EchoWrite: An Acoustic-Based Finger Input System Without Training
| Autor: | Kaishun Wu, Yongpan Zou, Qiang Yang, Baojie Yuan, Mo Li, Rukhsana Ruby |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer Networks and Communications
business.industry Computer science Mobile computing Training (meteorology) 020206 networking & telecommunications 02 engineering and technology Text recognition Smartwatch User experience design Human–computer interaction 0202 electrical engineering electronic engineering information engineering Overhead (computing) Electrical and Electronic Engineering business Software Wearable technology |
| Zdroj: | IEEE Transactions on Mobile Computing. 20:1789-1803 |
| ISSN: | 2161-9875 1536-1233 |
| DOI: | 10.1109/tmc.2020.2973094 |
| Popis: | Recently, wearable devices have become increasingly popular in our lives because of their neat features and stylish appearance. However, their tiny sizes bring about new challenges to human-device interaction such as texts input. Although some novel methods have been put forward, they possess different defects and are not applicable to deal with the problem. As a result, we propose an acoustic-based texts-entry system, i.e., EchoWrite, by which texts can be entered with a finger writing in the air without wearing any additional device. More importantly, different from many previous works, EchoWrite runs in a training-free style which reduces the training overhead and improves system scalability. We implement EchoWrite with commercial devices and conduct comprehensive experiments to evaluate its texts-entry performance. Experimental results show that EchoWrite enables users to enter texts at a speed of 7.5 WPM without practice, and 16.6 WPM after about 30-minute practice. This speed is better than touch screen-based method on smartwatches, and comparable with previous related works. Moreover, EchoWrite provides favorable user experience of entering texts. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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