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  • 标题:An Acoustic Events Recognition for Robotic Systems Based on a Deep Learning Method
  • 本地全文:下载
  • 作者:Tadaaki Niwa ; Takashi Kawakami ; Ryosuke Ooe
  • 期刊名称:Journal of Computer and Communications
  • 印刷版ISSN:2327-5219
  • 电子版ISSN:2327-5227
  • 出版年度:2015
  • 卷号:03
  • 期号:11
  • 页码:46-51
  • DOI:10.4236/jcc.2015.311008
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:In this paper, we provide a new approach to classify and recognize the acoustic events for multiple autonomous robots systems based on the deep learning mechanisms. For disaster response robotic systems, recognizing certain acoustic events in the noisy environment is very effective to perform a given operation. As a new approach, trained deep learning networks which are constructed by RBMs, classify the acoustic events from input waveform signals. From the experimental results, usefulness of our approach is discussed and verified.
  • 关键词:Acoustic Events Recognition;Deep Learning;Restricted Boltzmann Machine
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