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

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

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IEEE ICASSP 2020 Virtual Conference May 2020

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

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

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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