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We present the Zero Resource Speech Challenge 2021, which asks participants to learn a language model directly from audio, without any text or labels.
1907
Earlier work this paper cites.
H. Rubenstein and J. B. Goodenough, “Contextual correlates of synonymy,” Communications of the ACM , vol. 8, no. 10, pp. 627–633, 1965
1965
Earlier work this paper cites.
G. A. Miller and W. G. Charles, “Contextual correlates of semantic similarity,” Language and cognitive processes , vol. 6, no. 1, pp. 1–28, 1991
1991
Earlier work this paper cites.
D. Yang and D. M. Powers, Verb similarity on the taxonomy of WordNet . Masaryk University, 2006
2006
Earlier work this paper cites.
E. Agirre, E. Alfonseca, K. Hall, J. Kravalova, M. Pasca, and A. Soroa, “A study on similarity and relatedness using distributional and wordnet-based approaches,” 2009
2009
Earlier work this paper cites.
E. Keuleers and M. Brysbaert, “Wuggy: A multilingual pseudoword generator,” Behavior research methods , vol. 42, no. 3, pp. 627–633, 2010
2010
Earlier work this paper cites.
K. Radinsky, E. Agichtein, E. Gabrilovich, and S. Markovitch, “A word at a time: computing word relatedness using temporal semantic analysis,” in Proceedings of the 20th international conference on World wide web , 2011, pp. 337–346
2011
Earlier work this paper cites.
E. Bruni, G. Boleda, M. Baroni, and N.-K. Tran, “Distributional semantics in technicolor,” in Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , 2012, pp. 136–145
2012
Earlier work this paper cites.
G. Halawi, G. Dror, E. Gabrilovich, and Y. Koren, “Large-scale learning of word relatedness with constraints,” in Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining , 2012, pp. 1406–1414
2012
Earlier work this paper cites.
M.-T. Luong, R. Socher, and C. D. Manning, “Better word representations with recursive neural networks for morphology,” in Proceedings of the Seventeenth Conference on Computational Natural Language Learning , 2013, pp. 104–113
2013
Earlier work this paper cites.
S. Baker, R. Reichart, and A. Korhonen, “An unsupervised model for instance level subcategorization acquisition,” in Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) , 2014, pp. 278–289
2014
Earlier work this paper cites.
V. Panayotov, G. Chen, D. Povey, and S. Khudanpur, “Librispeech: An asr corpus based on public domain audio books,” in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2015, pp. 5206–5210
2015
Earlier work this paper cites.
F. Hill, R. Reichart, and A. Korhonen, “Simlex-999: Evaluating semantic models with (genuine) similarity estimation,” Computational Linguistics , vol. 41, no. 4, pp. 665–695, 2015
2015
Cited alongside, same era.
T. Schatz, “Abx-discriminability measures and applications,” Ph.D. dissertation, Paris 6, 2016
2016
Cited alongside, same era.
2016
Cited alongside, same era.
R. Dror, G. Baumer, M. Bogomolov, and R. Reichart, “Replicability analysis for natural language processing: Testing significance with multiple datasets,” Transactions of the Association for Computational Linguistics , vol. 5, pp. 471–486, 2017
2017
Cited alongside, same era.
2020
Later among the works it cites.
M. Rivière, A. Joulin, P.-E. Mazaré, and E. Dupoux, “Unsupervised pretraining transfers well across languages,” 2020
2020
Later among the works it cites.
A. Baevski, S. Schneider, and M. Auli, “vq-wav2vec: Self-supervised learning of discrete speech representations,” in International Conference on Learning Representations , 2020. [Online]. Available: https://openreview.net/forum?id=rylwJxrYDS
2020
Later among the works it cites.
A. T. Liu, S.-w. Yang, P.-H. Chi, P.-c. Hsu, and H.-y. Lee, “Mockingjay: Unsupervised speech representation learning with deep bidirectional transformer encoders,” in ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2020, pp. 6419–6423
2020
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2018
Cited alongside, same era.
2018
Cited alongside, same era.
2019
Cited alongside, same era.
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” NAACL , 2019
2019
Cited alongside, same era.
M. Ott, S. Edunov, A. Baevski, A. Fan, S. Gross, N. Ng, D. Grangier, and M. Auli, “fairseq: A fast, extensible toolkit for sequence modeling,” in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations) . Minneapolis, Minnesota: Association for Computational Linguistics, Jun. 2019, pp. 48–53. [Online]. Available: https://www.aclweb.org/anthology/N19-4009
2019
Cited alongside, same era.
E. Dunbar, R. Algayres, J. Karadayi, M. Bernard, J. Benjumea, X.-N. Cao, L. Miskic, C. Dugrain, L. Ondel, A. W. Black, L. Besacier, S. Sakti, and E. Dupoux, “The zero resource speech challenge 2019: Tts without t,” 2019
2019
Cited alongside, same era.
J. Kahn, M. Riviere, W. Zheng, E. Kharitonov, Q. Xu, P. Mazare, J. Karadayi, V. Liptchinsky, R. Collobert, C. Fuegen, and et al., “Libri-light: A benchmark for asr with limited or no supervision,” ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , May 2020. [Online]. Available: http://dx.doi.org/10.1109/ICASSP40776.2020.9052942
2020
Cited alongside, same era.
Later among the works it cites.
E. Dunbar, J. Karadayi, M. Bernard, X.-N. Cao, R. Algayres, L. Ondel, L. Besacier, S. Sakriani, and E. Dupoux, “The zero resource speech challenge 2020: Discovering discrete subword and word units,” in INTERSPEECH, perception;bootstrapping/modeling;clustering/bootphon , 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
B. van Niekerk, L. Nortje, M. Baas, and H. Kamper, “Analyzing speaker information in self-supervised models to improve zero-resource speech processing,” Submitted to Interspeech, 2021
2021
Closest in time.
J. Chorowski, G. Ciesielski, J. Dzikowski, A. Łancucki, R. Marxer, M. Opala, P. Pusz, P. Rychlikowski, and M. Stypułkowski, “Submission to interspeech, 2021,” Submitted to Interspeech, 2021
2021
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Liu, “Submission to interspeech, 2021,” Submitted to Interspeech, 2021
2021
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T. Maekaku, Y. Fujita, X. Chang, L.-W. Chen, S. Watanabe, and A. Rudnicky, “Submission to interspeech, 2021,” Submitted to Interspeech, 2021
2021
Closest in time.