Dasformer: Deep Alternating Spectrogram Transformer For Multi/Single-Channel Speech Separation
Author:
Affiliation:
1. Institute of Acoustics,Chinese Academy of Sciences,Beijing,China
2. Microsoft Research Asia,Beijing,China
3. Microsoft Corporation,Redmond,WA,USA,98052
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10094559/10094560/10095037.pdf?arnumber=10095037
Reference22 articles.
1. WHAMR!: Noisy and Reverberant Single-Channel Speech Separation
2. TFPSNet: Time-Frequency Domain Path Scanning Network for Speech Separation
3. DPT-FSNet: Dual-Path Transformer Based Full-Band and Sub-Band Fusion Network for Speech Enhancement
4. Compute and Memory Efficient Universal Sound Source Separation
5. Conformer: Convolution-augmented Transformer for Speech Recognition
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Opine: Leveraging a Optimization-Inspired Deep Unfolding Method for Multi-Channel Speech Enhancement;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
2. CST-Former: Transformer with Channel-Spectro-Temporal Attention for Sound Event Localization and Detection;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
3. SpatialNet: Extensively Learning Spatial Information for Multichannel Joint Speech Separation, Denoising and Dereverberation;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024
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