標題: A REAL-TIME UNUSUAL VOICE DETECTOR BASED ON NURSING AT HOME
作者: Jing, Min-Quan
Wang, Chao-Chun
Chen, Ling-Hwei
資訊工程學系
Department of Computer Science
關鍵字: Nursing system;Cough;groan;Wheeze;Cry for help;Zero crossing and correlation
公開日期: 2009
摘要: In this paper, we will propose a method to detect an unusual voice for nursing system. Based on the healthy condition of a person, we define four kinds of unusual voices including cough, groan, wheeze and cry for help. When the person nursed sends out the unusual voices, we judge that his health condition have a doubt, and need someone to pay attention. In order to detect the unusual voices, we extract five features on audio waveform, including the number of segmented parts, duration of waveform, mean of volume, zero crossing rate and correlation. Experimental results show that the detection rate is 94%similar to 97% for these four kinds of unusual voices. In false alarm, there are only 0.08% of wrong rates.
URI: http://hdl.handle.net/11536/14256
ISBN: 978-1-4244-4705-3
期刊: PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6
起始頁: 2368
結束頁: 2373
Appears in Collections:Conferences Paper