Insect sound recognition based on SBC and HMM
In order to help general technicians to recognize insects conveniently in pests management, this paper proposed a viable scheme to identify insect sounds automatically by using Sub-band based cepstral(SBC) and Hidden Markov Model(HMM). The acoustic signal is preprocessed, segmented into a series of sound samples. SBC is extracted from the sound sample as the feature, and HMMs are trained with given features. The matching for a test sample is completed by finding the best matcher in all HMMs. The method is tested in a database with acoustic samples of 50 different insect sounds. The recognition rate was above 90％. The test results proved the efficiency of the proposed method.
Insects sound recognition Sub-band based cepstral(SBC) Hidden Markov Model(HMM)
Zhu Leqing Zhang Zhen
College of Computer Science and Information Engineering Zhejiang Gongshang University Hangzhou 31001 Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry Beijin
国际会议
长沙
英文
1714-1718
2010-05-11（万方平台首次上网日期，不代表论文的发表时间）