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How much does prosody help word segmentation? A simulation study on infant-directed speech
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-03498888 ; Cognition, Elsevier, 2022, 219, pp.104961. ⟨10.1016/j.cognition.2021.104961⟩ (2022)
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On the role of population heterogeneity in emergent communication ...
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SCALa: A blueprint for computational models of language acquisition in social context
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.inria.fr/hal-03373586 ; Cognition, Elsevier, 2021, 213, pp.104779. ⟨10.1016/j.cognition.2021.104779⟩ (2021)
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The Zero Resource Speech Challenge 2021: Spoken language modelling
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In: ISSN: 0162-8828 ; IEEE Transactions on Pattern Analysis and Machine Intelligence ; https://hal.inria.fr/hal-03329301 ; IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2021, pp.1-1. ⟨10.1109/TPAMI.2021.3083839⟩ (2021)
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| 5 |
The Zero Resource Speech Challenge 2021: Spoken language modelling
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In: Interspeech 2021 - Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-03329301 ; Interspeech 2021 - Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic. ⟨10.1109/TPAMI.2021.3083839⟩ (2021)
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Do Infants Really Learn Phonetic Categories?
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In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-03550830 ; Open Mind, MIT Press, 2021, 5, pp.113-131. ⟨10.1162/opmi_a_00046⟩ (2021)
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Speech Resynthesis from Discrete Disentangled Self-Supervised Representations
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In: INTERSPEECH 2021 - Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-03329245 ; INTERSPEECH 2021 - Annual Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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| 8 |
Communicating artificial neural networks develop efficient color-naming systems
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In: ISSN: 0027-8424 ; EISSN: 1091-6490 ; Proceedings of the National Academy of Sciences of the United States of America ; https://hal.inria.fr/hal-03329084 ; Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2021, 118 (12), ⟨10.1073/pnas.2016569118⟩ (2021)
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| 9 |
Early phonetic learning without phonetic categories -- Insights from large-scale simulations on realistic input
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In: ISSN: 0027-8424 ; EISSN: 1091-6490 ; Proceedings of the National Academy of Sciences of the United States of America ; https://hal.archives-ouvertes.fr/hal-03070566 ; Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2021, 118 (7), pp.e2001844118. ⟨10.1073/pnas.2001844118⟩ (2021)
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| 10 |
Does infant-directed speech help phonetic learning? A machine learning investigation
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In: ISSN: 0364-0213 ; EISSN: 1551-6709 ; Cognitive Science ; https://hal.archives-ouvertes.fr/hal-03080098 ; Cognitive Science, Wiley, 2021, 45 (5), ⟨10.1111/cogs.12946⟩ (2021)
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| 11 |
On Generative Spoken Language Modeling from Raw Audio
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In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03329219 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021 (2021)
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VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation
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Wang, Changhan; Rivière, Morgane; Lee, Ann; Wu, Anne; Talnikar, Chaitanya; Haziza, Daniel; Williamson, Mary; Pino, Juan; Dupoux, Emmanuel. - : HAL CCSD, 2021
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In: https://hal.inria.fr/hal-03329290 ; 2021, ⟨10.18653/v1/2021.acl-long.80⟩ (2021)
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Abstract:
International audience ; We introduce VoxPopuli, a large-scale multilingual corpus providing 400K hours of unlabeled speech data in 23 languages. It is the largest open data to date for unsupervised representation learning as well as semisupervised learning. VoxPopuli also contains 1.8K hours of transcribed speeches in 15 languages and their aligned oral interpretations into 15 target languages totaling 17.3K hours. We provide speech recognition (ASR) baselines and validate the versatility of VoxPopuli unlabeled data in semisupervised ASR and speech-to-text translation under challenging out-of-domain settings.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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URL: https://hal.inria.fr/hal-03329290/document
https://hal.inria.fr/hal-03329290
https://doi.org/10.18653/v1/2021.acl-long.80
https://hal.inria.fr/hal-03329290/file/2101.00390.pdf
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| 13 |
IntPhys 2019: A Benchmark for Visual Intuitive Physics Understanding
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In: ISSN: 0162-8828 ; IEEE Transactions on Pattern Analysis and Machine Intelligence ; https://hal.archives-ouvertes.fr/hal-02274273 ; IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2021 (2021)
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| 14 |
Occlusion resistant learning of intuitive physics from videos
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In: https://hal.archives-ouvertes.fr/hal-03139755 ; 2021 (2021)
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Learning spectro-temporal representations of complex sounds with parameterized neural networks
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In: ISSN: 0001-4966 ; EISSN: 1520-8524 ; Journal of the Acoustical Society of America ; https://hal.inria.fr/hal-03329261 ; Journal of the Acoustical Society of America, Acoustical Society of America, 2021, 150 (1), pp.353-366. ⟨10.1121/10.0005482⟩ (2021)
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| 18 |
VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation ...
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VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation ...
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