Speech Enhancement: Traditional and Deep Learning Techniques
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1549-7_6
Reference26 articles.
1. Takeuchi D, Yatabe K, Koizumi Y, Oikawa Y, Harada N (2020) Real-time speech enhancement using equilibriated RNN. In: ICASSP 2020—2020 IEEE international conference on acoustics, speech and signal processing (ICASSP), Barcelona, Spain, pp 851–855. https://doi.org/10.1109/ICASSP40776.2020.9054597
2. Park S, Lee J (2017) A fully convolutional neural network for speech enhancement (1993–1997). https://doi.org/10.21437/Interspeech.2017-1465
3. Weninger F, Erdogan H, Watanabe S, Vincent E, Le Roux J, Hershey JR, Schuller B (2015) Speech enhancement with LSTM recurrent neural networks and its application to noise-robust ASR. In: Latent variable analysis and signal separation: 12th international conference, LVA/ICA 2015, Liberec, Czech Republic, August 25–28, 2015, Proceedings 12. Springer, pp 91–99
4. Donahue C, Li B, Prabhavalkar R (2018) Exploring speech enhancement with generative adversarial networks for robust speech recognition. In: 2018 IEEE international conference on acoustics, speech and signal processing (ICASSP), Calgary, AB, Canada, pp 5024–5028. https://doi.org/10.1109/ICASSP.2018.8462581
5. Loizou PC (2013) Speech enhancement: theory and practice. CRC Press
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