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SMT-based ASR domain adaptation methods for under-resourced languages: Application to Romanian.

, , , and . Speech Commun., (2014)

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Data selection for compact adapted SMT models., and . AMTA, page 301-314. Association for Machine Translation in the Americas, (2014)Models of Visually Grounded Speech Signal Pay Attention to Nouns: A Bilingual Experiment on English and Japanese., , and . ICASSP, page 8618-8622. IEEE, (2019)GSM speech coding and speaker recognition., , , , and . ICASSP, page 1085-1088. IEEE, (2000)Automatic Identification of Arabic Dialects., , and . LREC, European Language Resources Association, (2010)Using closely-related language to build an ASR for a very under-resourced language: Iban., , , and . O-COCOSDA, page 1-5. IEEE, (2014)Investigating the role of machine translated text in ASR domain adaptation: Unsupervised and semi-supervised methods., , , and . ASRU, page 260-265. IEEE, (2011)Unwritten languages demand attention too! Word discovery with encoder-decoder models., , , and . ASRU, page 458-465. IEEE, (2017)Actes de la conférence conjointe JEP-TALN-RECITAL 2012, volume 4: conférences invités, , , , and . ATALA/AFCP, (2012)Encoding Sentence Position in Context-Aware Neural Machine Translation with Concatenation., , and . CoRR, (2023)An Empirical Study of End-To-End Simultaneous Speech Translation Decoding Strategies., , and . ICASSP, page 7528-7532. IEEE, (2021)