December 12, 2017
Comments Off on A Regression Approach to Single-Channel Speech Separation Via High- Resolution Deep Neural Networks
Posted in: IEEE 2017, Power Electronics
A Regression Approach to Single-Channel Speech Separation Via High-Resolution Deep Neural Networks Abstract: We propose a novel data-driven approach to single-channel speech separation based on deep neural networks (DNNs) to directly model the highly nonlinear relationship between speech features of a mixed signal containing a target speaker and other interfering speakers. We focus our discussion […]
December 12, 2017
Comments Off on Two Efficient Lattice Rescoring Methods Using Recurrent Neural Network Language Models
Posted in: IEEE 2017, Power Electronics
Two Efficient Lattice Rescoring Methods Using Recurrent Neural Network Language Models Abstract: An important part of the language modelling problem for automatic speech recognition (ASR) systems, and many other related applications, is to appropriately model long-distance context dependencies in natural languages. Hence, statistical language models (LMs) that can model longer span history contexts, for example, […]