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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 15 of 15 1 XTREME-S: Evaluating Cross-lingual Speech Representations ... Conneau, Alexis; Bapna, Ankur; Zhang, Yu. - : arXiv, 2022 BASE Show details 2 mSLAM: Massively multilingual joint pre-training for speech and text ... Bapna, Ankur; Cherry, Colin; Zhang, Yu. - : arXiv, 2022 BASE Show details 3 Larger-Scale Transformers for Multilingual Masked Language Modeling ... Goyal, Naman; Du, Jingfei; Ott, Myle. - : arXiv, 2021 BASE Show details 4 Multilingual Speech Translation from Efficient Finetuning of Pretrained Models ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Auli, Michael; Baevski, Alexei. - : Underline Science Inc., 2021 BASE Show details 5 Unsupervised Cross-lingual Representation Learning for Speech Recognition ... Conneau, Alexis; Baevski, Alexei; Collobert, Ronan; Mohamed, Abdelrahman; Auli, Michael. - : arXiv, 2020 Abstract: This paper presents XLSR which learns cross-lingual speech representations by pretraining a single model from the raw waveform of speech in multiple languages. We build on wav2vec 2.0 which is trained by solving a contrastive task over masked latent speech representations and jointly learns a quantization of the latents shared across languages. The resulting model is fine-tuned on labeled data and experiments show that cross-lingual pretraining significantly outperforms monolingual pretraining. On the CommonVoice benchmark, XLSR shows a relative phoneme error rate reduction of 72% compared to the best known results. On BABEL, our approach improves word error rate by 16% relative compared to a comparable system. Our approach enables a single multilingual speech recognition model which is competitive to strong individual models. Analysis shows that the latent discrete speech representations are shared across languages with increased sharing for related languages. We hope to catalyze research in low-resource ... Keyword: 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; Sound cs.SD URL: https://arxiv.org/abs/2006.13979 https://dx.doi.org/10.48550/arxiv.2006.13979 BASE Hide details 6 Multilingual Speech Translation with Efficient Finetuning of Pretrained Models ... Li, Xian; Wang, Changhan; Tang, Yun. - : arXiv, 2020 BASE Show details 7 Unsupervised Cross-lingual Representation Learning at Scale ... Conneau, Alexis; Khandelwal, Kartikay; Goyal, Naman. - : arXiv, 2019 BASE Show details 8 Emerging Cross-lingual Structure in Pretrained Language Models ... Wu, Shijie; Conneau, Alexis; Li, Haoran. - : arXiv, 2019 BASE Show details 9 Specializing distributional vectors of all words for lexical entailment Ponti, Edoardo Maria; Kamath, Aishwarya; Pfeiffer, Jonas. - : Association for Computational Linguistics, 2019 BASE Show details 10 What you can cram into a single \$&!#* vector: Probing sentence embeddings for linguistic properties Conneau, Alexis; Kruszewski, German; Lample, Guillaume... In: ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01898412 ; ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Jul 2018, Melbourne, Australia. pp.2126-2136 (2018) BASE Show details 11 XNLI: Evaluating Cross-lingual Sentence Representations ... Conneau, Alexis; Lample, Guillaume; Rinott, Ruty. - : arXiv, 2018 BASE Show details 12 What you can cram into a single vector: Probing sentence embeddings for linguistic properties ... Conneau, Alexis; Kruszewski, German; Lample, Guillaume. - : arXiv, 2018 BASE Show details 13 Very Deep Convolutional Networks for Text Classification Conneau, Alexis; Schwenk, Holger; Barrault, Loïc... 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) BASE Show details 14 Word Translation Without Parallel Data ... Conneau, Alexis; Lample, Guillaume; Ranzato, Marc'Aurelio. - : arXiv, 2017 BASE Show details 15 What you can cram into a single $&!#* vector: probing sentence embeddings for linguistic properties Kruszewski, German; Barrault, Loïc; Baroni, Marco. - : ACL (Association for Computational Linguistics) BASE Show details

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