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README.md
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@@ -30,7 +30,19 @@ cd chest_falsetto
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```
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## Results
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<style>
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#falsetto td {
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vertical-align: middle !important;
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@@ -43,15 +55,15 @@ A fine-tuning result of MaxViT-T on CQT:
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<table id="falsetto">
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<tr>
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<th>Loss curve</th>
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<td><img src="https://www.modelscope.cn/models/ccmusic-database/chest_falsetto/resolve/master/
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</tr>
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<tr>
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<th>Training and validation accuracy</th>
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<td><img src="https://www.modelscope.cn/models/ccmusic-database/chest_falsetto/resolve/master/
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</tr>
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<tr>
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<th>Confusion matrix</th>
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<td><img src="https://www.modelscope.cn/models/ccmusic-database/chest_falsetto/resolve/master/
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</tr>
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</table>
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```
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## Results
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| Backbone | Mel | CQT | Chroma |
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| :---------------: | :-------------------------: | :---------: | :---------: |
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| Swin-S V2 | **_0.968_** | 0.268 | **_0.268_** |
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| MaxViT-T | 0.820 | **_0.933_** | 0.250 |
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| | | | |
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| AlexNet | [**_0.994_**](#best-result) | **_0.963_** | **_0.586_** |
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| ShuffleNet V2 2.0 | 0.939 | 0.669 | 0.222 |
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| GoogleNet | 0.983 | 0.274 | 0.292 |
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| MNASNet-A3 | 0.756 | 0.260 | 0.320 |
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| SqueezeNet 1.1 | 0.963 | 0.900 | 0.378 |
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| Average | 0.918 | 0.610 | 0.331 |
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### Best Result
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<style>
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#falsetto td {
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vertical-align: middle !important;
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<table id="falsetto">
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<tr>
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<th>Loss curve</th>
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<td><img src="https://www.modelscope.cn/models/ccmusic-database/chest_falsetto/resolve/master/alexnet_mel_2024-07-30_11-52-53/loss.jpg"></td>
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</tr>
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<tr>
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<th>Training and validation accuracy</th>
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<td><img src="https://www.modelscope.cn/models/ccmusic-database/chest_falsetto/resolve/master/alexnet_mel_2024-07-30_11-52-53/acc.jpg"></td>
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</tr>
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<tr>
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<th>Confusion matrix</th>
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<td><img src="https://www.modelscope.cn/models/ccmusic-database/chest_falsetto/resolve/master/alexnet_mel_2024-07-30_11-52-53/mat.jpg"></td>
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</tr>
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</table>
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