Implementation of Real-Time Speech Separation Model Using Time-Domain Audio Separation Network (TasNet) and Dual-Path Recurrent Neural Network (DPRNN)

Abstract

Abstract The purpose of this research is to develop a model that is able to perform real-time speaker independent multi-talker speech separation task in time-domain using Time-Domain Audio Separation Network (TasNet) and Dual-Path Recurrent Neural Network (DPRNN). This research will conduct experiments on some RNN architectures, number of batch size, and optimizers as hyper-parameters in order to implement TasNet and DPRNN. This research also try to analyze the impact of these hyperparameters setup on model performance. The expected result of this research is a more accurate model and lower latency to complete speaker independent multi-talker speech separation task in real-time than previous research model.