53 citations · 72 across the 10 of their papers we have counts for
10 papers
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…
On feature representations for marmoset vocal communication analysis
Eklavya Sarkar, Kaja Wierucka, Alexandra B. Bosshard +2
The acoustic analysis of marmoset (Callithrix jacchus) vocalizations is often used to understand the evolutionary origins of human language. Currently, the analysis is largely carr…
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-…
Feature Representations for Automatic Meerkat Vocalization Classification
Imen Ben Mahmoud, Eklavya Sarkar, Marta Manser +1
Understanding evolution of vocal communication in social animals is an important research problem. In that context, beyond humans, there is an interest in analyzing vocalizations o…
On the Utility of Speech and Audio Foundation Models for Marmoset Call Analysis
Eklavya Sarkar, Mathew Magimai. -Doss
Marmoset monkeys encode vital information in their calls and serve as a surrogate model for neuro-biologists to understand the evolutionary origins of human vocal communication. Tr…
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…
Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering
Eklavya Sarkar, RaviShankar Prasad, Mathew Magimai. -Doss
Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which conta…
Are GAN-based Morphs Threatening Face Recognition?
Eklavya Sarkar, Pavel Korshunov, Laurent Colbois +1
Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applicat…
Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks
Eklavya Sarkar, Pavel Korshunov, Laurent Colbois +1
Morphing attacks is a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applicati…