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arXiv · 1712.04276

Multi-Speaker Localization Using Convolutional Neural Network Trained with Noise

Soumitro Chakrabarty·Emanuël A. P. Habets
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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.

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Soumitro Chakrabarty, Emanuël A. P. Habets. 2017-12-12. Multi-Speaker Localization Using Convolutional Neural Network Trained with Noise. https://arxiv.org/abs/1712.04276

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