Recognition of Fruit Fly Wings Vibration Sound Based on HMM

This paper classifies and recognizes three different strains of fruit fly by their wings vibration sounds. It uses Mel-Frequency Cepstrum Coefficient to extract features of fruit fly wings vibration sound, then applies Hidden Markov Model to establish models of three different strains of fruit fly w...

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Bibliographic Details
Published in2010 2nd International Conference on Information Engineering and Computer Science pp. 1 - 4
Main Authors Ningxian Zhang, Min Guo
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2010
Subjects
Computational modeling
Feature extraction
Hidden Markov models
Mel frequency cepstral coefficient
Strain
Training
Vibrations
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Summary:This paper classifies and recognizes three different strains of fruit fly by their wings vibration sounds. It uses Mel-Frequency Cepstrum Coefficient to extract features of fruit fly wings vibration sound, then applies Hidden Markov Model to establish models of three different strains of fruit fly wings vibration sound and recognize three strains of fruit fly. Experiment shows that the recognition rates of the three strains of fruit fly reach over 70%, and the result is satisfying. Thus, the method used by the paper is feasible and effective, and provides a new basis for fruit fly's research.
ISBN:1424479398
9781424479399
ISSN:2156-7379
DOI:10.1109/ICIECS.2010.5678369