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Dog voice identification (ID) for detection system


Yeo, Che Yong and Syed Mohamed, Syed Abdul Rahman Al-Haddad and Ng, Chee Kyun (2012) Dog voice identification (ID) for detection system. In: Second International Conference on Digital Information Processing and Communications (ICDIPC 2012), 10-12 July 2012, Klaipeda City, Lithuania. (pp. 120-123).


Voice recognition systems have become the important applications for speech recognition technology. In this paper, an animal identification (ID) detection system based on animal voice pattern recognition algorithm has been developed. The developed animal voice recognition system uses the zero-cross-rate (ZCR), Mel-Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) joint algorithms as the tools for recognizing the voice of the particular animal. ZCR is used for the end point detection of input voice such that the silence voice can be removed. MFCC is used for the process of feature extraction where a more compact and less redundant of the representative voice can be obtained from the input voice. While the voice pattern classification will be done by using DTW algorithm. The DTW voice pattern classification module is playing a very important role as it is used to get the optimal path between the input voice and the reference voice in the database. The obtained results show that the developed recognition system can be worked as expected.

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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1109/ICDIPC.2012.6257264
Publisher: IEEE
Keywords: Animal; Voice recognition; ZCR; MFCC; DTW
Depositing User: Nabilah Mustapa
Date Deposited: 02 Jul 2019 08:00
Last Modified: 02 Jul 2019 08:00
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICDIPC.2012.6257264
URI: http://psasir.upm.edu.my/id/eprint/69338
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