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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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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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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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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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The Zero Resource Speech Challenge 2021: Spoken language modelling ...
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Textless Speech Emotion Conversion using Discrete and Decomposed Representations ...
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Communicating artificial neural networks develop efficient color-naming systems
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In: Proc Natl Acad Sci U S A (2021)
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Compositionality and Generalization in Emergent Languages
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In: ACL 2020 - 8th annual meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02959466 ; ACL 2020 - 8th annual meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States (2020)
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LIBRI-LIGHT: a benchmark for asr with limited or no supervision
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In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-02959460 ; ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona / Virtual, Spain. pp.7669-7673, ⟨10.1109/ICASSP40776.2020.9052942⟩ (2020)
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Data Augmenting Contrastive Learning of Speech Representations in the Time Domain
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In: SLT 2020 - IEEE Spoken Language Technology Workshop ; https://hal.archives-ouvertes.fr/hal-03070321 ; SLT 2020 - IEEE Spoken Language Technology Workshop, Dec 2020, Shenzhen / Virtual, China (2020)
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Anti-efficient encoding in emergent communication
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In: https://hal.archives-ouvertes.fr/hal-02274205 ; 2019 (2019)
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Word-order biases in deep-agent emergent communication
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In: ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02274157 ; ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Jul 2019, Florence, Italy (2019)
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EGG: a toolkit for research on Emergence of lanGuage in Games
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In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations ; https://hal.archives-ouvertes.fr/hal-02274229 ; Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, Nov 2019, Hong Kong, China. ⟨10.18653/v1/D19-3010⟩ (2019)
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Abstract:
International audience ; There is renewed interest in simulating language emergence among deep neural agents that communicate to jointly solve a task, spurred by the practical aim to develop language-enabled interactive AIs, as well as by theoretical questions about the evolution of human language. However, optimizing deep architectures connected by a discrete communication channel (such as that in which language emerges) is technically challenging. We introduce EGG, a toolkit that greatly simplifies the implementation of emergent-language communication games. EGG's modular design provides a set of building blocks that the user can combine to create new games, easily navigating the optimization and architecture space. We hope that the tool will lower the technical barrier, and encourage researchers from various backgrounds to do original work in this exciting area.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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URL: https://hal.archives-ouvertes.fr/hal-02274229/file/1907.00852.pdf
https://hal.archives-ouvertes.fr/hal-02274229
https://hal.archives-ouvertes.fr/hal-02274229/document
https://doi.org/10.18653/v1/D19-3010
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