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- W61409596 abstract "Phonetization is a crucial step for oral document processing. In this paper, a new letter-to-phoneme conversion approach is pro- posed; it is automatic, simple, portable and efficient. It relies on a machine learning technique initially developed for translit- eration and translation; the system infers rewriting rules from examples of words with their phonetic representations. This approach is evaluated in the framework of the Pronalsyl Pas- cal challenge, which includes several datasets on different lan- guages. The obtained results equal or outperform those of the best known systems. Moreover, thanks to the simplicity of our technique, the inference time of our approach is much lower than those of the best performing state-of-the-art systems. Index Terms : phonetization, inference of rewriting rules, phonemization, grapheme-to-phoneme, Pronalsyl Challenge." @default.
- W61409596 created "2016-06-24" @default.
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- W61409596 date "2009-09-06" @default.
- W61409596 modified "2023-09-26" @default.
- W61409596 title "Letter-to-phoneme conversion by inference of rewriting rules" @default.
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- W61409596 doi "https://doi.org/10.21437/interspeech.2009-406" @default.
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