3 papers
cs.SD2026
Comparison of sEMG Encoding Accuracy Across Speech Modes Using Articulatory and Phoneme Features
Chenqian Le, Ruisi Li, Beatrice Fumagalli +6
We test whether Speech Articulatory Coding (SPARC) features can linearly predict surface electromyography (sEMG) envelopes across aloud, mimed, and subvocal speech in twenty-four s…
cs.LG2025
Machine Learning-Based Prediction of Speech Arrest During Direct Cortical Stimulation Mapping
Nikasadat Emami, Amirhossein Khalilian-Gourtani, Jianghao Qian +4
Identifying cortical regions critical for speech is essential for safe brain surgery in or near language areas. While Electrical Stimulation Mapping (ESM) remains the clinical gold…
eess.IV2024
GroupCDL: Interpretable Denoising and Compressed Sensing MRI via Learned Group-Sparsity and Circulant Attention
Nikola Janjusevic, Amirhossein Khalilian-Gourtani, Adeen Flinker +2
Nonlocal self-similarity within images has become an increasingly popular prior in deep-learning models. Despite their successful image restoration performance, such models remain…