Automatic Bird Species Audio Detection
Automatické rozpoznávání ptačích druhů podle zvuku
bachelor thesis (DEFENDED)

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Permanent link
http://hdl.handle.net/20.500.11956/148278Identifiers
Study Information System: 235436
Collections
- Kvalifikační práce [11563]
Author
Advisor
Referee
Pilát, Martin
Faculty / Institute
Faculty of Mathematics and Physics
Discipline
General Computer Science
Department
Department of Theoretical Computer Science and Mathematical Logic
Date of defense
10. 9. 2021
Publisher
Univerzita Karlova, Matematicko-fyzikální fakultaLanguage
English
Grade
Good
Keywords (Czech)
Zpracování signálu|neuronové sítě|automatická detekce ptáků|strojové učeníKeywords (English)
neural network|signal processing|automatic bird detection|machine learningBirds have been long monitored manually, which is very labor intensive. This work tries to explore and compare different types of neural networks (MLP,CNN,RNN,CRNN) to automatically find and classify acoustic activity of birds within audio recordings of wilderness. It could save a lot of time and effort, since people wouldn't have to go through the recordings and manually identify the birds. By saving lots of time, bird monitoring could be done at greater scale, helping with conservation and scientific research. The objective is to build a user-friendly application, where the user can train a new bird- identifying model and use it without needing any computer skills. 1