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https://github.com/funcwj/uPIT-for-speech-separation
Speech separation with utterance-level PIT experiments
https://github.com/funcwj/uPIT-for-speech-separation
pit pytorch speech-separation
Last synced: 3 months ago
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Speech separation with utterance-level PIT experiments
- Host: GitHub
- URL: https://github.com/funcwj/uPIT-for-speech-separation
- Owner: funcwj
- Created: 2018-06-22T04:08:07.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2018-07-12T09:29:59.000Z (over 6 years ago)
- Last Synced: 2024-08-02T07:14:11.746Z (6 months ago)
- Topics: pit, pytorch, speech-separation
- Language: Python
- Size: 38.1 KB
- Stars: 101
- Watchers: 9
- Forks: 39
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-speech-enhancement - [Code
README
## Speech Separation with uPIT
Speech separation with utterance-level PIT(Permutation Invariant Training)
### Requirements
see [requirements.txt](requirements.txt)
### Usage
1. Generate dataset using [create-speaker-mixtures.zip](http://www.merl.com/demos/deep-clustering/create-speaker-mixtures.zip)
2. Prepare cmvn, .scp and configure experiments in .yaml files
3. Training:
```shell
./run_pit.py --config $conf --num-epoches 100 > $checkpoint/train.log 2>&1 &
```
4. Inference:
```
./separate.py --dump-dir cache $mdl_dir/train.yaml $mdl_dir/epoch.40.pkl egs.scp
```
### Experiments
| Configure | Mask | Epoch | FM | FF | MM | FF/MM | AVG |
| :-------: | :--: | :---: | :---: | :--: | :--: | :---: | :--: |
| [config-1](conf/1.config.yaml) | AM-ReLU | 75 | 10.41 | 6.73 | 7.35 | 7.19 | 8.82 |
| [config-2](conf/2.config.yaml) | AM-sigmoid | 50 | 9.95 | 5.99 | 6.72 | 6.35 | 8.26 |
| [config-3](conf/3.config.yaml) | PSM-ReLU | 73 | 10.29 | 6.54 | 7.28 | 7.09 | 8.71 |
| [config-4](conf/4.config.yaml) | PSM-ReLU | 80 | 10.37 | 6.59 | 7.29 | 7.10 | 8.76 |
| [config-5](conf/5.config.yaml) | PSM-ReLU | 62 | 10.58 | 7.00 | 7.55 | 7.40 | 9.01 |
| [config-6](conf/6.config.yaml) | PSM-ReLU | 62 | 10.47 | 7.44 | 7.78 | 7.69 | 9.10 |
| [config-7](conf/7.config.yaml) | PSM-ReLU | 61 | 10.43 | 7.17 | 7.41 | 7.34 | 8.91 |
| - | IAM-oracle | - | 12.49 | 12.73 | 11.58 | 11.88 | 12.19 |
| - | IBM-oracle | - | 12.94 | 13.20 | 12.04 | 12.35 | 12.65 |
| - | IRM-oracle | - | 12.86 | 13.14 | 11.96 | 12.27 | 12.57 |
| - | PSM-oracle | - | 15.79 | 16.03 | 14.90 | 15.20 | 15.50 |
### Reference
* Kolbæk M, Yu D, Tan Z H, et al. Multitalker speech separation with utterance-level permutation invariant training of deep recurrent neural networks[J]. IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2017, 25(10): 1901-1913.