iPhoneme: Brain-to-Text Communication for ALS Using ConformerXL Decoding
Brain-computer interfaces (BCIs) for speech restoration hold transformative potential for the approximately 173,000--232,500 individuals worldwide with ALS-related dysarthria. Despite recent progress, high-performance speech BCIs have been demonstrated in only 22--31 patients globally, largely due to limitations in neural decoding accuracy and practical input interfaces. We present iPhoneme, a brain-to-text communication system that jointly addresses these challenges through integrated modeling and interaction design. The system combines a deep learning phoneme decoder based on a modified Conformer architecture (ConformerXL, 192.9M parameters) with a gaze-assisted phoneme input interface ...
| Authors | Yoonmin Cha, Dawit Chun, Sung Park |
|---|---|
| Primary category | cs.SD |
| Published | 7 April 2026 |
| Last updated at source | 7 April 2026 |
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