arXiv Machine Learning

MAST: Label-Efficient, Robust, and Generalizable Sound Detection for Biodiversity Monitoring via Masked Audio Pretraining and Self-Training

arXiv Machine Learning

Jul 16

MetaPerch: Learning from metadata for bioacoustics foundation models

arXiv:2607. 14072v1 Announce Type: new Abstract: Bioacoustic foundation models rely on large-scale citizen science platforms like Xeno-Canto for geographically and ecologically diverse data.

By Mustafa Chasmai, Vincent Dumoulin, Jenny Hamer

benchmarks

Hugging Face Trending Papers

Jul 15

MetaPerch: Learning from metadata for bioacoustics foundation models

Bioacoustic foundation models rely on large-scale citizen science platforms like Xeno-Canto for geographically and ecologically diverse data. Recent work has shown that supervision alone can produce SotA species detection models when trained on this large-scale data -- however, there remains unutilized potential in the form of recording metadata readily available within these community-driven data hubs.

benchmarks

arXiv Computer Vision

Sep 14

Unlabeled Echoes: Pseudo-Labels and Genus-Aware Smoothing for Bat Call Recognition

arXiv:2609.11986v1 Announce Type: cross Abstract: Passive acoustic monitoring produces far more bat recordings than experts can label. We show that simple model-generated pseudo-labels turn this surp...

By Frank Fundel, Alexandra Howard

arXiv AI

Jun 2

VocSim: A Training-free Benchmark for Zero-shot Content Identity in Single-source Audio

arXiv:2512. 10120v2 Announce Type: replace-cross Abstract: General-purpose audio representations aim to map acoustically variable instances of the same event to nearby points, resolving content identity in a zero-shot setting.

By Maris Basha, Anja Zai, Sabine Stoll, Richard Hahnloser

rag multimodal benchmarks safety

arXiv Machine Learning

Jul 7

Adaptive Loss Balancing for Multi-Task Bioacoustic Classification of Bird Species and Call Types

arXiv:2607. 03304v1 Announce Type: cross Abstract: Reliable analysis of bird vocalisations in passive acoustic monitoring requires models handling multiple, imbalanced annotation targets.

By Paria Vali Zadeh, Sven Tomforde

fine-tuning

arXiv AI

Jun 12

Decoding Insect Song: A Multitask Semisupervised Orthoptera Bioacoustic Classifier

arXiv:2606. 13236v1 Announce Type: cross Abstract: Passive acoustic monitoring holds great promise for ecological inference, yet existing automated tools are typically narrowly trained and non-transferable.

By Olga Isupova, Danil Kuzin, Ella Browning, Tom Mills, Steven Reece

rag efficiency benchmarks

arXiv AI

Jul 17

Can Tokens Compete? Token Representations against Supervised CNN Backbones for BirdCLEF+ 2026

arXiv:2607. 14474v1 Announce Type: cross Abstract: This paper details the DS@GT ARC team's approach to BirdCLEF+ 2026, multi-label detection of animal vocalizations in soundscapes from the Pantanal wetlands.

By Anthony Miyaguchi, Murilo Gustineli, Adrian Cheung

rag benchmarks

arXiv Machine Learning

Sep 15

Large-scale bioacoustic detection using semantic segmentation: a deep learning framework applied to fin whale calls in ocean-bottom seismometer recordings

arXiv:2609.13281v1 Announce Type: cross Abstract: Ocean-bottom seismometers (OBS), originally deployed for geophysical research, continuously record low-frequency sound for months to years across bro...

By Jocelyn Japnanto, Alex A. Saoulis, Miriam Romagosa, Rita Leit\~ao, Gabrielle Arrieta, M\'onica A. Silva, Matthew Graham, Ana M. G. Ferreira

computer-vision

arXiv Machine Learning

Jul 10

A Self-Supervised Approach for Minimal-Annotation Hydroacoustic Data Exploration

arXiv:2607. 07733v1 Announce Type: cross Abstract: Passive hydroacoustic monitoring often generates large volumes of continuous recordings that are only partially exploited due to the cost of manual annotation.

By Pierre-Yves Raumer, Axel Marmoret, Dorian Cazau, Anatole Gros-Martial, Richard Dreo, Maelle Torterotot, Sara Bazin, Flore Samaran, Jean-Yves Royer

rag

arXiv Machine Learning

2d ago

Beyond Discrimination: Calibrated Geoprior Fusion for Bioacoustic Monitoring

arXiv:2609.35863v1 Announce Type: cross Abstract: Modern bioacoustic foundation models like Perch and BirdNET can identify species with high discriminative accuracy, yet their confidence scores are o...

By Neha Sajja, Bart van Merri\"{e}nboer, Burcu Karagol Ayan, Tom Denton

arXiv Machine Learning

Jun 19

Bioacoustic Geolocation: Species Sounds as Geographic Signals

arXiv:2505. 18726v3 Announce Type: replace-cross Abstract: Can we determine someone's geographic location solely from the sounds they hear?

By Mustafa Chasmai, Wuao Liu, Subhransu Maji, Grant Van Horn

multimodal benchmarks

arXiv AI

Jun 30

Semi-Supervised Sound Event Detection with Conditional Mixup and Embedding-Level Contrastive Loss

arXiv:2606. 29901v1 Announce Type: cross Abstract: Sound event detection (SED) is a core module for acoustic environmental analysis, yet its performance is often limited by scarce labeled data.

By Nian Shao, Xian Li, Xiaofei Li

rag fine-tuning

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