arXiv AI September 16, 2026 By Mudit Sinha, Sanika Chavan

Structure Across Voices: Comparing acoustic-event type accumulation and sequence dependence across four vocal repertoires using frozen audio encoders

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arXiv AI

Jun 16

Rhythm of the Deep: A Computational-Linguistic Test of Duality of Patterning in Sperm Whale Codas

arXiv:2606. 16084v1 Announce Type: new Abstract: Human language has often been described as combining structure at two levels: lower-level units combine into larger units, which then combine into larger sequences.

By Mudit Sinha, Sanika Chavan

arXiv AI

Sep 16

Rhythm of the Deep: Two-tier acoustic organization of sperm-whale codas from click waveforms to second-order sequence dependence

arXiv:2606.16084v3 Announce Type: replace Abstract: Sperm-whale codas are conventionally characterized by click count and inter-click intervals (ICIs), leaving recurring differences in constituent cl...

By Mudit Sinha, Sanika Chavan

arXiv Machine Learning

Jul 27

Phylogenetic signal in marine mammal and bird vocalizations captured by audio foundation models: the limited benefit of domain-specific pretraining

arXiv:2607. 22458v1 Announce Type: new Abstract: Do learned audio embeddings encode structure that nobody told them to encode?

By V\'ictor Rinc\'on Yepes

rag

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

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

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

arXiv:2609.15221v1 Announce Type: cross Abstract: Passive acoustic monitoring can measure biodiversity at larger scales, but time--frequency annotation of animal vocalizations is expensive, site-spec...

By Tianyi Xu, Daniel Pimentel-Alarc\'on, Zuzana Bu\v{r}ivalov\'a, Claudia Sol\'is-Lemus

One email a morning, machine-written

Related stories

Rhythm of the Deep: A Computational-Linguistic Test of Duality of Patterning in Sperm Whale Codas

Rhythm of the Deep: Two-tier acoustic organization of sperm-whale codas from click waveforms to second-order sequence dependence

Phylogenetic signal in marine mammal and bird vocalizations captured by audio foundation models: the limited benefit of domain-specific pretraining

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

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

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