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From Signals to Patterns: Non-Invasive Tuberculosis Detection from Cough Audio using Bandit Weighted Hyperbolic Prototypes
Mohd Mujtaba Akhtar, Girish, Sanjam Wadhwa +2
In this study, we focus on cough-based tuberculosis screening (CBTS) and hypothesize that fusing speech/audio foundation representations with spectral descriptors will yield strong…
Bridging the Age Gap: Towards Detecting Neural Audio Codec Synthesized Elderly Speech Deepfake
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar +1
In this study, we introduce the Elderly CodecFake Detection (ECFD) task and release the Elderly-CodecFake (ECF) dataset in English and Chinese. We show that state-of-the-art CF det…
Towards Detecting Neural Audio Codec Synthesized Heart Sounds
Girish, Orchid Chetia Phukan, Mohd Mujtaba Akhtar +3
In this paper, we introduce Synthetic Heart Sound Detection (SHAC), a task aimed at identifying phonocardiograms (PCGs) synthesized using neural audio codecs (NACs). To facilitate…
Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning
Girish, Mohd Mujtaba Akhtar, Farhan Sheth +4
In this work, we study zero-shot cross-lingual speech-based Alzheimer's disease detection (SADD). We hypothesize that learning language-invariant multimodal representations by fusi…
Bridging the SEA Gap: An Initial Benchmark for Neural Audio Codec-Synthesized Speech Deepfakes in South-East Asian Languages
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar +1
Codecfakes (CFs) are a type of speech deepfakes generated through Audio Language Models (ALMs), with Neural Audio Codecs (NACs) forming the core mechanism for speech encoding and g…
Prosody as Supervision: Bridging the Non-Verbal--Verbal for Multilingual Speech Emotion Recognition
Girish, Mohd Mujtaba Akhtar, Muskaan Singh
In this work, we introduce a paralinguistic supervision paradigm for low-resource multilingual speech emotion recognition (LRM-SER) that leverages non-verbal vocalizations to explo…
Indic-CodecFake meets SATYAM: Towards Detecting Neural Audio Codec Synthesized Speech Deepfakes in Indic Languages
Girish, Mohd Mujtaba Akhtar, Orchid Chetia Phukan +1
The rapid advancement of Audio Large Language Models (ALMs), driven by Neural Audio Codecs (NACs), has led to the emergence of highly realistic speech deepfakes, commonly referred…
HCFD: A Benchmark for Audio Deepfake Detection in Healthcare
Mohd Mujtaba Akhtar, Girish, Muskaan Singh
In this study, we present Healthcare Codec-Fake Detection (HCFD), a new task for detecting codec-fakes under pathological speech conditions. We intentionally focus on codec based s…
Bridging Attribution and Open-Set Detection using Graph-Augmented Instance Learning in Synthetic Speech
Mohd Mujtaba Akhtar, Girish, Farhan Sheth +1
We propose a unified framework for not only attributing synthetic speech to its source but also for detecting speech generated by synthesizers that were not encountered during trai…
DIVINE: Coordinating Multimodal Disentangled Representations for Oro-Facial Neurological Disorder Assessment
Mohd Mujtaba Akhtar, Girish, Muskaan Singh
In this study, we present a multimodal framework for predicting neuro-facial disorders by capturing both vocal and facial cues. We hypothesize that explicitly disentangling shared…