From the 1 of 8 linked papers with an AI index.
1 citations · 1 across the 4 of their papers we have counts for
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Detecting Audio Deepfakes on the Edge:Lightweight SSL-Based Detection in a Browser Plugin
Octavian Pascu, Dan Oneata, Horia Cucu +1
Audio deepfakes are a growing challenge for the general public, as well as for journalists and fact-checkers. The latter need reliable tools to verify the authenticity of their sou…
Anchoring the Unknown: Open-Set Model Attribution via Proxy-Anchor Learning
Cristian-Teodor Neamtu, Serban Mihalache, Stefan Smeu +3
The proliferation of text-to-speech (TTS) systems capable of generating realistic synthetic speech poses growing challenges for audio forensics. While binary deepfake detection has…
How Open is Open TTS? A Practical Evaluation of Open Source TTS Tools
Teodora RÄgman, Adrian Bogdan Stânea, Horia Cucu +1
Open-source text-to-speech (TTS) frameworks have emerged as highly adaptable platforms for developing speech synthesis systems across a wide range of languages. However, their appl…
Understanding the strengths and weaknesses of SSL models for audio deepfake model attribution
Gabriel Pîrlogeanu, Adriana Stan, Horia Cucu
Audio deepfake model attribution aims to mitigate the misuse of synthetic speech by identifying the source model responsible for generating a given audio sample, enabling accountab…
Open Source State-Of-the-Art Solution for Romanian Speech Recognition
Gabriel Pirlogeanu, Alexandru-Lucian Georgescu, Horia Cucu
In this work, we present a new state-of-the-art Romanian Automatic Speech Recognition (ASR) system based on NVIDIA's FastConformer architecture--explored here for the first time in…
Unmasking real-world audio deepfakes: A data-centric approach
David Combei, Adriana Stan, Dan Oneata +2
The growing prevalence of real-world deepfakes presents a critical challenge for existing detection systems, which are often evaluated on datasets collected just for scientific pur…