Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation
Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation
The dominant speech separation models are based on complex recurrent or convolution neural network that model speech sequences indirectly conditioning on context, such as passing information through many intermediate states in recurrent neural network, leading to suboptimal separation performance.In this paper, we propose a dual-path transformer network (DPT-Net) for end-to-end …