Supervised Contrastive Learning for Accented Speech Recognition

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Y. Huang, D. Yu, C. Liu, and Y. Gong, “Multi-accent deep neural network acoustic model with accent-specific top layer using the kld-regularized model adaptation,” in Conference of the International Speech Communication Association , 2014

2014

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M. Chen, Z. Yang, J. Liang, Y. Li, and W. Liu, “Improving deep neural networks based multi-accent mandarin speech recognition using i-vectors and accent-specific top layer,” in Conference of the International Speech Communication Association , 2015

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A. Jain, M. Upreti, and P. Jyothi, “Improved accented speech recognition using accent embeddings and multi-task learning.” in Conference of the International Speech Communication Association , 2018

2018

Cited alongside, same era.

X. Yang, K. Audhkhasi, A. Rosenberg, S. Thomas, B. Ramabhadran, and M. Hasegawa-Johnson, “Joint modeling of accents and acoustics for multi-accent speech recognition,” in International Conference on Acoustics, Speech and Signal Processing , 2018

2018

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S. Sun, C.-F. Yeh, M.-Y. Hwang, M. Ostendorf, and L. Xie, “Domain adversarial training for accented speech recognition,” in International Conference on Acoustics, Speech and Signal Processing , 2018

2018

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J. Shen, R. Pang, R. J. Weiss, M. Schuster, N. Jaitly, Z. Yang, Z. Chen, Y. Zhang, Y. Wang, R. Skerrv-Ryan et al. , “Natural tts synthesis by conditioning wavenet on mel spectrogram predictions,” in International Conference on Acoustics, Speech and Signal Processing , 2018

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2019

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G. I. Winata, S. Cahyawijaya, Z. Liu, Z. Lin, A. Madotto, P. Xu, and P. Fung, “Learning Fast Adaptation on Cross-Accented Speech Recognition,” in Conference of the International Speech Communication Association , 2020

2020

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T. Chen, S. Kornblith, M. Norouzi, and G. Hinton, “A simple framework for contrastive learning of visual representations,” in International Conference on Machine Learning , 2020

2020

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P. Khosla, P. Teterwak, C. Wang, A. Sarna, Y. Tian, P. Isola, A. Maschinot, C. Liu, and D. Krishnan, “Supervised contrastive learning,” in Conference on Neural Information Processing Systems , 2020

2020

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