collaborators

5 papers

eess.AS2026

Leveraging Gradient Reversal Loss and Multitask Learning for Datasets-Aware Audio Deepfake Detection

Mingrui Liang, Thomas Thebaud, Lukasz Wojciak +4

Recent advances in speech synthesis and voice conversion, which pose threats to security and privacy, have underscored the need for deepfake detection technology. Although existing…

eess.AS2026

ProPS: Prompted Profile Synthesis for Natural Language-Conditioned Speaker Embedding Distributions

Thomas Thebaud, Junhyeok Lee, Laureano Moro-Velazquez +2

Speaker embeddings, or x-vectors, are widely used to represent speaker identity and speaker-related attributes, but existing embedding extractors are typically descriptive rather t…

cs.AI2026

StanceBench: A Benchmark for Audio LLM-Based Interpersonal Stance Evaluation from Speech

Yuzhe Wang, Thomas Thebaud, Jennifer Hu +5

Speech-to-speech dialogue models increasingly depend on prosody and interactional nuance to convey social intent, yet benchmarks for these cues remain limited. We introduce StanceB…

cs.CL2026

Beyond Transcripts: Iterative Peer-Editing with Audio Unlocks High-Quality Human Summaries of Conversational Speech

Kaavya Chaparala, Thomas Thebaud, Jesús Villalba López +3

There are not enough established benchmarks for the task fo speech summarization. Creating new benchmarks demands human annotation, as LLMs could embed systemic errors and bias int…

cs.SD2025

Multi-Target Backdoor Attacks Against Speaker Recognition

Alexandrine Fortier, Sonal Joshi, Thomas Thebaud +3

In this work, we propose a multi-target backdoor attack against speaker identification using position-independent clicking sounds as triggers. Unlike previous single-target approac…