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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 Page: 1 2 Hits 1 – 20 of 28 1 Segmentation en mots faiblement supervisée pour la documentation automatique des langues OKABE, Shu; Yvon, François; Besacier, Laurent In: https://hal.archives-ouvertes.fr/hal-03477475 ; 2021 (2021) BASE Show details 2 Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads? ... Kim, Zae Myung; Besacier, Laurent; Nikoulina, Vassilina. - : arXiv, 2021 BASE Show details 3 Lightweight Adapter Tuning for Multilingual Speech Translation ... Le, Hang; Pino, Juan; Wang, Changhan. - : arXiv, 2021 BASE Show details 4 Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ... Üstün, Ahmet; Bérard, Alexandre; Besacier, Laurent. - : arXiv, 2021 BASE Show details 5 Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings ... Boito, Marcely Zanon; Yusuf, Bolaji; Ondel, Lucas; Villavicencio, Aline; Besacier, Laurent. - : arXiv, 2021 Abstract: When documenting oral-languages, Unsupervised Word Segmentation (UWS) from speech is a useful, yet challenging, task. It can be performed from phonetic transcriptions, or in the absence of these, from the output of unsupervised speech discretization models. These discretization models are trained using raw speech only, producing discrete speech units which can be applied for downstream (text-based) tasks. In this paper we compare five of these models: three Bayesian and two neural approaches, with regards to the exploitability of the produced units for UWS. Two UWS models are experimented with and we report results for Finnish, Hungarian, Mboshi, Romanian and Russian in a low-resource setting (using only 5k sentences). Our results suggest that neural models for speech discretization are difficult to exploit in our setting, and that it might be necessary to adapt them to limit sequence length. We obtain our best UWS results by using the SHMM and H-SHMM Bayesian models, which produce high quality, yet ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.2106.04298 https://arxiv.org/abs/2106.04298 BASE Hide details 6 User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis Adams, Oliver; Galliot, Benjamin; Wisniewski, Guillaume... In: ComputEL-4: Fourth Workshop on the Use of Computational Methods in the Study of Endangered Languages ; https://halshs.archives-ouvertes.fr/halshs-03030529 ; 2020 ; https://computel-workshop.org/ (2020) BASE Show details 7 A Data Efficient End-To-End Spoken Language Understanding Architecture ... Dinarelli, Marco; Kapoor, Nikita; Jabaian, Bassam. - : arXiv, 2020 BASE Show details 8 Catplayinginthesnow: Impact of Prior Segmentation on a Model of Visually Grounded Speech ... Havard, William N.; Chevrot, Jean-Pierre; Besacier, Laurent. - : arXiv, 2020 BASE Show details 9 Investigating Language Impact in Bilingual Approaches for Computational Language Documentation ... Boito, Marcely Zanon; Villavicencio, Aline; Besacier, Laurent. - : arXiv, 2020 BASE Show details 10 Controlling Utterance Length in NMT-based Word Segmentation with Attention ... Godard, Pierre; Besacier, Laurent; Yvon, Francois. - : arXiv, 2019 BASE Show details 11 MaSS - Multilingual corpus of Sentence-aligned Spoken utterances ... Boito, Marcely Zanon; Havard, William N.; Mahault Garnerin. - : Zenodo, 2019 BASE Show details 12 MaSS - Multilingual corpus of Sentence-aligned Spoken utterances ... Boito, Marcely Zanon; Havard, William N.; Mahault Garnerin. - : Zenodo, 2019 BASE Show details 13 How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages ... Boito, Marcely Zanon; Villavicencio, Aline; Besacier, Laurent. - : arXiv, 2019 BASE Show details 14 Word Recognition, Competition, and Activation in a Model of Visually Grounded Speech ... Havard, William N.; Chevrot, Jean-Pierre; Besacier, Laurent. - : arXiv, 2019 BASE Show details 15 Models of Visually Grounded Speech Signal Pay Attention To Nouns: a Bilingual Experiment on English and Japanese ... Havard, William N.; Chevrot, Jean-Pierre; Besacier, Laurent. - : arXiv, 2019 BASE Show details 16 Synthetically Spoken STAIR ... Havard, William N.; Chevrot, Jean-Pierre; Besacier, Laurent. - : Zenodo, 2018 BASE Show details 17 Synthetically Spoken STAIR ... Havard, William N.; Chevrot, Jean-Pierre; Besacier, Laurent. - : Zenodo, 2018 BASE Show details 18 Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop ... Scharenborg, Odette; Besacier, Laurent; Black, Alan. - : arXiv, 2018 BASE Show details 19 Unsupervised Word Segmentation from Speech with Attention ... Godard, Pierre; Zanon-Boito, Marcely; Ondel, Lucas. - : arXiv, 2018 BASE Show details 20 SPEECH-COCO ... Havard, William N.; Besacier, Laurent. - : Zenodo, 2017 BASE Show details Page: 1 2

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