53 citations · 72 across the 10 of their papers we have counts for
4 papers · 1 filter
Beyond the Baseband: Adaptive Multi-Band Encoding for Full-Spectrum Bioacoustics Classification
Eklavya Sarkar, Marius Miron, David Robinson +6
Animals hear and vocalize across frequency ranges that differ substantially from humans, often extending into the ultrasonic domain. Yet most computational bioacoustics systems rel…
Towards Leveraging Sequential Structure in Animal Vocalizations
Eklavya Sarkar, Mathew Magimai. -Doss
Animal vocalizations contain sequential structures that carry important communicative information, yet most computational bioacoustics studies average the extracted frame-level fea…
Comparing Self-Supervised Learning Models Pre-Trained on Human Speech and Animal Vocalizations for Bioacoustics Processing
Eklavya Sarkar, Mathew Magimai. -Doss
Self-supervised learning (SSL) foundation models have emerged as powerful, domain-agnostic, general-purpose feature extractors applicable to a wide range of tasks. Such models pre-…
Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?
Eklavya Sarkar, Mathew Magimai. -Doss
Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an…