Yang Sun
Newcastle University
27 Papers
65 Citations
Yang Sun is an academic researcher from Newcastle University. The author has contributed to research in topics: Computer science & TIMIT. The author has an hindex of 6, co-authored 22 publications. Previous affiliations of Yang Sun include University of Oxford.
Chat about Author
Papers
Monaural Source Separation in Complex Domain With Long Short-Term Memory Neural Network
TL;DR: The complex signal approximation (cSA), which is operated in the complex domain to utilize the phase information of the desired speech signal to improve the separation performance, is proposed.
Two-Stage Monaural Source Separation in Reverberant Room Environments Using Deep Neural Networks
TL;DR: A two-stage approach with two DNN-based methods to address dereverberation and separation in the monaural source separation problem, which outperform the state-of-the-art specifically in highly reverberant room environments.
Convolutional fusion network for monaural speech enhancement.
TL;DR: In this article, a new convolutional fusion network (CFN) is proposed for monaural speech enhancement by improving model performance, inter-channel dependency, information reuse and parameter efficiency.
18
A Multi-Scale Feature Recalibration Network for End-to-End Single Channel Speech Enhancement
TL;DR: In this article, a multi-scale feature recalibration convolutional encoder-decoder with bidirectional gated recurrent unit (BGRU) architecture was proposed for end-to-end speech enhancement.
Underdetermined source separation using time-frequency masks and an adaptive combined Gaussian-Student's t probabilistic model
Yang Sun,Waqas Rafique,Jonathon A. Chambers,Syed Mohsen Naqvi +3 more
- 01 Mar 2017
TL;DR: A Gaussian-Student's t distribution combined mixture model is exploited for robust binaural speech separation and the objective performance measure signal to distortion ratio (SDR) confirms the improvement and robustness of the proposed method.
15