14 papers
SPADE: A Multilingual Dataset for Speech Partial Deepfake Detection and Localization
Yuan Tseng, Aishwarya Fursule, Andrew Zijun Ma +4
Recent improvements in voice-cloning speech generation systems raise concerns about misuse by malicious actors to impersonate others and spread misinformation. Detecting such tampe…
NanoSleep: A Parameter-Efficient Hybrid Temporal Convolutional Network for Single-Channel Sleep Stage Classification
S M Asif Hossain, Shruti Kshirsagar
Sleep stage classification from single-channel electroencephalography (EEG) is essential for wearable and home-based sleep monitoring. However, many deep learning models achieve hi…
How Temperature Shapes Ideological Discourse in Retrieval-Augmented Generation?
Elmira Salari, Hazem Amamou, José Victor de Souza +3
Retrieval-Augmented Generation (RAG) has been increasingly adopted to reduce hallucinations and strengthen the factual grounding of large language models (LLMs). While robustness t…
What You Train Is What You Get: Gender Bias, Training Composition, and Post-Hoc Mitigation in Audio Deepfake Detection
Aishwarya R. Fursule, Vamshi Nallaguntla, Shruti Kshirsagar +1
Audio deepfake detection models determine whether speech is genuine or artificially generated, but high overall accuracy can mask substantial performance disparities across demogra…
InfiltrNet: Dual-Branch CNN-Transformer Architecture for Brain Tumor Infiltration Risk Prediction
S M Asif Hossain, Shruti Kshirsagar
Gliomas are aggressive brain tumors that infiltrate surrounding tissue beyond the visible tumor margins observed on Magnetic Resonance Imaging (MRI). Predicting the spatial extent…
Towards Trustworthy Audio Deepfake Detection: A Systematic Framework for Diagnosing and Mitigating Gender Bias
Aishwarya Fursule, Shruti Kshirsagar, Anderson R. Avila
Audio deepfake detection systems are increasingly deployed in high-stakes security applications, yet their fairness across demographic groups remains critically underexamined. Prio…
STDA-Net: Spectrogram-Based Domain Adaptation for cross-dataset Sleep Stage Classification
Unaza Tallal, Shruti Kshirsagar, Ankita Shukla
Accurate sleep stage classification across datasets remains challenging due to variability in EEG channel montages, sampling rates, recording environments, and subject populations.…
Phoneme-Level Deepfake Detection Across Emotional Conditions Using Self-Supervised Embeddings
Vamshi Nallaguntla, Shruti Kshirsagar, Anderson R. Avila
Recent advances in emotional voice conversion (EVC) have enabled the generation of expressive synthetic speech, raising new concerns in audio deepfake detection. Existing approache…
Demographic-Aware Transfer Learning for Sleep Stage Classification in Clinical Polysomnography
S M Asif Hossain, Shruti Kshirsagar
Automated sleep stage classification typically employs a single population-agnostic model, disregarding established demographic variations in sleep architecture. Sleep patterns, ho…
PhonemeDF: A Synthetic Speech Dataset for Audio Deepfake Detection and Naturalness Evaluation
Vamshi Nallaguntla, Aishwarya Fursule, Shruti Kshirsagar +1
The growing sophistication of speech generated by Artificial Intelligence (AI) has introduced new challenges in audio deepfake detection. Text-to-speech (TTS) and voice conversion…
The Impact of Ideological Discourses in RAG: A Case Study with COVID-19 Treatments
Elmira Salari, Maria Claudia Nunes Delfino, Hazem Amamou +4
This paper studies the impact of retrieved ideological texts on the outputs of large language models (LLMs). While interest in understanding ideology in LLMs has recently increased…
Investigating the Impact of Speech Enhancement on Audio Deepfake Detection in Noisy Environments
Anacin, Angela, Shruti Kshirsagar +1
Logical Access (LA) attacks, also known as audio deepfake attacks, use Text-to-Speech (TTS) or Voice Conversion (VC) methods to generate spoofed speech data. This can represent a s…
Robust Building Damage Detection in Cross-Disaster Settings Using Domain Adaptation
Asmae Mouradi, Shruti Kshirsagar
Rapid structural damage assessment from remote sensing imagery is essential for timely disaster response. Within human-machine systems (HMS) for disaster management, automated dama…
Gender Fairness in Audio Deepfake Detection: Performance and Disparity Analysis
Aishwarya Fursule, Shruti Kshirsagar, Anderson R. Avila
Audio deepfake detection aims to detect real human voices from those generated by Artificial Intelligence (AI) and has emerged as a significant problem in the field of voice biomet…