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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 – 9 of 9 1 XTREME-S: Evaluating Cross-lingual Speech Representations ... Conneau, Alexis; Bapna, Ankur; Zhang, Yu. - : arXiv, 2022 BASE Show details 2 Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training ... Sanabria, Ramon; Hsu, Wei-Ning; Baevski, Alexei. - : arXiv, 2022 BASE Show details 3 Simple and Effective Unsupervised Speech Synthesis ... Liu, Alexander H.; Lai, Cheng-I Jeff; Hsu, Wei-Ning. - : arXiv, 2022 BASE Show details 4 Simple and Effective Zero-shot Cross-lingual Phoneme Recognition ... Xu, Qiantong; Baevski, Alexei; Auli, Michael. - : arXiv, 2021 BASE Show details 5 Discriminative Reranking for Neural Machine Translation ... 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; Lee, Ann. - : Underline Science Inc., 2021 BASE Show details 6 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; Conneau, Alexis; Li, Xian; Pino, Juan; Tang, Yuqing; Tang, Yun; Tran, Chau; Wang, Changhan. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.68 Abstract: We present a simple yet effective approach to build multilingual speech-to-text (ST) translation through efficient transfer learning from a pretrained speech encoder and text decoder. Our key finding is that a minimalistic LNA (LayerNorm and Attention) finetuning can achieve zero-shot crosslingual and cross-modality transfer ability by only finetuning 10~50% of the pretrained parameters. This effectively leverages large pretrained models at low training cost such as wav2vec 2.0 for acoustic modeling, and mBART for multilingual text generation. This sets a new state-of-the-art for 36 translation directions (and surpassing cascaded ST for 26 of them) on the large-scale multilingual ST benchmark CoVoST 2 (+6.4 BLEU on average for En-X directions and +6.7 BLEU for X-En directions). Our approach demonstrates strong zero-shot performance in a many-to-many multilingual model (+5.6 BLEU on average across 28 non-English directions), making it an ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://dx.doi.org/10.48448/z2bj-rv03 https://underline.io/lecture/25429-multilingual-speech-translation-from-efficient-finetuning-of-pretrained-models BASE Hide details 7 Unsupervised Cross-lingual Representation Learning for Speech Recognition ... Conneau, Alexis; Baevski, Alexei; Collobert, Ronan. - : arXiv, 2020 BASE Show details 8 Beyond English-Centric Multilingual Machine Translation ... Fan, Angela; Bhosale, Shruti; Schwenk, Holger. - : arXiv, 2020 BASE Show details 9 Multilingual Speech Translation with Efficient Finetuning of Pretrained Models ... Li, Xian; Wang, Changhan; Tang, Yun. - : arXiv, 2020 BASE Show details

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