Comments (2)
Can you take a look at Figure 1 of this paper https://arxiv.org/pdf/2305.10790.pdf to see an example to mean pool over the frequency dimension to get representation in temporal order? Code implementation is here:
However, the code is for "no-overalp" patch split, apply to "overlapped" patch split (in this repo) requires some change.
You can also check SSAST which supports naive temporal order representation. https://github.com/YuanGongND/ssast
When you have temporal order representation, you can do seq2seq tasks, e.g., add a CTC on top of the temporal representations.
-Yuan
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I got the results I wanted by removing line 184 in https://github.com/YuanGongND/ast/blob/master/src/models/ast_models.py and setting t_stride = 1, I think that should give me a working seq2seq classification. I will take a look at the links you provided as well!
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Related Issues (20)
- how to use my own dataset HOT 3
- AST Audioset Training Time and Hardware HOT 2
- After fine-tune a 3-class dataset, how to load its fine-tuned weighted to update pre-trained ast model? HOT 7
- CPU memory increase while training HOT 6
- Fine tuning AST model to Music Emotion Classification Overfit HOT 3
- How can I adapt the pretrained AST model to fit my own dataset HOT 6
- ESC-50-master zip file location has changed HOT 2
- Installing requirements issues HOT 1
- When I download the pretrained model with stride=16, I need to change `fstride` and `tstride` in the source code from 10 to 16. Besides these changes, what else do I need to adjust?
- Different audio sample size for fine-tuning the model gives overfitting issue HOT 1
- training MAP HOT 2
- One question regarding the linear projection of AST. HOT 1
- Inquiry Regarding Audio Spectrogram Transformer HOT 2
- self-contained Google Colab script error HOT 2
- Ask for help HOT 1
- some questions when reproducing your results HOT 2
- csv error HOT 1
- AssertionError: choose a window size 400 that is [2, 1] HOT 2
- Discrepancy in Model Performance Using HuggingFace Pipeline Utility HOT 5
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