RoBINN: Robust Bird Species Identification using Neural Network

Chirag Samal, Prince Yadav, Sakshi Singh, Satyanarayana Vollala, Amrita Mishra

2021

Abstract

Recent developments in machine and deep learning have made it possible to expand the realms of traditional audio pattern recognition to real-time and practical applications. This work proposes a novel framework for robust bird species identification using the neural network (RoBINN) based on their unique vocal signatures. To make the network robust and efficient, data augmentation is performed to create synthetic training samples for bird species with less available recordings. Further, inherent properties of audio signals are suitably leveraged via effective speech recognition-based feature engineering techniques to develop an end-to-end convolutional neural network (CNN). Additionally, the proposed model architecture for the CNN framework employs residual learning and attention mechanism to generate attention-aware features, which enhances the overall accuracy of birdcall identification. The proposed architecture employs an exhaustive dataset with 21375 recordings corresponding to 264 bird species. Experimental results validate the proposed bird species classification technique in terms of accuracy, F1-score, and binary cross-entropy loss.

Paper Citation

in Harvard Style

Samal C., Yadav P., Singh S., Vollala S. and Mishra A. (2021). RoBINN: Robust Bird Species Identification using Neural Network. In Proceedings of the 18th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, ISBN 978-989-758-525-8, pages 31-38. DOI: 10.5220/0010647500310038

in Bibtex Style

@conference{sigmap21,
author={Chirag Samal and Prince Yadav and Sakshi Singh and Satyanarayana Vollala and Amrita Mishra},
title={RoBINN: Robust Bird Species Identification using Neural Network},
booktitle={Proceedings of the 18th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP,},
year={2021},
pages={31-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010647500310038},
isbn={978-989-758-525-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP,
TI - RoBINN: Robust Bird Species Identification using Neural Network
SN - 978-989-758-525-8
AU - Samal C.
AU - Yadav P.
AU - Singh S.
AU - Vollala S.
AU - Mishra A.
PY - 2021
SP - 31
EP - 38
DO - 10.5220/0010647500310038