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Investigating alignment interpretability for low-resource NMT
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation
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In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03372487 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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Alternate Endings: Improving Prosody for Incremental Neural TTS with Predicted Future Text Input
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In: Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03372802 ; Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic. pp.3865-3869, ⟨10.21437/Interspeech.2021-275⟩ (2021)
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LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: ; INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: ; INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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Contribution d'informations syntaxiques aux capacités de généralisation compositionelle des modèles seq2seq convolutifs
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In: Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale ; Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-03265890 ; Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.134-141 (2021)
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Abstract:
International audience ; Les modèles neuronaux de type seq2seq manifestent d’étonnantes capacités de prédiction quand ils sont entraînés sur des données de taille suffisante. Cependant, ils échouent à généraliser de manière satisfaisante quand la tâche implique d’apprendre et de réutiliser des règles systématiques de composition et non d’apprendre simplement par imitation des exemples d’entraînement. Le jeu de données SCAN, constitué d’un ensemble de commandes en langage naturel associées à des séquences d’action, a été spécifiquement conçu pour évaluer les capacités des réseaux de neurones à apprendre ce type de généralisation compositionnelle. Dans cet article, nous nous proposons d’étudier la contribution d’informations syntaxiques sur les capacités de généralisation compositionnelle des réseaux de neurones seq2seq convolutifs.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Compositionnalité; jeux de données SCAN; modèle convolutionnel seq2seq
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URL: https://hal.archives-ouvertes.fr/hal-03265890/document https://hal.archives-ouvertes.fr/hal-03265890/file/28.pdf https://hal.archives-ouvertes.fr/hal-03265890
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Lightweight Adapter Tuning for Multilingual Speech Translation
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In: The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) ; https://hal.archives-ouvertes.fr/hal-03294912 ; The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Aug 2021, Bangkok (Virtual), Thailand (2021)
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Visualizing Cross-Lingual Discourse Relations in Multilingual TED Corpora
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In: Proceedings of the 2nd Workshop on Computational Approaches to Discourse ; CODI 2021: 2nd Workshop on Computational Approaches to Discourse ; https://hal.archives-ouvertes.fr/hal-03642341 ; CODI 2021: 2nd Workshop on Computational Approaches to Discourse, Nov 2021, Punta Cana, Dominican Republic. ⟨10.18653/v1/2021.codi-main.16⟩ (2021)
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Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?
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In: Findings of ACL 2021 ; https://hal.archives-ouvertes.fr/hal-03299010 ; Findings of ACL 2021, Aug 2021, Bangkok (virtual), Thailand (2021)
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User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis
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In: ComputEL-4: Fourth Workshop on the Use of Computational Methods in the Study of Endangered Languages ; https://halshs.archives-ouvertes.fr/halshs-03030529 ; ComputEL-4: Fourth Workshop on the Use of Computational Methods in the Study of Endangered Languages, Mar 2021, Hawai‘i, United States (2021)
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Segmentation en mots faiblement supervisée pour la documentation automatique des langues
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In: https://hal.archives-ouvertes.fr/hal-03477475 ; 2021 (2021)
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Investigating the Impact of Gender Representation in ASR Training Data: a Case Study on Librispeech
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In: Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing ; 3rd Workshop on Gender Bias in Natural Language Processing ; https://hal.univ-grenoble-alpes.fr/hal-03472117 ; 3rd Workshop on Gender Bias in Natural Language Processing, Aug 2021, Online, France. pp.86-92, ⟨10.18653/v1/2021.gebnlp-1.10⟩ (2021)
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Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads? ...
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Lightweight Adapter Tuning for Multilingual Speech Translation ...
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Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ...
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Controlling Prosody in End-to-End TTS: A Case Study on Contrastive Focus Generation ...
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Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings ...
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Lightweight Adapter Tuning for Multilingual Speech Translation ...
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