Skip to content
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

Lookahead in compute_rnn (c++) #49

Open
aaronhsueh0506 opened this issue May 10, 2022 · 3 comments
Open

Lookahead in compute_rnn (c++) #49

aaronhsueh0506 opened this issue May 10, 2022 · 3 comments

Comments

@aaronhsueh0506
Copy link

Hi Noh,

We queue a buffer when I was training the model (maybe 500 frames), but I think the funciton compute_rnn looks like a frame-in-frame-out flow.
My question is, is there no need to prepare a buffer for inference?

Thanks,
Aaron

@jzi040941
Copy link
Owner

Hi there,
rnnoise_process_frame is called while inference step,
in that function it calls compute_frame_features function which is stacking input X to comb_buf and pitch_buf.

so there's no need to add buffer in compute_rnn.

I'm not sure this is your intention of your question. feel free to leave comments more if is not correct

@aaronhsueh0506
Copy link
Author

Hi Noh,

Thanks for your reply.
Yes, I am confused about buffer.
So we only feed a frame length data into the neural network?
Because I am trying to construct the real-time flow and the frame length is a factor related to the complexity of the model.

Thanks,
Aaron

@jzi040941
Copy link
Owner

jzi040941 commented May 27, 2022

Yes, you need feed features(Ex[34], Exp[34], T, corr) extracted from frame length audio to neural network
it's possible to run it in realtime frame by frame

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants