AIBullisharXiv – CS AI · Mar 37/103
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A cross-species neural foundation model for end-to-end speech decoding
Researchers developed a new Brain-to-Text (BIT) framework that uses cross-species neural foundation models to decode speech from brain activity with significantly improved accuracy. The system reduces word error rates from 24.69% to 10.22% compared to previous methods and enables seamless translation of both attempted and imagined speech into text.