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Beyond Speech and More: Investigating the Emergent Ability of Speech Foundation Models for Classifying Physiological Time-Series Signals
Orchid Chetia Phukan, Swarup Ranjan Behera, Girish +3
Despite being trained exclusively on speech data, speech foundation models (SFMs) like Whisper have shown impressive performance in non-speech tasks such as audio classification. T…
Representation Loss Minimization with Randomized Selection Strategy for Efficient Environmental Fake Audio Detection
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar +5
The adaptation of foundation models has significantly advanced environmental audio deepfake detection (EADD), a rapidly growing area of research. These models are typically fine-tu…
Strong Alone, Stronger Together: Synergizing Modality-Binding Foundation Models with Optimal Transport for Non-Verbal Emotion Recognition
Orchid Chetia Phukan, Mohd Mujtaba Akhtar, Girish +5
In this study, we investigate multimodal foundation models (MFMs) for emotion recognition from non-verbal sounds. We hypothesize that MFMs, with their joint pre-training across mul…
Modality-Order Matters! A Novel Hierarchical Feature Fusion Method for CoSAm: A Code-Switched Autism Corpus
Mohd Mujtaba Akhtar, Girish, Muskaan Singh +1
Autism Spectrum Disorder (ASD) is a complex neuro-developmental challenge, presenting a spectrum of difficulties in social interaction, communication, and the expression of repetit…
NeuRO: An Application for Code-Switched Autism Detection in Children
Mohd Mujtaba Akhtar, Girish, Orchid Chetia Phukan +1
Code-switching is a common communication phenomenon where individuals alternate between two or more languages or linguistic styles within a single conversation. Autism Spectrum Dis…