Deep Speech Synthesis and Its Implications for News Verification: Lessons Learned in the RTVE-UGR Chair
Metadatos
Mostrar el registro completo del ítemAutor
Calderón-González, Daniel; Ábalos, Nieves; Bayo, Blanca; Cánovas, Pedro; Griol Barres, David; Muñoz-Romero, Carlos; Pérez Cernuda, Carmen; Vila Fumas, Pere; Callejas Carrión, ZoraidaEditorial
MDPI
Materia
audio deepfake speech synthesis voice conversion
Fecha
2024-10-30Referencia bibliográfica
Calderón González, D. et. al. Appl. Sci. 2024, 14, 9916. [https://doi.org/10.3390/app14219916]
Patrocinador
Project IVERES (PLEC2021-008176), financed by MCIN/AEI/10.13- 039/501100011033; European Union “NextGenerationEU”/PRTR; RTVE-UGR ChairResumen
This paper presents the multidisciplinary work carried out in the RTVE-UGR Chair within
the IVERES project, whose main objective is the development of a tool for journalists to verify the
veracity of the audios that reach the newsrooms. In the current context, voice synthesis has both
beneficial and detrimental applications, with audio deepfakes being a significant concern in the world
of journalism due to their ability to mislead and misinform. This is a multifaceted problem that can
only be tackled adopting a multidisciplinary perspective. In this article, we describe the approach
we adopted within the RTVE-UGR Chair to successfully address the challenges derived from audio
deepfakes involving a team with different backgrounds and a specific methodology of iterative
co-creation. As a result, we present several outcomes including the compilation and generation of
audio datasets, the development and deployment of several audio fake detection models, and the
development of a web audio verification tool addressed to journalists. As a conclusion, we highlight
the importance of this systematic collaborative work in the fight against misinformation and the
future potential of audio verification technologies in various applications.