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Neurolinguistic and machine-learning perspectives on direct speech BCIs for restoration of naturalistic communication

Neurolinguistic and machine-learning perspectives on direct speech BCIs for restoration of... AbstractThe ultimate goal of brain-computer-interface (BCI) research on speech restoration is to develop devices which will be able to reconstruct spontaneous, naturally spoken language from the underlying neuronal signals. From this it follows that thorough understanding of brain activity and its functional dynamics during real-world speech will be required. Here, we review current developments in intracranial neurolinguistic and BCI research on speech production under increasingly naturalistic conditions. With an example of neurolinguistic data from our ongoing research, we illustrate the plausibility of neurolinguistic investigations in non-experimental, out-of-the-lab conditions of speech production. We argue that interdisciplinary endeavors at the interface of neuroscience and linguistics can provide valuable insight into the functional significance of speech-related neuronal data. Finally, we anticipate that work with neurolinguistic corpora composed of real-world language samples and simultaneous neuronal recordings, together with machine-learning methodology accounting for the specifics of the neurolinguistic material, will improve the functionality of speech BCIs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Brain-Computer Interfaces Taylor & Francis

Neurolinguistic and machine-learning perspectives on direct speech BCIs for restoration of naturalistic communication

Neurolinguistic and machine-learning perspectives on direct speech BCIs for restoration of naturalistic communication

Abstract

AbstractThe ultimate goal of brain-computer-interface (BCI) research on speech restoration is to develop devices which will be able to reconstruct spontaneous, naturally spoken language from the underlying neuronal signals. From this it follows that thorough understanding of brain activity and its functional dynamics during real-world speech will be required. Here, we review current developments in intracranial neurolinguistic and BCI research on speech production under increasingly...
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Publisher
Taylor & Francis
Copyright
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
ISSN
2326-2621
eISSN
2326-263x
DOI
10.1080/2326263X.2017.1330611
Publisher site
See Article on Publisher Site

Abstract

AbstractThe ultimate goal of brain-computer-interface (BCI) research on speech restoration is to develop devices which will be able to reconstruct spontaneous, naturally spoken language from the underlying neuronal signals. From this it follows that thorough understanding of brain activity and its functional dynamics during real-world speech will be required. Here, we review current developments in intracranial neurolinguistic and BCI research on speech production under increasingly naturalistic conditions. With an example of neurolinguistic data from our ongoing research, we illustrate the plausibility of neurolinguistic investigations in non-experimental, out-of-the-lab conditions of speech production. We argue that interdisciplinary endeavors at the interface of neuroscience and linguistics can provide valuable insight into the functional significance of speech-related neuronal data. Finally, we anticipate that work with neurolinguistic corpora composed of real-world language samples and simultaneous neuronal recordings, together with machine-learning methodology accounting for the specifics of the neurolinguistic material, will improve the functionality of speech BCIs.

Journal

Brain-Computer InterfacesTaylor & Francis

Published: Jul 3, 2017

Keywords: BCI; ECoG; speech production; neurolinguistics; real-world communication

References