7 papers
I-DCCRN-VAE: An Improved Deep Representation Learning Framework for Complex VAE-based Single-channel Speech Enhancement
Jiatong Li, Simon Doclo
Recently, a complex variational autoencoder (VAE)-based single-channel speech enhancement system based on the DCCRN architecture has been proposed. In this system, a noise suppress…
Binaural Localization Model for Speech in Noise
Vikas Tokala, Eric Grinstein, Rory Brooks +4
Binaural acoustic source localization is important to human listeners for spatial awareness, communication and safety. In this paper, an end-to-end binaural localization model for…
Binaural Speech Enhancement Using Complex Convolutional Recurrent Networks
Vikas Tokala, Eric Grinstein, Mike Brookes +3
From hearing aids to augmented and virtual reality devices, binaural speech enhancement algorithms have been established as state-of-the-art techniques to improve speech intelligib…
Comparison of Knowledge Distillation Methods for Low-complexity Multi-microphone Speech Enhancement using the FT-JNF Architecture
Robert Metzger, Mattes Ohlenbusch, Christian Rollwage +1
Multi-microphone speech enhancement using deep neural networks (DNNs) has significantly progressed in recent years. However, many proposed DNN-based speech enhancement algorithms c…
Incremental Averaging Method to Improve Graph-Based Time-Difference-of-Arrival Estimation
Klaus Brümann, Kouei Yamaoka, Nobutaka Ono +1
Estimating the position of a speech source based on time-differences-of-arrival (TDOAs) is often adversely affected by background noise and reverberation. A popular method to estim…
Soft-Constrained Spatially Selective Active Noise Control for Open-fitting Hearables
Tong Xiao, Reinhild Roden, Matthias Blau +1
Recent advances in spatially selective active noise control (SSANC) using multiple microphones have enabled hearables to suppress undesired noise while preserving desired speech fr…