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  • The Inria's Research Teams produce an annual Activity Report presenting their activities and their results of the year. These reports include the team members, the scientific program, the software developed by the team and the new results of the year. The report also describes the grants, contracts and the activities of dissemination and teaching. Finally, the report gives the list of publications of the year.

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Bibliography

Major publications by the team in recent years
  • 1E. Dupoux.

    Cognitive Science in the era of Artificial Intelligence: A roadmap for reverse-engineering the infant language-learner, in: Cognition, 2018.
  • 2A. Fourtassi, E. Dupoux.

    A Rudimentary Lexicon and Semantics Help Bootstrap Phoneme Acquisition, in: Proceedings of the 18th Conference on Computational Natural Language Learning (CoNLL), Baltimore, Maryland USA, Association for Computational Linguistics, June 2014, pp. 191-200. [ DOI : 10.3115/v1/W14-1620 ]
  • 3A. Fourtassi, T. Schatz, B. Varadarajan, E. Dupoux.

    Exploring the Relative Role of Bottom-up and Top-down Information in Phoneme Learning, in: Proceedings of the 52nd Annual meeting of the ACL, Baltimore, Maryland, Association for Computational Linguistics, 2014, vol. 2, pp. 1-6. [ DOI : 10.3115/v1/P14-2001 ]
  • 4Y. Hoshen, R. J. Weiss, K. W. Wilson.

    Speech acoustic modeling from raw multichannel waveforms, in: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on, IEEE, 2015, pp. 4624–4628.
  • 5T. Linzen, E. Dupoux, Y. Goldberg.

    Assessing the ability of LSTMs to learn syntax-sensitive dependencies, in: Transactions of the Association for Computational Linguistics, 2016, vol. 4, pp. 521-535.
  • 6T. Linzen, E. Dupoux, B. Spector.

    Quantificational features in distributional word representations, in: Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics, 2016, pp. pages 1 – 1-11. [ DOI : 10.18653/v1/S16-2001 ]
  • 7A. Martin, S. Peperkamp, E. Dupoux.

    Learning Phonemes with a Proto-lexicon, in: Cognitive Science, 2013, vol. 37, pp. 103-124. [ DOI : 10.1111/j.1551-6709.2012.01267.x ]
  • 8S. Mehri, K. Kumar, I. Gulrajani, R. Kumar, S. Jain, J. Sotelo, A. Courville, Y. Bengio.

    SampleRNN: An unconditional end-to-end neural audio generation model, in: arXiv preprint arXiv:1612.07837, 2016.
  • 9T. N. Sainath, R. J. Weiss, A. Senior, K. W. Wilson, O. Vinyals.

    Learning the speech front-end with raw waveform CLDNNs, in: Sixteenth Annual Conference of the International Speech Communication Association, 2015.
  • 10T. Schatz, V. Peddinti, F. Bach, A. Jansen, H. Hynek, E. Dupoux.

    Evaluating speech features with the Minimal-Pair ABX task: Analysis of the classical MFC/PLP pipeline, in: INTERSPEECH-2013, Lyon, France, International Speech Communication Association, 2013, pp. 1781-1785.
  • 11R. Thiollière, E. Dunbar, G. Synnaeve, M. Versteegh, E. Dupoux.

    A Hybrid Dynamic Time Warping-Deep Neural Network Architecture for Unsupervised Acoustic Modeling, in: INTERSPEECH-2015, 2015, pp. 3179-3183.
  • 12A. Van Den Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. Senior, K. Kavukcuoglu.

    Wavenet: A generative model for raw audio, in: CoRR abs/1609.03499, 2016.
Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 15E. Dupoux.

    Cognitive science in the era of artificial intelligence: A roadmap for reverse-engineering the infant language-learner, in: Cognition, April 2018, vol. 173, pp. 43 - 59, https://arxiv.org/abs/1607.08723. [ DOI : 10.1016/j.cognition.2017.11.008 ]

    https://hal.archives-ouvertes.fr/hal-01888694
  • 16A. Guevara-Rukoz, A. Cristia, B. Ludusan, R. Thiollière, A. Martin, R. Mazuka, E. Dupoux.

    Are Words Easier to Learn From Infant- Than Adult-Directed Speech? A Quantitative Corpus-Based Investigation, in: Cognitive Science, July 2018, vol. 42, no 5, pp. 1586 - 1617. [ DOI : 10.1111/cogs.12616 ]

    https://hal.archives-ouvertes.fr/hal-01888701
  • 17T. Schatz, F. Bach, E. Dupoux.

    Evaluating automatic speech recognition systems as quantitative models of cross-lingual phonetic category perception, in: Journal of the Acoustical Society of America, May 2018, vol. 143, no 5, pp. EL372 - EL378. [ DOI : 10.1121/1.5037615 ]

    https://hal.archives-ouvertes.fr/hal-01888735

International Conferences with Proceedings

  • 18X.-N. Cao, C. Dakhlia, P. Del Carmen, M.-A. Jaouani, M. Ould-Arbi, E. Dupoux.

