Context-Aware Enhanced Dereverberation Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5591-2_35
Reference26 articles.
1. Naylor, P., Gaubitch, N.: Speech Dereverberation. Springer, London (2010)
2. Yoshioka, T., et al.: Making machines understand us in reverberant rooms: robustness against reverberation for automatic speech recognition. IEEE Signal Process. Mag. 29(6), 114–126 (2012)
3. Kinoshita, K., et al.: The REVERB challenge: a common evaluation framework for dereverberation and recognition of reverberant speech. In: Proceeding 2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 1–4 (2013)
4. Giri, R., Seltzer, M.L., Droppo, J., Yu, D.: Improving speech recognition in reverberation using a room-aware deep neural network and multi-task learning. In: Proceeding 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5014–5018 (2015)
5. Zhao, X., Wang, Y., Wang, D.: Robust speaker identification in noisy and reverberant conditions. IEEE/ACM Trans. Audio Speech Lang. Process. 22, 836–845 (2014)
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