Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
