DocumentCode
1901526
Title
Recognition of Fruit Fly Wings Vibration Sound Based on HMM
Author
Zhang, Ningxian ; Guo, Min
Author_Institution
Coll. of Comput. Sci., Shaanxi Normal Univ., Xi´´an, China
fYear
2010
fDate
25-26 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
acoustic signal processing; feature extraction; hidden Markov models; vibrations; HMM; feature extraction; fruit fly wings vibration sounds; hidden Markov model; mel-frequency cepstrum coefficient; recognition rates; Computational modeling; Feature extraction; Hidden Markov models; Mel frequency cepstral coefficient; Strain; Training; Vibrations;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location
Wuhan
ISSN
2156-7379
Print_ISBN
978-1-4244-7939-9
Electronic_ISBN
2156-7379
Type
conf
DOI
10.1109/ICIECS.2010.5678369
Filename
5678369
Link To Document