Common Bird Sound Recognition at Vietnam Based on CNN
Phan Thi Ha1, Trinh Thi Van Anh2
1Dr. Phan Thi Ha, lecturer, Faculty of Information Technology at Posts and Telecommunications Institute of Technology (PTIT), Ha Noi, Vietnam, and Computing Fundamental Department, FPTUniversity, Hanoi, Viet Nam.
2Trinh Thi Van Anh, lecturer, Faculty of Information Technology at Posts and Telecommunications Institute of Technology (PTIT), Ha Noi, Vietnam, and Computing Fundamental Department, FPT University, Hanoi, Viet Nam.
Manuscript received on 03 November 2023 | Revised Manuscript received on 12 November 2023 | Manuscript Accepted on 15 December 2023 | Manuscript published on 30 December 2023 | PP: 13-18 | Volume-13 Issue-1, December 2023 | Retrieval Number: 100.1/ijitee.A97561213123 | DOI: 10.35940/ijitee.A9756.1213123
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This article about developing a software extracting bird sound from a website [13], that has sounds of different bird species in Vietnam, explores the CNN model to develop a bird sound recognition system. The process includes conducting methodological experiments on self-collected datasets, providing assessments based on obtained results and building a bird sound recognition application.
Keywords: CNN, RNN, CRNN, Bird CLEF, Recognition, Classification, Bird Sound, Mel Spectrogram, Xception, Mobile Net, Efficient Net.
Scope of the Article: Classification