collaborators

12 papers

eess.AS2026

AffectDF: The Most Comprehensive Benchmark for Speech Deepfake Detection against Emotionally Expressive Attacks

Aurosweta Mahapatra, Xiutian Zhao, Shreeram Suresh Chandra +7

Speech deepfake detection (SDD) systems achieve strong performance on conventional benchmarks; however, existing datasets provide limited coverage of emotionally expressive and rec…

eess.AS2026

Multimodal Speaker Verification as a Threat to Speaker Anonymization

Ashi Garg, Cristina Aggazzotti, Leibny Paola García-Perera +1

Most automatic speaker verification (ASV) systems operate on individual utterances, despite real-world interactions typically consisting of multiple utterances. As speech accumulat…

eess.AS2026

Universal Speech Content Factorization

Henry Li Xinyuan, Zexin Cai, Lin Zhang +5

We propose Universal Speech Content Factorization (USCF), a simple and invertible linear method for extracting a low-rank speech representation in which speaker timbre is suppresse…

eess.AS2026

DiffAnon: Diffusion-based Prosody Control for Voice Anonymization

Ismail Rasim Ulgen, Zexin Cai, Nicholas Andrews +2

To preserve or not to preserve prosody is a central question in voice anonymization. Prosody conveys meaning and affect, yet is tightly coupled with speaker identity. Existing meth…

eess.AS2026

ProSDD: Learning Prosodic Representations for Speech Deepfake Detection against Expressive and Emotional Attacks

Aurosweta Mahapatra, Ismail Rasim Ulgen, Kong Aik Lee +2

Speech deepfake detection (SDD) systems perform well on standard benchmarks datasets but often fail to generalize to expressive and emotional spoofing attacks. Many methods rely on…

eess.AS2026

Integrated Spoofing-Robust Automatic Speaker Verification via a Three-Class Formulation and LLR

Kai Tan, Lin Zhang, Ruiteng Zhang +6

Spoofing-robust automatic speaker verification (SASV) aims to integrate automatic speaker verification (ASV) and countermeasure (CM). A popular solution is fusion of independent AS…