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
The Unreliability of Acoustic Systems in Alzheimer's Speech Datasets with Heterogeneous Recording Conditions
Lara Gauder, Pablo Riera, Andrea Slachevsky, Gonzalo Forno, Adolfo M. Garcia, Luciana Ferrer
SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and Synthesis
Helin Wang, Meng Yu, Jiarui Hai, Chen Chen, Yuchen Hu, Rilin Chen, Najim Dehak, Dong Yu
Classifying populist language in American presidential and governor speeches using automatic text analysis
Olaf van der Veen, Semir Dzebo, Levi Littvay, Kirk Hawkins, Oren Dar
Infusing Acoustic Pause Context into Text-Based Dementia Assessment
Franziska Braun, Sebastian P. Bayerl, Florian Hönig, Hartmut Lehfeld, Thomas Hillemacher, Tobias Bocklet, Korbinian Riedhammer
YOLO-Stutter: End-to-end Region-Wise Speech Dysfluency Detection
Xuanru Zhou, Anshul Kashyap, Steve Li, Ayati Sharma, Brittany Morin, David Baquirin, Jet Vonk, Zoe Ezzes, Zachary Miller, Maria Luisa Gorno Tempini, Jiachen Lian, Gopala Krishna Anumanchipalli