Comments (7)
Xiaobin-Rong
commented on June 5, 2024
1
@limmark21
GTCRN_A_Speech_Enhancement_Model_Requiring_Ultralow_Computational_Resources.pdf
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Xiaobin-Rong
commented on June 5, 2024
Yes, the paper has not been publicly available online. In fact, this is the paper I submitted to ICASSP 2024 this year, and it is currently under review. If the review process is successful, I will update it here promptly. Thanks for your ongoing interest and support!
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ltcxjtu
commented on June 5, 2024
I'm looking forward,the parameter quantity of the Model is really attractive.
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Xiaobin-Rong
commented on June 5, 2024
@ltcxjtu
感谢你的关注，paper已经见刊: https://ieeexplore.ieee.org/document/10448310
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limmark21
commented on June 5, 2024
could you please share pdf file, i cannot download paper from link(
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limmark21
commented on June 5, 2024
THANK YOU SO MUCH, I just have started to explore speech enhancement models. But your gtcrn made a big impression on me!
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Xiaobin-Rong
commented on June 5, 2024
@limmark21
You're welcome, and thank you for your kind words! I wish you smooth progress in your research.
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Related Issues (14)
- could you share the paper link? Thanks HOT 12
- 请问您排查到onnxsim.simplify导出时的问题所在了吗 HOT 3
- 提问，关于SFE模块使用nn.unfold的目的。 HOT 3
- 请教一下Temporal Recurrent Attention的作用 HOT 2
- 请问，训练代码在之后会开源吗 HOT 3
- 请问，如果想扩展一下，用计算量换模型的性能，应该朝哪个方向调参？ HOT 4
- Is this paper available for download online? HOT 1
- LIcense? HOT 1
- 请问，模型低信噪比场景听感难受问题 HOT 4
- Loss gets nan HOT 14
- 48k_training HOT 1
- 对比模型的计算量问题 HOT 3
- GTCRN的look-ahead是70ms吗 HOT 2
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