Comments (4)
Are there some special tricks used for model training?
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Could adding data improve the generalization ability of the model?
The training data of voca is only 40 sentences per person, which can not be enough.
from voca.
Does audio data have requirements for speech speed, volume, pitch and timbre?
from voca.
We share the training data and the whole training code, all "tricks" are part of the code. The general problem of the error not reducing on the validation set is the big difference in speaking style between subjects. I recommend using the validation set to qualitatively assess the training progress, the quantitative evaluation is less meaningful.
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Related Issues (20)
- is the eye blink useful for FLame 2020 model ? HOT 3
- "video.mp4" only has speech but no images ? HOT 4
- Windows support and installing MPI-IS / mesh HOT 1
- Should --uv_template_fname be the same as --template_fname in run_voca.py?
- can you give pretrained_models?
- Initialization Of Decoder Layer
- Problem of training voca
- How to control expression in the edit_sequence.py? HOT 2
- Can I train this on custom dataset?
- Unknown mesh file format. HOT 1
- Training with new Tensorflow Version
- Unsolved reference tfbody
- Missing data on subj_seq_to_idx.pkl file HOT 1
- If I want to control the expression of the eyes, how should I set the parameters?
- I haven't found the 'output_graph.pb' file, where can I get it?
- dataset/voca_face_former/templates.pkl not found HOT 1
- Where to download npy and pkl files HOT 1
- Inference other .ply files
- Hot to get blink_exp_betas for another flame version?
- Is the the vertice's coordinates in registered data the same as it in data_verts.npy in training data?
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