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Modélisation acoustico-phonétique de langues peu dotées : Études phonétiques et travaux de reconnaissance automatique en luxembourgois
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In: Journées d'Etude sur la Parole ; https://hal.archives-ouvertes.fr/hal-01843399 ; Journées d'Etude sur la Parole, Jan 2014, Le Mans, France (2014)
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Speech Alignment and Recognition Experiments for Luxembourgish
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In: Proceedings of the 4th International Workshop on Spoken Language Technologies for Underresourced Languages ; 4th International Workshop on Spoken Language Technologies for Underresourced Languages ; https://hal.archives-ouvertes.fr/hal-01134824 ; 4th International Workshop on Spoken Language Technologies for Underresourced Languages, May 2014, Saint-Petersbourg, Russia. pp.53-60 ; http://www.mica.edu.vn/sltu2014/ (2014)
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A First LVCSR System for Luxembourgish, a Low-Resourced European Language
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In: Human Language Technology Challenges for Computer Science and Linguistics ; https://hal.archives-ouvertes.fr/hal-01135103 ; Zygmunt Vetulani; Joseph Mariani. Human Language Technology Challenges for Computer Science and Linguistics, 8387, Springer International Publishing, pp.479-490, 2014, 5th Language and Technology Conference, LTC 2011, Poznań, Poland, November 25--27, 2011, Revised Selected Papers, 978-3-319-08957-7. ⟨10.1007/978-3-319-08958-4_39⟩ (2014)
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Abstract:
International audience ; Luxembourgish is embedded in a multilingual context on the divide between Romance and Germanic cultures and remains one of Europe’s low-resourced languages. We describe our efforts in building a large vocabulary ASR system for such a “minority” language without resorting to any prior transcribed audio training data. Instead, acoustic models are derived from major European languages. Furthermore, most Luxembourgish written sources include significant parts in other languages. This poses specific challenges to Language Model estimation. Some scientific and technological issues addressed include: (i) how to build acoustic models if no labeled acoustic training data are available for the under-resourced target language? (ii) how to make use of the new system to accelerate resource production for the target language? (iii) how to build a vocabulary and a language model with multilingual written texts? (iv) how to determine the “best” phonemic inventory for ASR? First ASR results illustrate the accuracy of the various sets of monolingual and multilingual acoustic models and what these suggest concerning language typology issues.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; Acoustic modeling; Forced alignment; Germanic languages; Luxembourgish; Multilingual models; Romance languages
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URL: https://doi.org/10.1007/978-3-319-08958-4_39
https://hal.archives-ouvertes.fr/hal-01135103
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