Tag: bioacoustics

Table ronde “à l’écoute du vivant” @ Trempo (Nantes)

Bruit vert est une structure de production nantaise, faisant le lien entre création sonore et questionnements sur le vivant. Pour cette Carte Blanche, elle donne la parole au groupe Labotanique, qui a composé son nouvel EP sur une île de Loire, interdite aux humains. Une table ronde explorera la question de l’utilisation du field recording dans… Continue reading Table ronde “à l’écoute du vivant” @ Trempo (Nantes)

Table ronde “IA en recherche” @ Ifremer

Cet événement, organisé par les doctorants de l’Ifremer, a déjà rassemblé une centaine de participants chaque année autour de présentations orales, de tables rondes et d’ateliers de prise en main. Cette journée est ouverte à toute personne intéressée par l’IA dans la recherche, des applications, les limites et les aspects éthiques.
Rendez-vous le mardi 8 octobre 2024 dans le centre Atlantique de l’Ifremer à Nantes.

BirdVoxDetect: Large-Scale Detection and Classification of Flight Calls for Bird Migration Monitoring @ IEEE TASLP

Sound event classification has the potential to advance our understanding of bird migration. Although it is long known that migratory species have a vocal signature of their own, previous work on automatic flight call classification has been limited in robustness and scope: e.g., covering few recording sites, short acquisition segments, and simplified biological taxonomies. In this paper, we present BirdVoxDetect (BVD), the first full-fledged solution to bird migration monitoring from acoustic sensor network data.

Mixture of Mixups for Multi-label Classification of Rare Anuran Sounds @ EUSIPCO

AnuraSet

Multi-label imbalanced classification poses a significant challenge in machine learning, particularly evident in bioacoustics where animal sounds often co-occur, and certain sounds are much less frequent than others. This paper focuses on the specific case of classifying anuran species sounds using the dataset AnuraSet, that contains both class imbalance and multi-label examples. To address these challenges, we introduce Mixture of Mixups (Mix2), a framework that leverages mixing regularization methods Mixup, Manifold Mixup, and MultiMix. Experimental results show that these methods, individually, may lead to suboptimal results; however, when applied randomly, with one selected at each training iteration, they prove effective in addressing the mentioned challenges, particularly for rare classes with few occurrences. Further analysis reveals that the model trained using Mix2 is also proficient in classifying sounds across various levels of class co-occurrences.

BioacAI doctoral network workshop in Czech Republic

From May 6th to May 10th, 2024, PhD student Yasmine Benhamadi and CNRS scientist Vincent Lostanlen have attended the first internal workshop of the BioacAI doctoral network. The Czech University of Life Sciences in Prague hosted the event in its University Forest Establishment, an ancient castle in the town of Kostelec nad Černými lesy.