Bird Species Detection From Voice Features

Authors

  • Rachana B  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India
  • Kavya Hegde  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India
  • Navya Bhat  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India

DOI:

https://doi.org/10.32628/CSEIT217453

Keywords:

Machine Learning, PC frameworks, Pseudo Code

Abstract

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.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-08-30

Issue

Volume 7, Issue 4, July-August-2021

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Rachana B, Kavya Hegde, Navya Bhat, " Bird Species Detection From Voice Features" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 4, pp.199-202, July-August-2021. Available at doi : https://doi.org/10.32628/CSEIT217453