Open AccessA Survey on Animal Voice Recognition: Mood and Behaviour using Machine Learning Approach
Author(s) -
C. Santhanakrishnan,
Nitish Jha,
Vishal Verma
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1362/1/012092
Subject(s) - voice analysis , computer science , speech recognition , point (geometry) , quality (philosophy) , artificial intelligence , mathematics , philosophy , geometry , epistemology
Voice recognition frameworks turned into the fundamental applications for discourse recognition innovation, a creature affirmation framework bolstered creature voice design recognition rule has been created. The proposed creature voice recognition framework uses the zero-cross rate, MelFrequency Cepstral Coefficient and Dynamic-Time wrap joint calculations in light of the fact that the instruments for recollecting the voice of the genuine creature. ZCR is utilized for the begin point recognition of testing voice indicated the commotion might be expelled. MFC is utilized for the strategy for quality extraction wherever an extra consolidated and less excess of the delegate voice might be accumulated from the testing voice. while the voice order will be finished by abuse DT WRAP rule. At that point the voice coordinating is done to distinguish and characterize the creature seen by the framework. The program made and data noted demonstrates the recognition framework works.