A Cross-Task Transfer Learning Approach To Adapting Deep Speech Enhancement Models To Unseen Background Noise Using Paired Senone Classifiers

This video program is a part of the Premium package:

A Cross-Task Transfer Learning Approach To Adapting Deep Speech Enhancement Models To Unseen Background Noise Using Paired Senone Classifiers


  • IEEE MemberUS $11.00
  • Society MemberUS $0.00
  • IEEE Student MemberUS $11.00
  • Non-IEEE MemberUS $15.00
Purchase

A Cross-Task Transfer Learning Approach To Adapting Deep Speech Enhancement Models To Unseen Background Noise Using Paired Senone Classifiers

1 view
  • Share
Create Account or Sign In to post comments
We propose an environment adaptation approach that improves deep speech enhancement models via minimizing the Kullback- Leibler divergence between posterior probabilities produced by a multi-condition senone classifier (teacher) fed with noisy speech feat
We propose an environment adaptation approach that improves deep speech enhancement models via minimizing the Kullback- Leibler divergence between posterior probabilities produced by a multi-condition senone classifier (teacher) fed with noisy speech feat