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This repository has been archived by the owner on Feb 6, 2024. It is now read-only.
So it looks like newer generation diffsinger models now have linguistic models that take in tokens, word divisions and word durations where the output is encoder_out and x_masks which then feed to the duration.onnx model
Example below(please tell me the if zeroes are needed in the below example)
results = linguistic_model.run(None, {
"tokens":[[26, 1, 22, 35, 11]] ,
"word_div": [[3,2,0,0,0]],
"word_dur": [[48,24,0,0,0]]
})
Happy to get your thoughts, thank you!
The text was updated successfully, but these errors were encountered:
This project is deprecated now. You can use OpenUTAU for DiffSinger to synthesis with ONNX models. Anyway, this is only a simple demo project, and you can extend it or even re-write it easily
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So it looks like newer generation diffsinger models now have linguistic models that take in tokens, word divisions and word durations where the output is encoder_out and x_masks which then feed to the duration.onnx model
Example below(please tell me the if zeroes are needed in the below example)
results = linguistic_model.run(None, {
"tokens":[[26, 1, 22, 35, 11]] ,
"word_div": [[3,2,0,0,0]],
"word_dur": [[48,24,0,0,0]]
})
Happy to get your thoughts, thank you!
The text was updated successfully, but these errors were encountered: