Speech Analysis
Speech analysis is a rapidly evolving field focused on understanding and manipulating spoken language using computational methods, aiming to improve human-computer interaction and address challenges in healthcare and other domains. Current research emphasizes developing robust models, often based on transformer networks and neural codecs, for tasks such as speech recognition, emotion detection, and generation, including handling multi-speaker scenarios and low-resource languages. These advancements have significant implications for applications ranging from improved accessibility for individuals with speech impairments to more natural and intuitive interfaces for various technologies, as well as enabling new diagnostic tools in healthcare.
Papers
Parole de présidents (1958-2022)
Dominique Labbé, Jacques Savoy
GPT as ghostwriter at the White House
Jacques Savoy
Wearable intelligent throat enables natural speech in stroke patients with dysarthria
Chenyu Tang, Shuo Gao, Cong Li, Wentian Yi, Yuxuan Jin, Xiaoxue Zhai, Sixuan Lei, Hongbei Meng, Zibo Zhang, Muzi Xu, Shengbo Wang, Xuhang Chen, Chenxi Wang, Hongyun Yang, Ningli Wang, Wenyu Wang, Jin Cao, Xiaodong Feng, Peter Smielewski, Yu Pan, Wenhui Song, Martin Birchall, Luigi G. Occhipint
Machine Unlearning reveals that the Gender-based Violence Victim Condition can be detected from Speech in a Speaker-Agnostic Setting
Emma Reyner-Fuentes, Esther Rituerto-Gonzalez, Carmen Pelaez-Moreno
Exploiting Phonological Similarities between African Languages to achieve Speech to Speech Translation
Peter Ochieng, Dennis Kaburu
Lina-Speech: Gated Linear Attention is a Fast and Parameter-Efficient Learner for text-to-speech synthesis
Théodor Lemerle, Harrison Vanderbyl, Vaibhav Srivastav, Nicolas Obin, Axel Roebel