5 papers
Similarity Choice and Negative Scaling in Supervised Contrastive Learning for Deepfake Audio Detection
Jaskirat Sudan, Hashim Ali, Surya Subramani +1
Supervised contrastive learning (SupCon) is widely used to shape representations, but has seen limited targeted study for audio deepfake detection. Existing work typically combines…
A SUPERB-Style Benchmark of Self-Supervised Speech Models for Audio Deepfake Detection
Hashim Ali, Nithin Sai Adupa, Surya Subramani +1
Self-supervised learning (SSL) has transformed speech processing, with benchmarks such as SUPERB establishing fair comparisons across diverse downstream tasks. Despite it's securit…
LJ-Spoof: A Generatively Varied Corpus for Audio Anti-Spoofing and Synthesis Source Tracing
Surya Subramani, Hashim Ali, Hafiz Malik
Speaker-specific anti-spoofing and synthesis-source tracing are central challenges in audio anti-spoofing. Progress has been hampered by the lack of datasets that systematically va…
Multilingual Dataset Integration Strategies for Robust Audio Deepfake Detection: A SAFE Challenge System
Hashim Ali, Surya Subramani, Lekha Bollinani +3
The SAFE Challenge evaluates synthetic speech detection across three tasks: unmodified audio, processed audio with compression artifacts, and laundered audio designed to evade dete…
Collecting, Curating, and Annotating Good Quality Speech deepfake dataset for Famous Figures: Process and Challenges
Hashim Ali, Surya Subramani, Raksha Varahamurthy +3
Recent advances in speech synthesis have introduced unprecedented challenges in maintaining voice authenticity, particularly concerning public figures who are frequent targets of i…