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
TRESTLE: Toolkit for Reproducible Execution of Speech, Text and Language Experiments
Changye Li, Weizhe Xu, Trevor Cohen, Martin Michalowski, Serguei Pakhomov
Synthesizing audio from tongue motion during speech using tagged MRI via transformer
Xiaofeng Liu, Fangxu Xing, Jerry L. Prince, Maureen Stone, Georges El Fakhri, Jonghye Woo