Open AccessBird Species Detection From Voice Features
Author(s) -
B Rachana,
K. S. Hegde,
Navya Bhat
Publication year - 2021
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/cseit217453
Subject(s) - bayes' theorem , naive bayes classifier , set (abstract data type) , computer science , field (mathematics) , artificial intelligence , machine learning , statistics , ecology , mathematics , biology , bayesian probability , support vector machine , pure mathematics , programming language
The objective is naturally recognize which types of bird is available in a sound data set utilizing regulated learning. Contriving successful calculations for bird species order is a fundamental advance toward separating valuable natural information from accounts gathered in the field. Here Naïve Bayes calculation to characterize bird voices into various species dependent on 265 highlights removed from the chipping sound of birds. The difficulties in this undertaking included memory the executives, the quantity of bird species for the machine perceive, and the jumble in signal-to-clamor proportion between the preparation and the testing sets. So to settle this difficulties we utilized Naïve Bayes calculation from this we got great precision in it. The calculation Naive Bayes got 91.58% exactness.