collaborators

6 papers

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…

cs.SD2026

Content Anonymization for Privacy in Long-form Audio

Cristina Aggazzotti, Ashi Garg, Zexin Cai +1

Voice anonymization techniques have been found to successfully obscure a speaker's acoustic identity in short, isolated utterances in benchmarks such as the VoicePrivacy Challenge.…

eess.AS2025

GenVC: Self-Supervised Zero-Shot Voice Conversion

Zexin Cai, Henry Li Xinyuan, Ashi Garg +5

Most current zero-shot voice conversion methods rely on externally supervised components, particularly speaker encoders, for training. To explore alternatives that eliminate this d…

eess.AS2025

Rapidly Adapting to New Voice Spoofing: Few-Shot Detection of Synthesized Speech Under Distribution Shifts

Ashi Garg, Zexin Cai, Henry Li Xinyuan +5

We address the challenge of detecting synthesized speech under distribution shifts -- arising from unseen synthesis methods, speakers, languages, or audio conditions -- relative to…

eess.AS2025

Scalable Controllable Accented TTS

Henry Li Xinyuan, Zexin Cai, Ashi Garg +5

We tackle the challenge of scaling accented TTS systems, expanding their capabilities to include much larger amounts of training data and a wider variety of accent labels, even for…

eess.AS2025

ShiftySpeech: A Large-Scale Synthetic Speech Dataset with Distribution Shifts

Ashi Garg, Zexin Cai, Lin Zhang +6

The problem of synthetic speech detection has enjoyed considerable attention, with recent methods achieving low error rates across several established benchmarks. However, to what…