    Baby Cloud, a technological platform for parents and researchers, in: LREC 2018 - 11th edition of the Language Resources and Evaluation Conference, Miyazaki, Japan, Proceedings of LREC 2018, May 2018.

    https://hal.archives-ouvertes.fr/hal-01948107
  • 19N. Holzenberger, M. Du, J. Karadayi, R. Riad, E. Dupoux.

    Learning Word Embeddings: Unsupervised Methods for Fixed-size Representations of Variable-length Speech Segments, in: Interspeech 2018, Hyderabad, India, Proceedings of Interspeech 2018, ISCA, September 2018. [ DOI : 10.21437/Interspeech.2018-2364 ]

    https://hal.archives-ouvertes.fr/hal-01888708
  • 20L. Ondel, P. Godard, L. Besacier, E. Larsen, M. Hasegawa-Johnson, O. Scharenborg, E. Dupoux, L. Burget, F. Yvon, S. Khudanpur.

    Bayesian Models for Unit Discovery on a Very Low Resource Language, in: ICASSP 2018, Calgary, Alberta, Canada, Proceedings of ICASSP 2018, April 2018, https://arxiv.org/abs/1802.06053 - Accepted to ICASSP 2018.

    https://hal.archives-ouvertes.fr/hal-01888718
  • 21R. Riad, C. Dancette, J. Karadayi, N. Zeghidour, T. Schatz, E. Dupoux.

    Sampling strategies in Siamese Networks for unsupervised speech representation learning, in: Interspeech 2018, Hyderabad, India, Proceedings of Interspeech 2018, September 2018, https://arxiv.org/abs/1804.11297 - Conference paper at Interspeech 2018.

    https://hal.archives-ouvertes.fr/hal-01888725
  • 22O. Scharenborg, L. Besacier, A. Black, M. Hasegawa-Johnson, F. Metze, G. Neubig, S. Stuker, P. Godard, M. Muller, L. Ondel, S. Palaskar, P. Arthur, F. Ciannella, M. Du, E. Larsen, D. Merkx, R. Riad, L. Wang, E. Dupoux.

    Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop, in: ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Alberta, Canada, April 2018.

    https://hal.archives-ouvertes.fr/hal-01709578
  • 23A. Thual, C. Dancette, J. Karadayi, J. Benjumea, E. Dupoux.

    A K-nearest neighbours approach to unsupervised spoken term discovery, in: IEEE Spoken Language Technology SLT-2018, Athènes, Greece, Proceedings of SLT 2018, December 2018.

    https://hal.archives-ouvertes.fr/hal-01947953
  • 24N. Zeghidour, N. Usunier, I. Kokkinos, T. Schatz, G. Synnaeve, E. Dupoux.

    Learning Filterbanks from Raw Speech for Phoneme Recognition, in: ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Alberta, Canada, Proceedings of ICASSP 2018, April 2018, https://arxiv.org/abs/1711.01161v2 - Accepted at ICASSP 2018.

    https://hal.archives-ouvertes.fr/hal-01888737
  • 25N. Zeghidour, N. Usunier, G. Synnaeve, R. Collobert, E. Dupoux.

    End-to-End Speech Recognition From the Raw Waveform, in: Interspeech 2018, Hyderabad, India, Proceedings of Interspeech 2018, September 2018, https://arxiv.org/abs/1806.07098 - Accepted for presentation at Interspeech 2018. [ DOI : 10.21437/Interspeech.2018-2414 ]

    https://hal.archives-ouvertes.fr/hal-01888739

Conferences without Proceedings

References in notes
  • 27D. A. Ferrucci.

    Introduction to “this is watson”, in: IBM Journal of Research and Development, 2012, vol. 56, no 3.4, pp. 1–1.
  • 28K. He, X. Zhang, S. Ren, J. Sun.

    Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, in: Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 1026–1034.
  • 29J. Hernández-Orallo, F. Martínez-Plumed, U. Schmid, M. Siebers, D. L. Dowe.

    Computer models solving intelligence test problems: Progress and implications, in: Artificial Intelligence, 2016, vol. 230, pp. 74–107.
  • 30B. M. Lake, T. D. Ullman, J. B. Tenenbaum, S. J. Gershman.

    Building machines that learn and think like people, in: arXiv preprint arXiv:1604.00289, 2016.
  • 31C. Lu, X. Tang.

    Surpassing human-level face verification performance on LFW with GaussianFace, in: arXiv preprint arXiv:1404.3840, 2014.
  • 32S. T. Mueller.

    A partial implementation of the BICA cognitive decathlon using the Psychology Experiment Building Language (PEBL), in: International Journal of Machine Consciousness, 2010, vol. 2, no 02, pp. 273–288.
  • 33D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, D. Hassabis.

    Mastering the game of Go with deep neural networks and tree search, in: Nature, 2016, vol. 529, no 7587, pp. 484–489.
  • 34I. Sutskever, O. Vinyals, Q. V. Le.

    Sequence to sequence learning with neural networks, in: Advances in neural information processing systems, 2014, pp. 3104–3112.
  • 35A. M. Turing.

    Computing machinery and intelligence, in: Mind, 1950, vol. 59, no 236, pp. 433–460.
  • 36W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig.

    Achieving human parity in conversational speech recognition, in: arXiv preprint arXiv:1610.05256, 2016.