Demonstrating TapType for mobile ten-finger text entry anywhere
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Author / Producer
Date
2022-04-27
Publication Type
Other Conference Item
ETH Bibliography
yes
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Abstract
We demonstrate a mobile text entry system that brings full-size ten-finger typing to everyday surfaces, allowing users to type anywhere. Our wearable wristband TapType integrates accelerometers that sense vibrations arising from finger taps against a passive surface, from which our Bayesian neural network estimates a probability distribution over the fingers of the hand. Given a pre-defined key-finger mapping, our text entry decoder fuses these predictions with the character priors of an n-gram language model to decode the input text entered by the user. TapType combines high portability with sustained rapid bimanual input across the full space, which we demonstrate at the example of supplementing text input on mobile touch devices, in eyes-free scenarios using audio feedback, and in a situated Mixed Reality scenario to enable typing outside visual control with passive haptic feedback.
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Publication status
published
External links
Book title
CHI EA '22: CHI Conference on Human Factors in Computing Systems Extended Abstracts
Journal / series
Volume
Pages / Article No.
195
Publisher
Association for Computing Machinery
Event
2022 Conference on Human Factors in Computing Systems (CHI 2022)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Mobile text entry; Invisible interfaces; Bayesian inference; Bayesian neural network; N-gram language model; Virtual reality
Organisational unit
09649 - Holz, Christian / Holz, Christian
Notes
Extended abstract.