3 papers
cs.SD2026
Physics-Informed Neural Operator for Speech Production Analysis
Kazuya Yokota, Xinmeng Luan, Debasish Ray Mohapatra +2
Physics-informed neural operators (PINOs) have recently gained attention as fast numerical simulators with potential for solving inverse problems. This study proposes the first PIN…
cs.SD2025
Physics-Informed Neural Networks for Speech Production
Kazuya Yokota, Ryosuke Harakawa, Masaaki Baba +1
The analysis of speech production based on physical models of the vocal folds and vocal tract is essential for studies on vocal-fold behavior and linguistic research. This paper pr…
eess.AS2025
Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks
Xinmeng Luan, Kazuya Yokota, Gary Scavone
This study investigates the application of Physics-Informed Neural Networks (PINNs) to inverse problems in acoustic tube analysis, focusing on reconstructing acoustic fields from n…