How We Swipe: A Large-scale Shape-writing Dataset and Empirical Findings

Luis A. Leiva, Sunjun Kim, Wenzhe Cui, Xiaojun Bi, Antti Oulasvirta

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

42 Lataukset (Pure)

Abstrakti

Despite the prevalence of shape-writing (gesture typing, swype input, or swiping for short) as a text entry method, there are currently no public datasets available. We report a large-scale dataset that can support efforts in both empirical study of swiping as well as the development of better intelligent text entry techniques. The dataset was collected via a web-based custom virtual keyboard, involving 1,338 users who submitted 11,318 unique English words. We report aggregate-level indices on typing performance, user-related factors, as well as trajectory-level data, such as the gesture path drawn on top of the keyboard or the time lapsed between consecutively swiped keys. We find some well-known effects reported in previous studies, for example that speed and error are affected by age and language skill. We also find surprising relationships such that, on large screens, swipe trajectories are longer but people swipe faster.

AlkuperäiskieliEnglanti
OtsikkoProceedings of MobileHCI 2021 - ACM International Conference on Mobile Human-Computer Interaction
AlaotsikkoMobile Apart, MobileTogether
KustantajaACM
Sivumäärä13
ISBN (elektroninen)9781450383288
DOI - pysyväislinkit
TilaJulkaistu - 27 syysk. 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Human-Computer Interaction with Mobile Devices and Services - Virtual, Online, Ranska
Kesto: 27 syysk. 20211 lokak. 2021
Konferenssinumero: 23

Conference

ConferenceInternational Conference on Human-Computer Interaction with Mobile Devices and Services
LyhennettäMobileHCI
Maa/AlueRanska
KaupunkiVirtual, Online
Ajanjakso27/09/202101/10/2021

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