Dilated Semi-Dense Convolutional Network for Multichannel Speech Enhancement
Abstract
This paper proposes a dilated semi-dense convolutional network for multichannel speech enhancement using machine learning. The baseline, SpatialNet, employs a Conformer for narrowband processing but uses a simple 3-layer CNN block, limiting local information extraction. To improve performance, we replace the Convolutional Neural Network (CNN) block with dilated convolution, dilated dense convolution, and the proposed dilated semi-dense convolution.
Fields of Study & Subjects
Speech and Audio Processing
Advanced Adaptive Filtering Techniques
Speech Recognition and Synthesis
Publication details
- Journal / source
- IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences
- Volume
- E109.A
- Issue
- 6
- Pages
- 1165–1169
- Publication date
- 6 January 2026
- Language
- EN