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This paper introduces GigaST, a large-scale pseudo speech translation (ST) corpus.
A. Bérard, O. Pietquin, C. Servan, and L. Besacier, “Listen and translate: A proof of concept for end-to-end speech-to-text translation,” in NIPS workshop on End-to-end Learning for Speech and Audio Processing , 2016
2016
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L. Duong, A. Anastasopoulos, D. Chiang, S. Bird, and T. Cohn, “An attentional model for speech translation without transcription,” in Proc. of NAACL-HLT , 2016, pp. 949–959
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R. Sennrich, B. Haddow, and A. Birch, “Improving neural machine translation models with monolingual data,” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 , 2016
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R. Sennrich, B. Haddow, and A. Birch, “Neural machine translation of rare words with subword units,” in Proc. of ACL , 2016, pp. 1715–1725
2016
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M. A. Di Gangi, R. Cattoni, L. Bentivogli, M. Negri, and M. Turchi, “MuST-C: a Multilingual Speech Translation Corpus,” in Proc. of NAACL-HLT , 2019, pp. 2012–2017
2017
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A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin, “Attention is all you need,” in Proc. of NeurIPS , I. Guyon, U. von Luxburg, S. Bengio, H. M. Wallach, R. Fergus, S. V. N. Vishwanathan, and R. Garnett, Eds., 2017, pp. 5998–6008
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2017
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L. Dong, S. Xu, and B. Xu, “Speech-transformer: A no-recurrence sequence-to-sequence model for speech recognition,” in Proc. of ICASSP , 2018, pp. 5884–5888
2018
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R. Bawden, R. Sennrich, A. Birch, and B. Haddow, “Evaluating discourse phenomena in neural machine translation,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) . New Orleans, Louisiana: Association for Computational Linguistics, Jun. 2018, pp. 1304–1313. [Online]. Available: https://aclanthology.org/N18-1118
2018
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S. Läubli, R. Sennrich, and M. Volk, “Has machine translation achieved human parity? a case for document-level evaluation,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . Brussels, Belgium: Association for Computational Linguistics, 2018, pp. 4791–4796. [Online]. Available: https://aclanthology.org/D18-1512
2018
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Y. Jia, M. Johnson, W. Macherey, R. J. Weiss, Y. Cao, C.-C. Chiu, N. Ari, S. Laurenzo, and Y. Wu, “Leveraging weakly supervised data to improve end-to-end speech-to-text translation,” in Proc. of ICASSP . IEEE, 2019
2019
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B. Li, Y. Li, C. Xu, Y. Lin, J. Liu, H. Liu, Z. Wang, Y. Zhang, N. Xu, Z. Wang, K. Feng, H. Chen, T. Liu, Y. Li, Q. Wang, T. Xiao, and J. Zhu, “The NiuTrans machine translation systems for WMT19,” in Proceedings of the Fourth Conference on Machine Translation , 2019
2019
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2020
Later among the works it cites.
C. Zhao, M. Wang, Q. Dong, R. Ye, and L. Li, “NeurST: Neural speech translation toolkit,” in Proc. of ACL - System Demonstrations , Aug. 2021
2021
Later among the works it cites.
G. Chen, S. Chai, G.-B. Wang, J. Du, W.-Q. Zhang, C. Weng, D. Su, D. Povey, J. Trmal, J. Zhang, M. Jin, S. Khudanpur, S. Watanabe, S. Zhao, W. Zou, X. Li, X. Yao, Y. Wang, Z. You, and Z. Yan, “GigaSpeech: An Evolving, Multi-Domain ASR Corpus with 10,000 Hours of Transcribed Audio,” in Proc. Interspeech 2021 , 2021, pp. 3670–3674
2021
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E. Salesky, M. Wiesner, J. Bremerman, R. Cattoni, M. Negri, M. Turchi, D. W. Oard, and M. Post, “The multilingual tedx corpus for speech recognition and translation,” in Proc. of Interspeech , 2021
2021
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2019
Cited alongside, same era.
D. S. Park, W. Chan, Y. Zhang, C.-C. Chiu, B. Zoph, E. D. Cubuk, and Q. V. Le, “Specaugment: A simple data augmentation method for automatic speech recognition,” in Proc. of INTERSPEECH , 2019
2019
Cited alongside, same era.
