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20212026
most citedHuman Perception of Audio Deepfakes

66 citations · 68 across the 6 of their papers we have counts for

collaborators

6 papers

cs.HC2026

Disclosure By Design: Identity Transparency as a Behavioural Property of Conversational AI Models

Anna Gausen, Sarenne Wallbridge, Hannah Rose Kirk +2

As conversational AI systems become more realistic and widely deployed, users are increasingly uncertain about whether they are interacting with a human or an AI system. When AI id…

cs.CY2024★ 2 cited

Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity

Sarah Kiden, Bernd Stahl, Beverley Townsend +22

This report presents a comprehensive response to the United Nation's Interim Report on Governing Artificial Intelligence (AI) for Humanity. It emphasizes the transformative potenti…

cs.SD2024

Voice Conversion-based Privacy through Adversarial Information Hiding

Jacob J Webber, Oliver Watts, Gustav Eje Henter +2

Privacy-preserving voice conversion aims to remove only the attributes of speech audio that convey identity information, keeping other speech characteristics intact. This paper pre…

cs.SD2024

A New Approach to Voice Authenticity

Nicolas M. Müller, Piotr Kawa, Shen Hu +4

Voice faking, driven primarily by recent advances in text-to-speech (TTS) synthesis technology, poses significant societal challenges. Currently, the prevailing assumption is that…

cs.AI2023

Protecting Publicly Available Data With Machine Learning Shortcuts

Nicolas M. Müller, Maximilian Burgert, Pascal Debus +3

Machine-learning (ML) shortcuts or spurious correlations are artifacts in datasets that lead to very good training and test performance but severely limit the model's generalizatio…

cs.HC2021★ 66 cited

Human Perception of Audio Deepfakes

Nicolas M. Müller, Karla Pizzi, Jennifer Williams

The recent emergence of deepfakes has brought manipulated and generated content to the forefront of machine learning research. Automatic detection of deepfakes has seen many new ma…