Joint Time-Domain and Frequency-Domain Progressive Learning for Single-Channel Speech Enhancement and Recognition
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0601-3_4
Reference31 articles.
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2. Zhang, Y., Chan, W., Jaitly, N.: Very deep convolutional networks for end-to-end speech recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4845–4849. IEEE (2017)
3. Loizou, P.C.: Speech Enhancement: Theory and Practice. CRC Press, Boca Raton (2013)
4. Tu, Y., Du, J., Sun, L., Ma, F., Lee, C.H.: On design of robust deep models for chime-4 multi-channel speech recognition with multiple configurations of array microphones. In: INTERSPEECH, pp. 394–398 (2017)
5. Wang, D.L., Chen, J.: Supervised speech separation based on deep learning: an overview. IEEE/ACM Trans. Audio Speech Lang. Process. 26(10), 1702–1726 (2018)
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