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Towards speech-based brain-computer interfaces: finding most distinguishable word articulations with autoencoders

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorKlink, P.C.
dc.contributor.authorStolwijk, Eli
dc.date.accessioned2023-01-30T01:00:47Z
dc.date.available2023-01-30T01:00:47Z
dc.date.issued2023
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/43475
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThis thesis aims to find a set of words that are most easily distinghuishable in terms of their articulation pattern for use in further research in communication BCI's
dc.titleTowards speech-based brain-computer interfaces: finding most distinguishable word articulations with autoencoders
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuArtificial Intelligence
dc.thesis.id13283


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