文件名称:
SOUND SOURCE LOCALIZATION BASED ON DEEP NEURAL NETWORKS WITH DIRECTIONAL ACTIVATE FUNCTION EXPLOITING PHASE INFORMATION
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文件大小: 5mb
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上传时间: 2019-08-27
详细说明: This paper describes sound source localization (SSL) based on deep neural networks (DNNs) using discriminative training. A na¨ıve DNNs for SSL can be configured as follows. Input is the frequency-domain feature used in other SSL methods, and the structure of DNNs is a fully-connected network using real numbers. The training fails be cause its network structure loses two important properties, i.e., the orthogonality of sub-bands and the intensity- and time-information saved in complex numbers. We solved these two problems by 1) integrating directional information at each sub-band hierarchically, and 2) designing a directional activator that could treat the complex numbers at each sub-band. Our experiments indicated that our method outperformed the na¨ıve DNN-based SSL by 20 points in terms of the block-level accuracy
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