VelociWatch: Designing and Evaluating a Virtual Keyboard for the Input of Challenging Text

Keith Vertanen, Dylan Gaines, Crystal Fletcher, Alex M. Stanage, Robbie Watling, Per Ola Kristensson

CHI '19: Proceedings of the ACM Conference on Human Factors in Computing Systems, 2019.

Virtual keyboard typing is typically aided by an auto-correct method that decodes a user's noisy taps into their intended text. This decoding process can reduce error rates and possibly increase entry rates by allowing users to type faster but less precisely. However, virtual keyboard decoders sometimes make mistakes that change a user's desired word into another. This is particularly problematic for challenging text such as proper names. We investigate whether users can guess words that are likely to cause auto-correct problems and whether users can adjust their behavior to assist the decoder. We conduct computational experiments to decide what predictions to offer in a virtual keyboard and design a smartwatch keyboard named VelociWatch. Novice users were able to use the features of VelociWatch to enter challenging text at 17 words-per-minute with a corrected error rate of 3%. Interestingly, they wrote slightly faster and just as accurately on a simpler keyboard with limited correction options. Our finding suggest users may be able to type difficult words on a smartwatch simply by tapping precisely without the use of auto-correct.