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dc.contributor.authorKristensson, Per Olaen
dc.contributor.authorLilley, Jamesen
dc.contributor.authorBlack, Rolfen
dc.contributor.authorWaller, Annaluen
dc.contributor.editorBernhaupt, Ren
dc.contributor.editorMueller, FFen
dc.contributor.editorVerweij, Den
dc.contributor.editorAndres, Jen
dc.contributor.editorMcGrenere, Jen
dc.contributor.editorCockburn, Aen
dc.contributor.editorAvellino, Ien
dc.contributor.editorGoguey, Aen
dc.contributor.editorBjøn, Pen
dc.contributor.editorZhao, Sen
dc.contributor.editorSamson, BPen
dc.contributor.editorKocielnik, Ren
dc.date.accessioned2020-01-29T11:47:19Z
dc.date.available2020-01-29T11:47:19Z
dc.date.issued2020en
dc.identifier.isbn978-1-4503-6708-0en
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/301405
dc.description.abstractNonspeaking individuals with motor disabilities typically have very low communication rates. This paper proposes a design engineering approach for quantitatively exploring contextaware sentence retrieval as a promising complementary input interface, working in tandem with a word-prediction keyboard. We motivate the need for complementary design engineering methodology in the design of augmentative and alternative communication and explain how such methods can be used to gain additional design insights. We then study the theoretical performance envelopes of a context-aware sentence retrieval system, identifying potential keystroke savings as a function of the parameters of the subsystems, such as the accuracy of the underlying auto-complete word prediction algorithm and the accuracy of sensed context information under varying assumptions. We find that context-aware sentence retrieval has the potential to provide users with considerable improvements in keystroke savings under reasonable parameter assumptions of the underlying subsystems. This highlights how complementary design engineering methods can reveal additional insights into design for augmentative and alternative communication.
dc.titleA Design Engineering Approach for Quantitatively Exploring Context-Aware Sentence Retrieval for Nonspeaking Individuals with Motor Disabilities.en
dc.typeConference Object
prism.endingPage11
prism.publicationDate2020en
prism.publicationNameCHIen
prism.publicationNameCHI '20: CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA, April 25-30, 2020en
prism.startingPage1
dc.identifier.doi10.17863/CAM.48483
dcterms.dateAccepted2020-01-16en
rioxxterms.versionAM*
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2020en
rioxxterms.typeConference Paper/Proceeding/Abstracten
pubs.funder-project-idEPSRC (EP/N014278/1)
pubs.funder-project-idEPSRC (via University of Dundee) (7836a-CRT)
dc.identifier.urlhttps://dl.acm.org/doi/proceedings/10.1145/3313831en
rioxxterms.freetoread.startdate2020-05-01


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