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An instantaneous voice synthesis neuroprosthesis.

Maitreyee Wairagkar1, Nicholas S Card1, Tyler Singer-Clark1,2

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This study introduces a brain-to-voice neuroprosthesis that synthesizes natural-sounding speech from brain activity. This brain computer interface (BCI) allows individuals with paralysis to communicate expressively, overcoming limitations of text-based systems.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Speech Synthesis

Background:

  • Brain computer interfaces (BCIs) offer communication restoration for individuals with speech loss due to neurological conditions.
  • Current BCIs primarily translate neural activity into text, missing speech's expressive qualities like intonation and prosody.
  • Synthesizing voice directly from neural signals could provide a more natural and nuanced communication method.

Purpose of the Study:

  • To demonstrate a novel "brain-to-voice" neuroprosthesis for real-time speech synthesis.
  • To decode neural activity for both phonemic content and paralinguistic features.
  • To enable individuals with severe speech impairments to communicate expressively via a BCI.

Main Methods:

  • Implanted 256 microelectrodes into the ventral precentral gyrus of a participant with amyotrophic lateral sclerosis and severe dysarthria.
  • Developed a neural decoder to translate intracortical activity into synthesized voice.
  • Incorporated closed-loop audio feedback for real-time voice modulation.
  • Overcame the challenge of training the decoder without ground-truth speech data.

Main Results:

  • Successfully synthesized intelligible and expressive voice from neural activity.
  • Decoded and synthesized paralinguistic features, allowing real-time modulation of intonation, emphasis, and melody.
  • Achieved accurate voice synthesis despite the absence of pre-recorded speech for training.
  • Demonstrated the participant's ability to sing short melodies using the BCI.

Conclusions:

  • The "brain-to-voice" neuroprosthesis is a feasible technology for restoring expressive speech.
  • BCIs can decode complex neural signals for nuanced vocalization, going beyond text-based communication.
  • This technology holds significant potential for improving communication and quality of life for individuals with paralysis.