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dc.contributor.authorVertanen, Keith
dc.contributor.authorMemmi, Haythem
dc.contributor.authorEmge, Justin
dc.contributor.authorReyal, Shyam Mehraaj
dc.contributor.authorKristensson, Per Ola
dc.date.accessioned2015-06-30T16:10:01Z
dc.date.available2015-06-30T16:10:01Z
dc.date.issued2015-04-18
dc.identifier.citationVertanen , K , Memmi , H , Emge , J , Reyal , S M & Kristensson , P O 2015 , VelociTap : investigating fast mobile text entry using sentence-based decoding of touchscreen keyboard input . in CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems . ACM , New York , pp. 659-668 , The 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI) , Seoul , Korea, Republic of , 18/04/15 . https://doi.org/10.1145/2702123.2702135en
dc.identifier.citationconferenceen
dc.identifier.isbn9781450331456
dc.identifier.otherPURE: 190332289
dc.identifier.otherPURE UUID: bc0f4b66-59f9-4242-8000-8c6ff5030e64
dc.identifier.otherScopus: 84951004741
dc.identifier.otherWOS: 000412395500077
dc.identifier.urihttp://hdl.handle.net/10023/6884
dc.descriptionDate of Acceptance: 15/12/2014en
dc.description.abstractWe present VelociTap: a state-of-the-art touchscreen keyboard decoder that supports a sentence-based text entry approach. VelociTap enables users to seamlessly choose from three word-delimiter actions: pushing a space key, swiping to the right, or simply omitting the space key and letting the decoder infer spaces automatically. We demonstrate that VelociTap has a significantly lower error rate than Google's keyboard while retaining the same entry rate. We show that intermediate visual feedback does not significantly affect entry or error rates and we find that using the space key results in the most accurate results. We also demonstrate that enabling flexible word-delimiter options does not incur an error rate penalty. Finally, we investigate how small we can make the keyboard when using VelociTap. We show that novice users can reach a mean entry rate of 41 wpm on a 40 mm wide smartwatch-sized keyboard at a 3% character error rate.
dc.format.extent9
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofCHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systemsen
dc.rightsPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others thanACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. Copyright c 2015 ACMen
dc.subjectMobile text entryen
dc.subjectTouchscreen keyboarden
dc.subjectSentence decodingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectNDASen
dc.subject.lccQA75en
dc.titleVelociTap : investigating fast mobile text entry using sentence-based decoding of touchscreen keyboard inputen
dc.typeConference itemen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1145/2702123.2702135


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