5 papers
Disentangling Geometry, Performance, and Training in Language Models
Atharva Kulkarni, Jacob Mitchell Springer, Arjun Subramonian +1
Geometric properties of Transformer weights, particularly the unembedding matrix, have been widely useful in language model interpretability research. Yet, their utility for estima…
Do Compact SSL Backbones Matter for Audio Deepfake Detection? A Controlled Study with RAPTOR
Ajinkya Kulkarni, Sandipana Dowerah, Atharva Kulkarni +2
Self-supervised learning (SSL) underpins modern audio deepfake detection, yet most prior work centers on a single large wav2vec2-XLSR backbone, leaving compact under studied. We pr…
Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models
Sandipana Dowerah, Atharva Kulkarni, Ajinkya Kulkarni +7
Parallel to the development of advanced deepfake audio generation, audio deepfake detection has also seen significant progress. However, a standardized and comprehensive benchmark…
Code-Switching in End-to-End Automatic Speech Recognition: A Systematic Literature Review
Maha Tufail Agro, Atharva Kulkarni, Karima Kadaoui +2
Motivated by a growing research interest into automatic speech recognition (ASR), and the growing body of work for languages in which code-switching (CS) often occurs, we present a…
Unveiling Biases while Embracing Sustainability: Assessing the Dual Challenges of Automatic Speech Recognition Systems
Ajinkya Kulkarni, Atharva Kulkarni, Miguel Couceiro +1
In this paper, we present a bias and sustainability focused investigation of Automatic Speech Recognition (ASR) systems, namely Whisper and Massively Multilingual Speech (MMS), whi…