Cortical encoding of phonemic context during word production

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Brain-computer interfaces that directly decode speech could restore communication to locked-in individuals. However, decoding speech from brain signals still faces many challenges. We investigated decoding of phonemes - the smallest separable parts of speech - from ECoG signals during word production. We expanded on previous efforts to identify specific phoneme by identifying phonemes by where in the word they were formed. We evaluated how the context of phonemes in words affects classification results using linear discriminant analysis. The decoding accuracy of our linear classifier indicated the degree to which the context of a phoneme can be determined from the cortical signal significantly greater than chance. Further, we identified the spectrotemporal features that contributed most to successful decoding of phonemic classes. Finally, we discuss how this can augment speech decoding for neural interfaces.

Original languageEnglish (US)
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6790-6793
Number of pages4
ISBN (Electronic)9781424479290
DOIs
StatePublished - Nov 2 2014
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: Aug 26 2014Aug 30 2014

Publication series

Name2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Other

Other2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
CountryUnited States
CityChicago
Period8/26/148/30/14

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering
  • Medicine(all)

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