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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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Evain, Solène; Nguyen, Ha; Le, Hang; Zanon Boito, Marcely; Mdhaffar, Salima; Alisamir, Sina; Tong, Ziyi; Tomashenko, Natalia; Dinarelli, Marco; Parcollet, Titouan; Allauzen, Alexandre; Estève, Yannick; Lecouteux, Benjamin; Portet, François; Rossato, Solange; Ringeval, Fabien; Schwab, Didier; Besacier, Laurent
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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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Abstract:
International audience ; Self-Supervised Learning (SSL) using huge unlabeled data has been successfully explored for image and natural language processing. Recent works also investigated SSL from speech. They were notably successful to improve performance on downstream tasks such as automatic speech recognition (ASR). While these works suggest it is possible to reduce dependence on labeled data for building efficient speech systems, their evaluation was mostly made on ASR and using multiple and heterogeneous experimental settings (most of them for English). This questions the objective comparison of SSL approaches and the evaluation of their impact on building speech systems. In this paper, we propose LeBenchmark: a reproducible framework for assessing SSL from speech. It not only includes ASR (high and low resource) tasks but also spoken language understanding, speech translation and emotion recognition. We also focus on speech technologies in a language different than English: French. SSL models of different sizes are trained from carefully sourced and documented datasets. Experiments show that SSL is beneficial for most but not all tasks which confirms the need for exhaustive and reliable benchmarks to evaluate its real impact. LeBenchmark is shared with the scientific community for reproducible research in SSL from speech.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; ASR; Automatic Emotion Recognition; Self-Supervised Representation Learning; SLU; Speech Translation
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URL: https://hal.archives-ouvertes.fr/hal-03317730v3/document https://hal.archives-ouvertes.fr/hal-03317730v3/file/FLOWBERT_IS2021%282%29.pdf https://hal.archives-ouvertes.fr/hal-03317730
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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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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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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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Controlling Prosody in End-to-End TTS: A Case Study on Contrastive Focus Generation ...
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Lightweight Adapter Tuning for Multilingual Speech Translation ...
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Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads? ...
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Multilingual Unsupervised Neural Machine Translation with Denoising Adapters ...
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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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Collaborative transcription in Australian Aboriginal communities
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Controlling Prosody in End-to-End TTS: A Case Study on Contrastive Focus Generation
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FlauBERT: Unsupervised Language Model Pre-training for French
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In: Proceedings of the 12th Language Resources and Evaluation Conference ; LREC ; https://hal.archives-ouvertes.fr/hal-02890258 ; LREC, 2020, Marseille, France (2020)
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