Comments (2)
Hi,
Table 1 are the result of CTC decoding. Our best result is obtained with S2S after training all iterations. But we did not find S2S always outperforms CTC in the entire process. Specifically for CTC decoding, we use 4-gram language model for decoding, similar to the original HuBERT. Besides, we use phone as the target unit during fine-tuning. You may find more details about the hyperparameters for CTC decoding in section A.4 of the paper.
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Thanks for your quick reply! I'll keep following the rest iters to see if the final result is right.
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Related Issues (20)
- ImportError: cannot import name 'metrics' from 'fairseq' (unknown location) HOT 5
- preparation-cnn_face_detector HOT 1
- Question about the use of CMUDict in CTC finetuning HOT 3
- issue during 1st iteration of pretraining HOT 1
- How to train a LM used for decoding HOT 2
- Error in step 2 of preprocessing, what values to put in ${rank} and ${nshard} HOT 5
- non-deterministic results when decoding with noises HOT 5
- Fixing Colab
- How to finetune on AVSR setting? HOT 3
- What's the difference between A/MFCC→A and A/MFCC→AV in the paper? HOT 1
- Value expected for ${layer}-th transformer layer of a trained AV-HuBERT model saved at ${ckpt_path} HOT 1
- Format of pretrain data in the LRS3 dataset HOT 1
- Cannot register duplicate model (av_hubert) HOT 1
- Extraction of features with AV HuBERT HOT 4
- A problem of traning a new model HOT 2
- Release of clustering models HOT 3
- How to decode without any label files HOT 2
- Request for Base model pre-trained on multi-lingual data HOT 1
- Error loading AVSR model HOT 3
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