Cite (Informal): Phonetic Normalization for Machine Translation of User Generated Content (Rosales Núñez et al., WNUT 2019) Copy Citation: BibTeX Markdown MODS XML Endnote More options… PDF: = "Phonetic Normalization for Machine Translation of User Generated Content",Īuthor = "Rosales N Carlos andīooktitle = "Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019)", Association for Computational Linguistics. In Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), pages 407–416, Hong Kong, China. Phonetic Normalization for Machine Translation of User Generated Content. Anthology ID: D19-5553 Volume: Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019) Month: November Year: 2019 Address: Hong Kong, China Venue: WNUT SIG: Publisher: Association for Computational Linguistics Note: Pages: 407–416 Language: URL: DOI: 10.18653/v1/D19-5553 Bibkey: rosales-nunez-etal-2019-phonetic Cite (ACL): José Carlos Rosales Núñez, Djamé Seddah, and Guillaume Wisniewski. Compare to using other phonetizers, our method boosts a transformer-based machine translation system on UGC. These potential corrections are then encoded in a lattice and ranked using a language model to output the most probable corrected phrase. Our method leverages on the fact that some errors are due to confusion induced by words with similar pronunciation which can be corrected using a phonetic look-up table to produce normalization candidates. In this way, we intend to correct grammar, vocabulary and accentuation errors often present in noisy UGC corpora. In order to do so, we have implemented a character-based neural model phonetizer to produce IPA pronunciations of words. Abstract We present an approach to correct noisy User Generated Content (UGC) in French aiming to produce a pretreatement pipeline to improve Machine Translation for this kind of non-canonical corpora.
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