Dog voice identification (ID) for detection system
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-...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2012
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| Online Access: | http://psasir.upm.edu.my/id/eprint/69338/ http://psasir.upm.edu.my/id/eprint/69338/1/Dog%20voice%20identification%20%28ID%29%20for%20detection%20system.pdf |
| _version_ | 1848856378694696960 |
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| author | Yeo, Che Yong Syed Mohamed, Syed Abdul Rahman Al-Haddad Ng, Chee Kyun |
| author_facet | Yeo, Che Yong Syed Mohamed, Syed Abdul Rahman Al-Haddad Ng, Chee Kyun |
| author_sort | Yeo, Che Yong |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T11:40:43Z |
| format | Conference or Workshop Item |
| id | upm-69338 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:40:43Z |
| publishDate | 2012 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-693382019-07-02T08:00:06Z http://psasir.upm.edu.my/id/eprint/69338/ Dog voice identification (ID) for detection system Yeo, Che Yong Syed Mohamed, Syed Abdul Rahman Al-Haddad Ng, Chee Kyun 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. IEEE 2012 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/69338/1/Dog%20voice%20identification%20%28ID%29%20for%20detection%20system.pdf 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). 10.1109/ICDIPC.2012.6257264 |
| spellingShingle | Yeo, Che Yong Syed Mohamed, Syed Abdul Rahman Al-Haddad Ng, Chee Kyun Dog voice identification (ID) for detection system |
| title | Dog voice identification (ID) for detection system |
| title_full | Dog voice identification (ID) for detection system |
| title_fullStr | Dog voice identification (ID) for detection system |
| title_full_unstemmed | Dog voice identification (ID) for detection system |
| title_short | Dog voice identification (ID) for detection system |
| title_sort | dog voice identification (id) for detection system |
| url | http://psasir.upm.edu.my/id/eprint/69338/ http://psasir.upm.edu.my/id/eprint/69338/ http://psasir.upm.edu.my/id/eprint/69338/1/Dog%20voice%20identification%20%28ID%29%20for%20detection%20system.pdf |