3 accepted papers
Despite the significant progress of deep learning based speech separation methods, it remains challenging to extract and track the speech from target speakers, especially in a single-channel multiple speaker situation. Previously, the authors proposed a source-aware context network to exploit the te…
Deep learning based approaches have achieved promising performance in speaker-dependent single-channel multispeaker speech separation. However, partly due to the label permutation problem, they may encounter difficulties in speaker-independent conditions. Recent methods address this problem by some…
Transfer learning methods have demonstrated state-of-the-art performance on various small-scale image classification tasks. This is generally achieved by exploiting the information from an ImageNet convolution neural network (ImageNet CNN). However, the transferred CNN model is generally with high c…