-
Notifications
You must be signed in to change notification settings - Fork 102
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Necessary preprocessing for inference wav data #12
Comments
For source wav, it is better to denoise it if it is too noisy, normalize it if the volume is too loud or too low; for target wav, it is better to trim its silent segments. |
@OlaWod Thanks a lot for the answer! Understood. I'll try the above. Also, would there be a preferred sampling rate for both source and target wav? |
16kHz |
Great, thanks for your response :) |
For the target wav, do you have recommendations as to the length? Does performance of the model improve/deteriorate with longer target wavs? If so, where's the sweet spot? |
haven't explored yet, but I think longer target wav might contain longer silent, which can deteriorate the performance. I think the sweet spot is a target wav that is not too short and contain almost no silent. |
Hi, Thanks for the great work! I'm trying to test the inference part with my own wav file but the output quality is less than I expected and I'm suspecting it's due to the input file.
Could you give me some instruction for how to preprocess the input source/target wav?
The text was updated successfully, but these errors were encountered: