Automated Bird Species Identification using Audio Signal Processing and Neural Networks

Registration ID: IJNRD_191762

Published ID: IJNRD2304405

DOI: Click Here to Get

Vivek Ganpat Kokare , Ruvighna Vishal Bhalerao , Nikita Nilesh Mane

This research explores approaches for bird identification and develops an automated system for recognizing bird species. Significant study on taxonomy and other subfields of ornithology has been a challenging and difficult endeavour for automatic identification of bird sounds without physical involvement. A two-stage identification approach is used in this work. The first step was creating an ideal dataset that included all of the bird species' sound recordings. The sound snippets were then put through a variety of sound preprocessing procedures, including pre-emphasis, framing, silence removal, and reconstruction. For each reconstructed sound clip, spectrograms were produced. In the subsequent stage, a neural network was set up and given the spectrograms as input. The Convolutional Neural Network (CNN) categorizes the sound sample and determines the species of bird based on the input features. For the aforementioned, a real-time implementation model was also created and used.

Published Paper   E-Certificate

Vivek Ganpat Kokare, Ruvighna Vishal Bhalerao, & Nikita Nilesh Mane (April-2023). Automated Bird Species Identification using Audio Signal Processing and Neural Networks. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), e21-e24. https://ijnrd.org/papers/IJNRD2304405.pdf

Volume 8 Issue 4, April-2023

Pages : e21-e24

Paper Reg. ID: IJNRD_191762

Published Paper Id: IJNRD2304405

Downloads: 000121987

Research Area: Computer Engineering 

Country: pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304405.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304405

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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