Séminaire « Neural Signal Interpretation for Spoken Communication » – 25/04/2024

22 avril 2024

On Thursday 25 April at 11am, we will host a talk from Prof. Tanja Schultz on « Neural Signal Interpretation for Spoken Communication ».   The room will be defined later.   Please find below a short abstract and bio from Prof. Tanja Schultz.   Abstract:  This talk presents advancements in decoding neural signals, providing further insights into the intricacies of spoken communication. Delving into both speech production and speech perception, we discuss low latency processing of neural signals from surface EEG, stereotactic EEG, and intracranial EEG using machine learning methods. Practical implications and human-centered applications are considered, including silent speech interfaces, neuro-speech prostheses, and the detection of auditory attention and distraction in communication. This presentation aims to spark curiosity about the evolving landscape of neural signal interpretation and its impact on the future of spoken communication. Bio: Tanja Schultz received the diploma and doctoral degrees in Informatics from University of Karlsruhe and a Master degree in Mathematics and Sport Sciences from Heidelberg University, both in  Germany. Since 2015 she is Professor for Cognitive Systems of the Faculty of Mathematics & Computer Science at the University of Bremen, Germany. Prior to Bremen she spent 7 years as Professor for Cognitive Systems at KIT (2007-2015) Plus d'infos

Soutenance de Thèse Imen Ben-Amor – 25/04/2024

15 avril 2024

Lieu: Centre d’Enseignement et de Recherche en Informatique (CERI), Amphi ADA – 339 Chemin des Meinajaries, CERI, 84000 Avignon. You can also attend the defense via video conference, using this link . You can fin the slides here. The jury members are the following: Pr. Tomi KINNUNEN, University of Eastern Finland – RapporteurPr. Alessandro VINCIARELLI, University of Glasgow – RapporteurPr. Tanja SCHULTZ, University Bremen- ExaminatricePr. Didier MEUWLY, Netherlands Forensic Institute, University of Twente- ExaminateurPr. Corinne FREDOUILLE, LIA, Université d’Avignon- ExaminatricePr. JEAN-FRANCOIS BONASTRE, Inria, LIA, Université d’Avignon – Directeur de thèse TITLE: Deep modeling based on voice attributes for explainable speaker recognition. Application in the forensic domain. Abstract:Automatic speaker recognition (ASpR) has been integrated into critical applications, ranging from customised assistant services to security systems and forensic investigations. It aims to automatically determine whether two voice samples originate from the same speaker. These systems primarily rely on complex deep neural networks (DNN) and present their results by a single value. Despite the high performance demonstrated by DNN-based ASpR systems, they struggle to provide transparent insights into the nature of speech representations, its encoding, and its use in decision-making process. This lack of transparency presents significant challenges in addressing ethical and legal Plus d'infos