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
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;
Conference_Titel :
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7939-9
Electronic_ISBN :
2156-7379
DOI :
10.1109/ICIECS.2010.5678369