Comments (1)
Hi,
The config file base_lrs3_30h.yaml
is for lip reading. In fine-tuning an ASR model, have you tuned hyperparameters, mostly: freeze_finetune_updates
, max_update
, warmup_steps
and decay_steps
?
One other thing to note is that 5.4 in table 4 of [2] is obtained with a pre-trained audio HuBERT model. Specifically, you need to take the pre-trained AV-HuBERT of penultimate iter to generate cluster and pre-train an audio-HuBERT (by setting modalities
to ['audio']
in pre-training) using those clusters. If you directly fine-tune an AV-HuBERT for ASR (where the ASR result in [2] is obtained), the result can be a bit different. In our experiments, it is slightly worse but the gap is not large.
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Related Issues (20)
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