H. Inaguma, S. Kiyono, K. Duh, S. Karita, N. Yalta, T. Hayashi, and S. Watanabe, “ESPnet-ST: All-in-one speech translation toolkit,” in Proc. of ACL , 2020, pp. 302–311
2020
Cited alongside, same era.
C. Wang, Y. Tang, X. Ma, A. Wu, D. Okhonko, and J. Pino, “Fairseq s2t: Fast speech-to-text modeling with fairseq,” in Proc. of AACL , 2020, pp. 33–39
2020
Cited alongside, same era.
A. Baevski, Y. Zhou, A. Mohamed, and M. Auli, “wav2vec 2.0: A framework for self-supervised learning of speech representations,” in Proc. of NeurIPS , H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, and H. Lin, Eds., 2020
2020
Cited alongside, same era.
L. Wu, X. Pan, Z. Lin, Y. Zhu, M. Wang, and L. Li, “The volctrans machine translation system for wmt20,” in Proceedings of the Fifth Conference on Machine Translation (Volume 2: Shared Task Papers) , Nov. 2020
2020
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Later among the works it cites.
W.-N. Hsu, B. Bolte, Y.-H. H. Tsai, K. Lakhotia, R. Salakhutdinov, and A. Mohamed, “Hubert: Self-supervised speech representation learning by masked prediction of hidden units,” IEEE/ACM Transactions on Audio, Speech, and Language Processing , vol. 29, pp. 3451–3460, 2021
2021
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F. Akhbardeh, A. Arkhangorodsky, M. Biesialska, O. Bojar, R. Chatterjee, V. Chaudhary, M. R. Costa-jussa, C. España-Bonet, A. Fan, C. Federmann, M. Freitag, Y. Graham, R. Grundkiewicz, B. Haddow, L. Harter, K. Heafield, C. Homan, M. Huck, K. Amponsah-Kaakyire, J. Kasai, D. Khashabi, K. Knight, T. Kocmi, P. Koehn, N. Lourie, C. Monz, M. Morishita, M. Nagata, A. Nagesh, T. Nakazawa, M. Negri, S. Pal, A. A. Tapo, M. Turchi, V. Vydrin, and M. Zampieri, “Findings of the 2021 conference on machine translation (WMT21),” in Proceedings of the Sixth Conference on Machine Translation . Association for Computational Linguistics, Nov. 2021, pp. 1–88. [Online]. Available: https://aclanthology.org/2021.wmt-1.1
2021
Later among the works it cites.
K. Kuligowska and B. Kowalczuk, “Pseudo-labeling with transformers for improving question answering systems,” Procedia Computer Science , vol. 192, pp. 1162–1169, 2021, knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1877050921016082
2021
Later among the works it cites.
F. Akhbardeh, A. Arkhangorodsky, M. Biesialska, O. Bojar, R. Chatterjee, V. Chaudhary, M. R. Costa-jussa, C. España-Bonet, A. Fan, C. Federmann, M. Freitag, Y. Graham, R. Grundkiewicz, B. Haddow, L. Harter, K. Heafield, C. Homan, M. Huck, K. Amponsah-Kaakyire, J. Kasai, D. Khashabi, K. Knight, T. Kocmi, P. Koehn, N. Lourie, C. Monz, M. Morishita, M. Nagata, A. Nagesh, T. Nakazawa, M. Negri, S. Pal, A. A. Tapo, M. Turchi, V. Vydrin, and M. Zampieri, “Findings of the 2021 conference on machine translation (WMT21),” in Proceedings of the Sixth Conference on Machine Translation . Online: Association for Computational Linguistics, Nov. 2021, pp. 1–88. [Online]. Available: https://aclanthology.org/2021.wmt-1.1
2021
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S.-w. Yang, P.-H. Chi, Y.-S. Chuang, C.-I. J. Lai, K. Lakhotia, Y. Y. Lin, A. T. Liu, J. Shi, X. Chang, G.-T. Lin et al. , “Superb: Speech processing universal performance benchmark,” in Proc. of INTERSPEECH , 2021
2021
Later among the works it cites.