Engineering and Technology

A high-performance speech neuroprosthesis

F. R. Willett, E. M. Kunz, et al.

This groundbreaking study reveals a high-performance speech-to-text brain-computer interface that significantly enhances accuracy and speed, even for participants with ALS, achieving a remarkable 9.1% error rate on a 50-word vocabulary. The innovative research conducted by Francis R. Willett and colleagues uncovers the intricate relationship between speech articulators and cortical representation, paving the way for future advancements.

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Abstract

This study demonstrates a high-performance speech-to-text brain-computer interface (BCI) achieving significantly improved accuracy and speed compared to previous systems. A participant with amyotrophic lateral sclerosis (ALS) achieved a 9.1% word error rate on a 50-word vocabulary and 23.8% on a 125,000-word vocabulary, decoded at 62 words per minute. The findings highlight the spatially intermixed tuning to speech articulators in the cortex and a detailed articulatory representation that facilitates accurate decoding.

Publisher

Nature

Published On

Jul 26, 2024

Authors

Francis R. Willett, Erin M. Kunz, Chaofei Fan, Donald T. Avansino, Guy H. Wilson, Eun Young Cho, Foram Kamdar, Matthew F. Glasser, Leigh R. Hochberg, Shaul Druckmann, Krishna V. Shenoy, Jaime M. Henderson

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