19 citations · 22 across the 5 of their papers we have counts for
5 papers
A cross-species neural foundation model for end-to-end speech decoding
Yizi Zhang, Linyang He, Chaofei Fan +9
Speech brain-computer interfaces (BCIs) aim to restore communication for people with paralysis by translating neural activity into text. Most systems use cascaded frameworks that d…
Brain-to-Text Benchmark '24: Lessons Learned
Francis R. Willett, Jingyuan Li, Trung Le +13
Speech brain-computer interfaces aim to decipher what a person is trying to say from neural activity alone, restoring communication to people with paralysis who have lost the abili…
Towards a Quantitative Analysis of Coarticulation with a Phoneme-to-Articulatory Model
Chaofei Fan, Jaimie M. Henderson, Chris Manning +1
Prior coarticulation studies focus mainly on limited phonemic sequences and specific articulators, providing only approximate descriptions of the temporal extent and magnitude of c…
A Cross-Modal Approach to Silent Speech with LLM-Enhanced Recognition
Tyler Benster, Guy Wilson, Reshef Elisha +2
Silent Speech Interfaces (SSIs) offer a noninvasive alternative to brain-computer interfaces for soundless verbal communication. We introduce Multimodal Orofacial Neural Audio (MON…
Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication
Chaofei Fan, Nick Hahn, Foram Kamdar +6
Intracortical brain-computer interfaces (iBCIs) have shown promise for restoring rapid communication to people with neurological disorders such as amyotrophic lateral sclerosis (AL…