Examinando por Materia "AnuraSet"

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    Reducción de ruido en señales bioacústicas : un enfoque basado en wavelets y aplicado al monitoreo de poblaciones de aves y anfibios
    (Universidad EAFIT, 2025) Carvalho Salazar, Sebastián; García Vargas, Johan Felipe
    Bioacoustic monitoring techniques enable non-invasive detection of biological populations through automatic recorders that continuously capture species vocalizations in natural habitats. This study assesses the impact of wavelet-based noise reduction on bioacoustic signal processing and evaluates its influence on benchmark classification models, specifically BirdNET for birds and AnuraSet for amphibians. Our methodology includes noise reduction preprocessing, followed by an in-depth analysis of classification performance metrics such as mel cosine similarity, temporal correlation, entropy ratio, and ROC-AUC curves. Results indicate that noise reduction enhances signal clarity and reduces false alarm rates, enabling more accurate discrimination in acoustically complex environments like urban areas and rainforests. Although the technique may suppress some subtle vocalization features, statistical analysis and radar plots suggest that adjustments to the denoising process can help optimize the balance between noise reduction and preservation of essential bioacoustic characteristics. Consequently, wavelet-based noise reduction is a robust strategy for high-interference environments, though it may be less suitable for studies requiring comprehensive capture of all vocalizations, such as endangered or low-density species. Moreover, denoising regulates confidence in incorrect predictions and preserves relevant features in correct predictions, reducing false alarms.