@ptrblck I have create repository on GitHub which consist of script and sample data. code 3
Below are some basic detail about my architecture.
The architecture is for multiclass classification. The full architecture I have already posted.
The architecture consist of TDNN layers which works at frame level (input data is of shape (200, 20)). StatsPool layer computes mean and std and combination of both gives us single 3000 dimensional vector. FInally, three Linear layers where last linear layers have 1739 output as I have that many number of classes. I have used CrossEntropyLoss as criterian.
Please let me know if you have any query regarding architecture and data I have used.