Speech Enhancement Based on Two-Stage Neural Network with Structured State Space for Sequence Transformation
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-51057-1_2
Reference18 articles.
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2. Hao, X., Su, X., Horaud, R, Li, X.: FullSubNet: a full-band and sub-band fusion model for real-time single-channel speech enhancement. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, Canada, 6–11 June 2021, pp. 6633–6637 (2021). https://doi.org/10.1109/ICASSP39728.2021.9414177
3. Communications in Computer and Information Science;R Nasretdinov,2022
4. Tan, K., Wang, D.: A convolutional recurrent neural network for real-time speech enhancement: In: Proceedings of the INTERSPEECH 2018, Hyderabad, India, 2–6 September 2018, pp. 3229–3233 (2018). https://doi.org/10.21437/Interspeech.2018-1405
5. Hu, Y., et al.: DCCRN: deep complex convolution recurrent network for phase-aware speech enhancement. In: Proceedings of INTERSPEECH 2020, Shanghai, China, 25–29 October 2020, pp. 2472–2476 (2020). https://doi.org/10.21437/Interspeech.2020-2537
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