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license: mit
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The model consumes a lot of resources for inference, so its inference code was modified to split the input into smaller parts, which results in longer inference time.<br>
The model might not have been fully trained, so the quality may not be optimal. It is currently paused at checkpoint 22080.<br>
The djcm.pt model has been trimmed by removing to_wav since it is not used.
Training with the original DJCM code (WIN LENGTH 2048 and HOP LENGTH 320)
| index | sdr±std | gnsdr | rpa±std | rca±std | oa±std |
|-------|-------------------|-------------|-------------------|-------------------|--------------------|
| 414 | 5.83±2.09 | 2.82 | 81.52±13.59 | 84.06±10.77 | 78.85±10.99 |
| 828 | 7.78±1.86 | 4.77 | 90.73±7.32 | 91.91±6.13 | 88.2±6.61 |
| 1242 | 8.67±1.71 | 5.65 | 90.65±7.33 | 91.37±6.3 | 89.57±6.09 |
| 1656 | 8.94±1.82 | 5.92 | 92.65±5.61 | 93.14±5.09 | 87.16±6.68 |
| 2484 | 10.16±2.05 | 7.15 | 92.17±5.9 | 92.42±5.67 | 91.04±5.16 |
| 2898 | 10.03±1.92 | 7.02 | 92.74±5.74 | 93.08±5.57 | 89.4±5.59 |
| 3312 | 10.56±1.83 | 7.55 | 92.85±5.57 | 93.18±5.25 | 91.85±4.82 |
| 4554 | 11.28±2.19 | 8.27 | 93.57±5.42 | 93.81±5.18 | 92.07±4.62 |
| 5796 | 11.27±2.06 | 8.25 | 93.59±5.53 | 93.97±5.0 | 91.65±5.08 |
| 6624 | 11.57±2.05 | 8.56 | 93.86±5.16 | 94.04±4.98 | ****92.93±4.26*** |
| 7038 | 11.63±1.98 | 8.62 | 94.05±4.82 | 94.29±4.44 | 91.79±4.63 |
| 7452 | 11.0±1.88 | 7.99 | 93.43±5.39 | 93.68±4.89 | 91.48±5.16 |
| 7866 | 11.55±2.22 | 8.54 | 93.15±5.43 | 93.37±5.14 | 91.62±4.88 |
| 8280 | 11.76±2.2 | 8.75 | 93.7±5.26 | 93.88±4.99 | 92.62±4.35 |
| 8694 | ****12.25±2.16*** | ****9.23*** | 93.32±5.45 | 93.49±5.15 | 92.55±4.3 |
| 9086 | 9.13±1.34 | 6.12 | 94.76±4.0 | 95.16±3.56 | 70.17±9.26 |
| 9499 | 8.75±1.19 | 5.74 | 95.06±3.76 | 95.49±3.4 | 71.86±9.23 |
| 9912 | 9.16±1.16 | 6.15 | 95.48±3.68 | 95.73±3.46 | 73.65±8.35 |
| 10325 | 8.66±0.97 | 5.65 | 95.35±3.6 | 95.72±3.06 | 74.58±7.88 |
| 10738 | 8.2±0.85 | 5.19 | ****95.58±3.52*** | ****95.87±3.23*** | 75.25±7.87 |
Training with my modified DJCM code (WIN LENGTH 1024 and HOP LENGTH 160)
With a mixture of 5 datasets, each set is extracted 20% for testing.
| index | sdr±std | gnsdr | rpa±std | rca±std | oa±std |
|-------|-------------------|-------------|-------------------|-------------------|--------------------|
| 11776 | NONE | NONE | 88.87±7.25 | 89.9±6.74 | 34.2±22.21 |
| 14720 | NONE | NONE | 89.09±7.47 | 90.15±6.88 | 39.83±24.26 |
| 17664 | NONE | NONE | 89.47±7.16 | 90.44±6.65 | 37.56±25.77 |
| 20608 | NONE | NONE | 90.49±6.63 | 91.29±6.24 | 37.71±25.67 |
| 22080 | NONE | NONE | ****90.65±6.69*** | ****91.56±6.15*** | ****41.01±24.69*** |
Training Dataset: https://huggingface.co/datasets/AnhP/Mir-1k-use-DJCM-training/resolve/main/dataset.zip<br>
Inference Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/inference.py<br>
Training Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/train.py<br>
Export Small Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/export_small_model.py<br>
Export Onnx Code: https://github.com/PhamHuynhAnh16/DJCM/blob/main/export_onnx.py |