C-PAK: Correcting and Completing Variable-Length Prefix-Based Abbreviated Keystrokes

Author:

Li Tianshi1ORCID,Quinn Philip2ORCID,Zhai Shumin2ORCID

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

2. Google, CA, USA

Abstract

Improving keystroke savings is a long-term goal of text input research. We present a study into the design space of an abbreviated style of text input called C-PAK (Correcting and completing variable-length Prefix-based Abbreviated Keystrokes) for text entry on mobile devices. Given a variable length and potentially inaccurate input string (e.g., “li g t m”), C-PAK aims to expand it into a complete phrase (e.g., “looks good to me”). We develop a C-PAK prototype keyboard, PhraseWriter , based on a current state-of-the-art mobile keyboard consisting of 1.3 million n -grams and 164,000 words. Using computational simulations on a large dataset of realistic input text, we found that, in comparison to conventional single-word suggestions, PhraseWriter improves the maximum keystroke savings rate by 6.7% (from 46.3% to 49.4,), reduces the word error rate by 14.7%, and is particularly advantageous for common phrases. We conducted a lab study of novice user behavior and performance which found that users could quickly utilize the C-PAK style abbreviations implemented in PhraseWriter, achieving a higher keystroke savings rate than forward suggestions (25% vs. 16%). Furthermore, they intuitively and successfully abbreviated more with common phrases. However, users had a lower overall text entry rate due to their limited experience with the system (28.5 words per minute vs. 37.7). We outline future technical directions to improve C-PAK over the PhraseWriter baseline, and further opportunities to study the perceptual, cognitive, and physical action trade-offs that underlie the learning curve of C-PAK systems.

Publisher

Association for Computing Machinery (ACM)

Subject

Human-Computer Interaction

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