mpariente commited on
Commit
5598825
·
1 Parent(s): 21c66c3

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +13 -6
README.md CHANGED
@@ -6,21 +6,21 @@ tags:
6
  datasets:
7
  - Wsj0MixVar
8
  - sep_clean
 
9
  inference: false
10
  ---
11
  ## Asteroid model
12
 
13
  ## Description:
14
- Code: The code corresponding to this model card can be found in the asteroid toolkit @ https://github.com/asteroid-team/asteroid, under "egs/wsj0-mix-var", where the recipe is stored.
15
 
16
- Paper: "Multi-Decoder DPRNN: High Accuracy Source Counting and Separation",
17
- Junzhe Zhu, Raymond Yeh, Mark Hasegawa-Johnson. ICASSP(2021). https://ieeexplore.ieee.org/document/9414205
18
 
19
- Summary: This model achieves SOTA on the problem of source separation with an unknown number of speakers. It uses multiple decoder heads(each tackling a distinct number of speakers), in addition to a classifier head that selects which decoder head to use.
20
 
21
- Demo Page: https://junzhejosephzhu.github.io/Multi-Decoder-DPRNN/
22
 
23
- Original research repo is at https://github.com/JunzheJosephZhu/MultiDecoder-DPRNN
24
 
25
  This model was trained by Joseph Zhu using the wsj0-mix-var/Multi-Decoder-DPRNN recipe in Asteroid.
26
  It was trained on the `sep_count` task of the Wsj0MixVar dataset.
@@ -69,3 +69,10 @@ loss:
69
  ```yaml
70
  'Accuracy': 0.9723333333333334, 'P-Si-SNR': 10.36027378628496
71
  ```
 
 
 
 
 
 
 
 
6
  datasets:
7
  - Wsj0MixVar
8
  - sep_clean
9
+ license: cc-by-sa-3.0
10
  inference: false
11
  ---
12
  ## Asteroid model
13
 
14
  ## Description:
15
+ - Code: The code corresponding to this pretrained model can be found in [this asteroid recipe](https://github.com/asteroid-team/asteroid/tree/master/egs/wsj0-mix-var/Multi-Decoder-DPRNN).
16
 
17
+ - [Paper](https://ieeexplore.ieee.org/document/9414205): "Multi-Decoder DPRNN: High Accuracy Source Counting and Separation", Junzhe Zhu, Raymond Yeh, Mark Hasegawa-Johnson. ICASSP(2021).
 
18
 
19
+ - Summary: This model achieves SOTA on the problem of source separation with an unknown number of speakers. It uses multiple decoder heads(each tackling a distinct number of speakers), in addition to a classifier head that selects which decoder head to use.
20
 
21
+ - [Demo Page](https://junzhejosephzhu.github.io/Multi-Decoder-DPRNN/)
22
 
23
+ - [Original research repo](https://github.com/JunzheJosephZhu/MultiDecoder-DPRNN)
24
 
25
  This model was trained by Joseph Zhu using the wsj0-mix-var/Multi-Decoder-DPRNN recipe in Asteroid.
26
  It was trained on the `sep_count` task of the Wsj0MixVar dataset.
 
69
  ```yaml
70
  'Accuracy': 0.9723333333333334, 'P-Si-SNR': 10.36027378628496
71
  ```
72
+
73
+ ### License notice:
74
+ This work "MultiDecoderDPRNN" is a derivative of [CSR-I (WSJ0) Complete](https://catalog.ldc.upenn.edu/LDC93S6A)
75
+ by [LDC](https://www.ldc.upenn.edu/), used under [LDC User Agreement for
76
+ Non-Members](https://catalog.ldc.upenn.edu/license/ldc-non-members-agreement.pdf) (Research only).
77
+ "MultiDecoderDPRNN" is licensed under [Attribution-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-sa/3.0/)
78
+ by Joseph Zhu.