Comments (2)
ycmin95
commented on August 23, 2024
Thanks for your attention to our work, the choice of init number (e.g., 20000) does not change the recognition results. As we only use the decoded indexes for predicition. It seems like vocabulary in ctcdecode can help word segmentation (space_id), which does not exist in current CSLR dataset.
Similar issue about the alignment results.
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blankspark
commented on August 23, 2024
感谢您的回复！我将尝试实现
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Related Issues (20)
- Error when i run the training part main.py HOT 1
- unable to run successfully when I run main.py HOT 1
- unable to successfully install CTC HOT 5
- Detailed code running steps HOT 19
- Visualizing the predicted alignments HOT 1
- unable to run these repository on google colab HOT 1
- Data augmention error HOT 4
- about the feature extractor architecture HOT 6
- Successfully inference, but unable to train HOT 3
- Visualize Epoch vs Loss HOT 1
- Hardware and Software Specifications for this research. HOT 3
- Gloss Segment Boundary Assignment Algorithm (GSBA) HOT 1
- Does your PHOENIX-2014-T dataset have /1/ folder? HOT 1
- model or model.parameters()? HOT 2
- Does your model produce different results each time it is run? HOT 4
- Training the baseline (without VAC, SMKD) HOT 2
- How can I use a trained model to test a video? HOT 1
- unable to reconize any word but the loss is decreasing??? HOT 1
- Does preprocess.sh have an effect if using datasets other than phoneix? HOT 1
- IndexError in DataLoader Worker Process with Custom Dataset
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