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Cued Speech (CS) is a visual communication system for the deaf or hearing impaired people.
R. O. Cornett, “Cued speech,” American annals of the deaf , pp. 3–13, 1967
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C. Benoit, T. Lallouache, T. Mohamadi, and C. Abry, “A set of french visemes for visual speech synthesis,” pp. 485–501, 1992
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F. Béchet, “Lia phon: un systeme complet de phonétisation de textes,” Traitement automatique des langues , vol. 42, no. 1, pp. 47–67, 2001
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T. Burger, A. Caplier, and S. Mancini, “Cued speech hand gestures recognition tool,” in Proc. EUSIPCO , pp. 1–4, 2005
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A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber, “Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks,” in Proc. ICML , pp. 369–376, 2006
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P. Heracleous, D. Beautemps, and N. Aboutabit, “Cued speech automatic recognition in normal-hearing and deaf subjects,” Speech Communication , vol. 52, no. 6, pp. 504–512, 2010
2010
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P. Heracleous, D. Beautemps, and N. Hagita, “Continuous phoneme recognition in cued speech for french,” in Proc. EUSIPCO , pp. 2090–2093, 2012
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A. Graves, A.-r. Mohamed, and G. Hinton, “Speech recognition with deep recurrent neural networks,” in Proc. ICASSP , pp. 6645–6649, 2013
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S. Ioffe and C. Szegedy, “Batch normalization: Accelerating deep network training by reducing internal covariate shift,” in Proc. ICML , pp. 448–456, 2015
2015
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2015
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S. Gupta, J. Hoffman, and J. Malik, “Cross modal distillation for supervision transfer,” in Proc. CVPR , pp. 2827–2836, 2016
2016
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D. Amodei, S. Ananthanarayanan, R. Anubhai, J. Bai, E. Battenberg, C. Case, J. Casper, B. Catanzaro, Q. Cheng, G. Chen et al. , “Deep speech 2: End-to-end speech recognition in english and mandarin,” in Proc. ICML , pp. 173–182, 2016
2016
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L. Liu, J. Li, G. Feng, and X.-P. S. Zhang, “Automatic detection of the temporal segmentation of hand movements in british english cued speech.” in Proc. INTERSPEECH , pp. 2285–2289, 2019
2019
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L. Liu, G. Feng, D. Beautemps, and X.-P. Zhang, “A novel resynchronization procedure for hand-lips fusion applied to continuous french cued speech recognition,” in Proc. EUSIPCO , pp. 1–5, 2019
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F. M. Thoker and J. Gall, “Cross-modal knowledge distillation for action recognition,” in Proc. ICIP , pp. 6–10, 2019
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W. Hao and Z. Zhang, “Spatiotemporal distilled dense-connectivity network for video action recognition,” Pattern Recognition , vol. 92, pp. 13–24, 2019
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M.-C. Wu, C.-T. Chiu, and K.-H. Wu, “Multi-teacher knowledge distillation for compressed video action recognition on deep neural networks,” in Proc. ICASSP , pp. 2202–2206, 2019
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2018
Cited alongside, same era.
L. Liu, G. Feng, and D. Beautemps, “Automatic temporal segmentation of hand movements for hand positions recognition in french cued speech,” in Proc. ICASSP , pp. 3061–3065, 2018
2018
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Z. Luo, J.-T. Hsieh, L. Jiang, J. C. Niebles, and L. Fei-Fei, “Graph distillation for action detection with privileged modalities,” in Proc. ECCV , pp. 166–183, 2018
2018
Cited alongside, same era.
E. J. Crowley, G. Gray, and A. J. Storkey, “Moonshine: Distilling with cheap convolutions.” in Proc. NeurIPS , pp. 2893–2903, 2018
2018
Cited alongside, same era.
M. Zhao, T. Li, M. Abu Alsheikh, Y. Tian, H. Zhao, A. Torralba, and D. Katabi, “Through-wall human pose estimation using radio signals,” in Proc. CVPR , pp. 7356–7365, 2018
2018
Cited alongside, same era.
M. Huang, Y. You, Z. Chen, Y. Qian, and K. Yu, “Knowledge distillation for sequence model.” in Proc. INTERSPEECH , pp. 3703–3707, 2018
2018
Cited alongside, same era.
A. Kendall, Y. Gal, and R. Cipolla, “Multi-task learning using uncertainty to weigh losses for scene geometry and semantics,” in Proc. CVPR , pp. 7482–7491, 2018
2018
Cited alongside, same era.
2019
Later among the works it cites.
R. Takashima, L. Sheng, and H. Kawai, “Investigation of sequence-level knowledge distillation methods for ctc acoustic models,” in Proc. ICASSP , pp. 6156–6160, 2019
2019
Later among the works it cites.
2019
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L. Liu, G. Feng, D. Beautemps, and X.-P. Zhang, “Re-synchronization using the hand preceding model for multi-modal fusion in automatic continuous cued speech recognition,” IEEE Transactions on Multimedia , vol. 23, pp. 292–305, 2020
2020
Later among the works it cites.
S. Zhang, S. Guo, L. Wang, W. Huang, and M. Scott, “Knowledge integration networks for action recognition,” in Proc. AAAI , vol. 34, no. 07, pp. 12 862–12 869, 2020
2020
Later among the works it cites.
K. Papadimitriou and G. Potamianos, “A fully convolutional sequence learning approach for cued speech recognition from videos,” in Proc. EUSIPCO , pp. 326–330, 2021
2021
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