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  • 标题:SPECTRAL ENERGY BASED VOICE ACTIVITY DETECTION FOR REAL-TIME VOICE INTERFACE
  • 本地全文:下载
  • 作者:JEONG-SIK PARK ; JUNG-SEOK YOON ; YONG-HO SEO
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2017
  • 卷号:95
  • 期号:17
  • 页码:4304
  • 出版社:Journal of Theoretical and Applied
  • 摘要:Voice activity detection (VAD) is a main process of speech recognition tasks in which every voice region is detected to extract acoustic feature parameters from the region. This paper proposes an efficient VAD approach for applying to real-time voice interface systems. Even though diverse VAD approaches have been successfully applied for speech applications, they may operate inefficiently according to environmental conditions. In this study, we attempt to enhance the conventional VAD method based on signal energy within time and spectral domain. In addition, an efficient end-point detection method is also proposed. We successfully verified the efficiency of the proposed approach via a set of VAD experiments, comparing with the performance of some conventional VAD methods including zero crossing rate.
  • 关键词:Voice Activity Detection; End-point Detection; Voice Interface; Spectral Domain; Spectral Energy
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