input/output dimension & model complexity

[saekisongalag]

Thank you for sharing! I can successfuly run the demo code and get the denoised and beamformed audio =]

However, I wondered that whether the input dimension is fixed or at least longer than a pre-defined length. It failed when the len_input and len_pad were set to 512 and 0, respectively.

I also calculated the run time during each iteration of inferencing (input was a 3-sec audio ). It took about 2 to 3 sec in the PMF prediction step and it took about 40 to 50 sec to execute update_beamform_coef_with_weights function

Is it possible that the input and output is a short frame size (20~30 ms) and the run time can be decreased to meet real-time criteria?