التفاصيل البيبلوغرافية
| العنوان: |
Extensive data engineering to the rescue: building a multi-species katydid detector from unbalanced, atypical training datasets. |
| المؤلفون: |
Madhusudhana, Shyam, Klinck, Holger, Symes, Laurel B. |
| المصدر: |
Philosophical Transactions of the Royal Society B: Biological Sciences; 6/24/2024, Vol. 379 Issue 1904, p1-13, 13p |
| مصطلحات موضوعية: |
KATYDIDS, TROPICAL ecosystems, DEEP learning, DATA augmentation, AUDITORY masking, BIODIVERSITY monitoring, DETECTORS |
| مستخلص: |
Passive acoustic monitoring (PAM) is a powerful tool for studying ecosystems. However, its effective application in tropical environments, particularly for insects, poses distinct challenges. Neotropical katydids produce complex species-specific calls, spanning mere milliseconds to seconds and spread across broad audible and ultrasonic frequencies. However, subtle differences in inter-pulse intervals or central frequencies are often the only discriminatory traits. These extremities, coupled with low source levels and susceptibility to masking by ambient noise, challenge species identification in PAM recordings. This study aimed to develop a deep learning-based solution to automate the recognition of 31 katydid species of interest in a biodiverse Panamanian forest with over 80 katydid species. Besides the innate challenges, our efforts were also encumbered by a limited and imbalanced initial training dataset comprising domain-mismatched recordings. To overcome these, we applied rigorous data engineering, improving input variance through controlled playback re-recordings and by employing physics-based data augmentation techniques, and tuning signal-processing, model and training parameters to produce a custom well-fit solution. Methods developed here are incorporated into Koogu, an open-source Python-based toolbox for developing deep learning-based bioacoustic analysis solutions. The parametric implementations offer a valuable resource, enhancing the capabilities of PAM for studying insects in tropical ecosystems. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'. [ABSTRACT FROM AUTHOR] |
|
Copyright of Philosophical Transactions of the Royal Society B: Biological Sciences is the property of Royal Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
