraction and pruning techniques are introduced to effectively handle the exceptional pronunciation of speech databases. The performances with the full rules and the reduced rules are 99.22% and 99.11% phoneme level accuracy, respectively. Compared with state-of-the-art previous works, the experimental results show that our method is very promising.