Abstract
Neural interfaces that directly produce intelligible speech from brain activity would allow people with severe impairment from neurological disorders to communicate more naturally. Here, we record neural population activity in motor, premotor and inferior frontal cortices during speech production using electrocorticography (ECoG) and show that ECoG signals alone can be used to generate intelligible speech output that can preserve conversational cues. To produce speech directly from neural data, we adapted a method from the field of speech synthesis called unit selection, in which units of speech are concatenated to form audible output. In our approach, which we call Brain-To-Speech, we chose subsequent units of speech based on the measured ECoG activity to generate audio waveforms directly from the neural recordings. Brain-To-Speech employed the user's own voice to generate speech that sounded very natural and included features such as prosody and accentuation. By investigating the brain areas involved in speech production separately, we found that speech motor cortex provided more information for the reconstruction process than the other cortical areas.
Original language | English (US) |
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Article number | 1267 |
Journal | Frontiers in Neuroscience |
Volume | 13 |
DOIs | |
State | Published - Nov 22 2019 |
Funding
CH, DK, and TS acknowledge funding by BMBF (01GQ1602) and NSF (1608140) as part of the NSF/NIH/BMBF Collaborative Research in Computational Neuroscience Program. MS acknowledges funding by the Doris Duke Charitable Foundation (Clinical Scientist Development Award, grant 2011039), a Northwestern Memorial Foundation Dixon Translational Research Award (including partial funding from NIH National Center for Advancing Translational Sciences, UL1TR000150 and UL1TR001422), NIH grants F32DC015708 and R01NS094748, and NSF grant 1321015. EM acknowledges funding by the NIDCD (grant 1 F32 DC015708-01). Funding. CH, DK, and TS acknowledge funding by BMBF (01GQ1602) and NSF (1608140) as part of the NSF/NIH/BMBF Collaborative Research in Computational Neuroscience Program. MS acknowledges funding by the Doris Duke Charitable Foundation (Clinical Scientist Development Award, grant 2011039), a Northwestern Memorial Foundation Dixon Translational Research Award (including partial funding from NIH National Center for Advancing Translational Sciences, UL1TR000150 and UL1TR001422), NIH grants F32DC015708 and R01NS094748, and NSF grant 1321015. EM acknowledges funding by the NIDCD (grant 1 F32 DC015708-01).
Keywords
- BCI
- ECoG
- brain-computer interface
- brain-to-speech
- speech
- synthesis
ASJC Scopus subject areas
- General Neuroscience