Multi-Speaker Localization Using Convolutional Neural Network Trained with Noise
Sound
2017-12-13 v1 Audio and Speech Processing
Machine Learning
Abstract
The problem of multi-speaker localization is formulated as a multi-class multi-label classification problem, which is solved using a convolutional neural network (CNN) based source localization method. Utilizing the common assumption of disjoint speaker activities, we propose a novel method to train the CNN using synthesized noise signals. The proposed localization method is evaluated for two speakers and compared to a well-known steered response power method.
Cite
@article{arxiv.1712.04276,
title = {Multi-Speaker Localization Using Convolutional Neural Network Trained with Noise},
author = {Soumitro Chakrabarty and Emanuël A. P. Habets},
journal= {arXiv preprint arXiv:1712.04276},
year = {2017}
}
Comments
Presented at Machine Learning for Audio Processing (ML4Audio) Workshop at NIPS 2017