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

Pre-trained Model and Code for Audio-Visual Wake Work Spotting #1

Closed
saurabh-shandilya opened this issue Sep 20, 2022 · 4 comments
Closed

Comments

@saurabh-shandilya
Copy link

Hi,

Thanks for sharing your paper and code. The results in the paper look impressive. If I want to reproduce these results - is there a pre-trained model (tf or tflite) available? Some steps are mentioned in https://github.com/LianjiaTech/athena/tree/main/examples/kws but not sure where I can find the folder athena_wakeup and files athena_wakeup/main.py, athena_wakeup/test_main.py, athena_wakeup/test_main_av.py?

@JianweiSun007
Copy link
Collaborator

Hi, thanks for your care, the examples/kws is updated, and the pre-trained models of KWS are not released at this time.

@saurabh-shandilya
Copy link
Author

@JianweiSun007 Thanks a lot for a quick response. Really appreciate it!

@saurabh-shandilya
Copy link
Author

saurabh-shandilya commented Sep 22, 2022

@JianweiSun007 Just one more clarification. Is the main.py script mentioned for training same as that in https://github.com/LianjiaTech/athena/blob/main/athena/main.py? Since the model is not released, I would like to try the training steps mentioned in the updated README. Thanks once again.

@JianweiSun007
Copy link
Collaborator

Yes, you can use this https://github.com/LianjiaTech/athena/blob/main/athena/main.py script.

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