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The lack of code-switch training data is one of the major concerns in the development of end-to-end code-switching automatic speech recognition (ASR) models.
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E. Yilmaz, M. McLaren, H. van den Heuvel, and D. A. van Leeuwen, “Semi-supervised acoustic model training for speech with code-switching,”
2018
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S. Karita, S. Watanabe, T. Iwata, A. Ogawa, and M. Delcroix, “Semi-supervised end-to-end speech recognition,” in
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Z. Zeng, Y. Khassanov, V. T. Pham, H. Xu, E. S. Chng, and H. Li, “On the end-to-end solution to mandarin-english code-switching speech recognition,” in
2019
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K. Li, J. Li, G. Ye, R. Zhao, and Y. Gong, “Towards code-switching asr for end-to-end ctc models,” in
2019
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C. Shan, C. Weng, G. Wang, D. Su, M. Luo, D. Yu, and L. Xie, “Investigating end-to-end speech recognition for mandarin-english code-switching,” in
2019
Closest in time.