Deep Speech Synthesis and Its Implications for News Verification: Lessons Learned in the RTVE-UGR Chair Calderón-González, Daniel Ábalos, Nieves Bayo, Blanca Cánovas, Pedro Griol Barres, David Muñoz-Romero, Carlos Pérez Cernuda, Carmen Vila Fumas, Pere Callejas Carrión, Zoraida audio deepfake speech synthesis voice conversion 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. 2024-11-05T11:15:06Z 2024-11-05T11:15:06Z 2024-10-30 journal article Calderón González, D. et. al. Appl. Sci. 2024, 14, 9916. [https://doi.org/10.3390/app14219916] https://hdl.handle.net/10481/96651 10.3390/app14219916 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional MDPI