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FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task ...
Tang, Yun; Gong, Hongyu; Li, Xian. - : arXiv, 2021
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CCMatrix: Mining Billions of High-Quality Parallel Sentences on the Web ...
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Textless Speech-to-Speech Translation on Real Data ...
Abstract: We present a textless speech-to-speech translation (S2ST) system that can translate speech from one language into another language and can be built without the need of any text data. Different from existing work in the literature, we tackle the challenge in modeling multi-speaker target speech and train the systems with real-world S2ST data. The key to our approach is a self-supervised unit-based speech normalization technique, which finetunes a pre-trained speech encoder with paired audios from multiple speakers and a single reference speaker to reduce the variations due to accents, while preserving the lexical content. With only 10 minutes of paired data for speech normalization, we obtain on average 3.2 BLEU gain when training the S2ST model on the \vp~S2ST dataset, compared to a baseline trained on un-normalized speech target. We also incorporate automatically mined S2ST data and show an additional 2.0 BLEU gain. To our knowledge, we are the first to establish a textless S2ST technique that can be ...
Keyword: Artificial Intelligence cs.AI; Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG
URL: https://dx.doi.org/10.48550/arxiv.2112.08352
https://arxiv.org/abs/2112.08352
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4
Beyond English-Centric Multilingual Machine Translation ...
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5
WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia ...
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6
MLQA: Evaluating Cross-lingual Extractive Question Answering ...
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7
CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB ...
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8
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 597-610 (2019) (2019)
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9
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond ...
Artetxe, Mikel; Schwenk, Holger. - : arXiv, 2018
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10
XNLI: Evaluating Cross-lingual Sentence Representations ...
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11
Filtering and Mining Parallel Data in a Joint Multilingual Space ...
Schwenk, Holger. - : arXiv, 2018
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12
A Corpus for Multilingual Document Classification in Eight Languages ...
Schwenk, Holger; Li, Xian. - : arXiv, 2018
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13
Very Deep Convolutional Networks for Text Classification
In: European Chapter of the Association for Computational Linguistics EACL'17 ; https://hal.archives-ouvertes.fr/hal-01454940 ; European Chapter of the Association for Computational Linguistics EACL'17, 2017, Valencia, Spain (2017)
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14
Learning Joint Multilingual Sentence Representations with Neural Machine Translation ...
Schwenk, Holger; Douze, Matthijs. - : arXiv, 2017
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15
OCR Error Correction Using Statistical Machine Translation
In: 16th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2015). ; https://hal.archives-ouvertes.fr/hal-01433200 ; 16th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2015)., 2015, Cairo, Egypt (2015)
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16
Continuous Adaptation to User Feedback for Statistical Machine Translation
In: North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2015) ; https://hal.archives-ouvertes.fr/hal-01454944 ; North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2015), 2015, Denver (Colorado, USA), Unknown Region (2015)
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17
Continuous adaptation to user feedback for statistical machine translation
In: 1001 ; 1005 (2015)
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18
Translation project adaptation for MT-enhanced computer assisted translation [<Journal>]
Cettolo, Mauro [Verfasser]; Bertoldi, Nicola [Verfasser]; Federico, Marcello [Verfasser].
DNB Subject Category Language
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19
Translation project adaptation for MT-enhanced computer assisted translation
In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 28 (2014) 2, 127-150
OLC Linguistik
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20
Translation project adaptation for MT-enhanced computer assisted translation
In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-01157893 ; Machine Translation, Springer Verlag, 2014, Machine Translation Journal, 28, pp.127. &#x27E8;10.1007/s10590-014-9152-1&#x27E9; (2014)
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