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We propose TF-GridNet, a novel multi-path deep neural network (DNN) operating in the time-frequency (T-F) domain, for monaural talker-independent speaker separation in anechoic conditions.
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E. Tzinis, Z. Wang, and P. Smaragdis, “Sudo RM -RF: Efficient Networks for Universal Audio Source Separation,” in
2020
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Y. Luo, Z. Chen, and T. Yoshioka, “Dual-Path RNN: Efficient Long Sequence Modeling for Time-Domain Single-Channel Speech Separation,” in
2020
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E. Nachmani, Y. Adi, and L. Wolf, “Voice Separation with An Unknown Number of Multiple Speakers,” in
2020
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J. Chen, Q. Mao, and D. Liu, “Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation,” in
2020
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K. Tan and D. Wang, “Learning Complex Spectral Mapping With Gated Convolutional Recurrent Networks for Monaural Speech Enhancement,”
2020
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Z.-Q. Wang and D. Wang, “Deep Learning Based Target Cancellation for Speech Dereverberation,”
2020
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——, “On The Compensation Between Magnitude and Phase in Speech Separation,”
2021
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A. Pandey and D. Wang, “Dense CNN with Self-Attention for Time-Domain Speech Enhancement,”
2021
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K. Zmolikova, M. Delcroix, D. Raj, S. Watanabe
2021
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S. Qian, L. Gao, H. Jia, and Q. Mao, “Efficient Monaural Speech Separation With Multiscale Time-Delay Sampling,” in
2022
Closest in time.
J. Rixen and M. Renz, “SFSRNet: Super-Resolution for Single-Channel Audio Source Separation,” in
2022
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2022
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L. Yang, W. Liu, and W. Wang, “TFPSNet: Time-Frequency Domain Path Scanning Network for Speech Separation,” in
2022
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F. Dang, H. Chen, and P. Zhang, “DPT-FSNet: Dual-Path Transformer Based Full-Band and Sub-Band Fusion Network for Speech Enhancement,” in
2022
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K. Tan, Z.-Q. Wang, and D. Wang, “Neural Spectrospatial Filtering,”
2022
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S. Lutati, E. Nachmani, and L. Wolf, “Sepit approaching a single channel speech separation bound,”
2022
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Y.-J. Lu, X. Chang, C. Li, W. Zhang
2022
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