Sound Events Recognition and Retrieval Using Multi-Convolutional-Channel Sparse Coding Convolutional Neural Networks

Chien Yao Wang, Tzu Chiang Tai, Jia Ching Wang, Andri Santoso, Seksan Mathulaprangsan, Chin Chin Chiang, Chung Hsien Wu

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

This article proposes two novel deep convolutional neural networks (CNN), which are called the sparse coding convolutional neural network (SC-CNN) and the multi-convolutional-channel SC-CNN (MSC-CNN), to address the sound event recognition and retrieval problem. Unlike the general framework of a CNN, in which the feature learning process is performed hierarchically, the proposed framework models the whole memorization process in the human brain, including encoding, storage, and recollection. In particular, the MSC-CNN is designed to recognize multiple sound events that occur simultaneously. The experimental results indicate that the proposed SC-CNN and MSC-CNN outperforms the state-of-the-art systems in sound event recognition and retrieval.

原文English
文章編號8952659
頁(從 - 到)1875-1887
頁數13
期刊IEEE/ACM Transactions on Audio Speech and Language Processing
28
DOIs
出版狀態Published - 2020

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Acoustics and Ultrasonics
  • Computational Mathematics
  • Electrical and Electronic Engineering

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