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My Own Little Work

Now just work following papers and two works, ideally.

The first one is reconstructed from Conv-TasNet of funcwj's work, and the paper is [1].
The second is about another, look more in below's paper.[2]

Some data processing code is inspired by pchao6's work.

2019.09.20
There will be also another speech separation work[3]'s implementation by recursive selecting speaker in the near future.

Reference

[1] Luo Y, Mesgarani N. TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation[J]. arXiv preprint arXiv:1809.07454, 2018.

[2] Kinoshita K, Drude L, Delcroix M, et al. Listening to Each Speaker One by One with Recurrent Selective Hearing Networks[C]. international conference on acoustics, speech, and signal processing, 2018: 5064-5068.

[3] Takahashi, N., Parthasaarathy, S., Goswami, N., Mitsufuji, Y. (2019) Recursive Speech Separation for Unknown Number of Speakers. Proc. Interspeech 2019, 1348-1352, DOI: 10.21437/Interspeech.2019-1550.

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