1 citations · 2 across the 14 of their papers we have counts for
14 papers
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…
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…
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…
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…
Curved Worlds, Clear Boundaries: Generalizing Speech Deepfake Detection using Hyperbolic and Spherical Geometry Spaces
Farhan Sheth, Girish, Mohd Mujtaba Akhtar +1
In this work, we address the challenge of generalizable audio deepfake detection (ADD) across diverse speech synthesis paradigms-including conventional text-to-speech (TTS) systems…
Towards Attribution of Generators and Emotional Manipulation in Cross-Lingual Synthetic Speech using Geometric Learning
Girish, Mohd Mujtaba Akhtar, Farhan Sheth +1
In this work, we address the problem of finegrained traceback of emotional and manipulation characteristics from synthetically manipulated speech. We hypothesize that combining sem…
Towards Machine Unlearning for Paralinguistic Speech Processing
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar +6
In this work, we pioneer the study of Machine Unlearning (MU) for Paralinguistic Speech Processing (PSP). We focus on two key PSP tasks: Speech Emotion Recognition (SER) and Depres…
Avengers Assemble: Amalgamation of Non-Semantic Features for Depression Detection
Orchid Chetia Phukan, Swarup Ranjan Behera, Shubham Singh +5
In this study, we address the challenge of depression detection from speech, focusing on the potential of non-semantic features (NSFs) to capture subtle markers of depression. Whil…
Speech Recognition Transformers: Topological-lingualism Perspective
Shruti Singh, Muskaan Singh, Virender Kadyan
Transformers have evolved with great success in various artificial intelligence tasks. Thanks to our recent prevalence of self-attention mechanisms, which capture long-term depende…
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…
ComFeAT: Combination of Neural and Spectral Features for Improved Depression Detection
Orchid Chetia Phukan, Sarthak Jain, Shubham Singh +3
In this work, we focus on the detection of depression through speech analysis. Previous research has widely explored features extracted from pre-trained models (PTMs) primarily tra…
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…