DNN-Based Online Speech Enhancement Using Multitask Learning and Suppression Rule Estimation

Most of the currently available speech enhancement algorithms use a statistical signal processing approach to remove the noise component from observed signals. The performance of these algorithms is thus dependent on the statistical assumptions they make about speech and noise signals, which are often inaccurate. In this work, we consider machine learning as an alternative, using deep neural networks to discover the transformation from noisy to clean speech. While DNNs are now the standard approach for acou