Grapheme-to-Phoneme (G2P) conversion is the task of predicting the pronunciation of a word given its graphemic or written form. Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016) The result shows that CRF, PBSMT and WFST approaches are the best performing methods for G2P conversion on Myanmar language.",Ĭomparison of Grapheme-to-Phoneme Conversion Methods on a Myanmar Pronunciation Dictionary
#Myanmar pronunciation manual#
The G2P bootstrapping experimental results were measured with both automatic phoneme error rate (PER) calculation and also manual checking in terms of voiced/unvoiced, tones, consonant and vowel errors.
In this paper, we evaluate seven G2P conversion approaches: Adaptive Regularization of Weight Vectors (AROW) based structured learning (S-AROW), Conditional Random Field (CRF), Joint-sequence models (JSM), phrase-based statistical machine translation (PBSMT), Recurrent Neural Network (RNN), Support Vector Machine (SVM) based point-wise classification, Weighted Finite-state Transducers (WFST) on a manually tagged Myanmar phoneme dictionary. It is a highly important part of both automatic speech recognition (ASR) and text-to-speech (TTS) systems.
Publisher = "The COLING 2016 Organizing Committee",Ībstract = "Grapheme-to-Phoneme (G2P) conversion is the task of predicting the pronunciation of a word given its graphemic or written form.
#Myanmar pronunciation mods#
| WSSANLP SIG: Publisher: The COLING 2016 Organizing Committee Note: Pages: 11–22 Language: URL: DOI: Bibkey: kyaw-thu-etal-2016-comparison Copy Citation: BibTeX MODS XML Endnote More options… PDF: = "Comparison of Grapheme-to-Phoneme Conversion Methods on a 2016)",
Anthology ID: W16-3702 Volume: Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016) Month: December Year: 2016 Address: Osaka, Japan Venues: WS The result shows that CRF, PBSMT and WFST approaches are the best performing methods for G2P conversion on Myanmar language. Abstract Grapheme-to-Phoneme (G2P) conversion is the task of predicting the pronunciation of a word given its graphemic or written form.