Toshiyuki Hagiya
Tatsuya Kawahara
ABSTRACT
Many older adults are interested in smartphones but encounter difficulties in self-instruction and need support, especially text input. Voice input is a useful option for text input, but also presents some difficulties for older adults.In this paper, we propose a tutoring system for voice input that detects input stumbles using a statistical approach and provides instructions to overcome them. We construct the tutoring system based on the data from a user study with novice older adults. In an evaluation experiment, the number of input stumble and the sentence completion time of the participants using the tutoring system were significantly smaller than those without it. The results showed that the tutoring system resulted in the improvement of the efficiency of voice input for novice older adults.
- Beverly Beisge and Marilyn Kraitchman. 2003. Senior Centers: Opportunities For Successful Aging. Springer Publishing Company (2003).Google Scholar
- Google. 2017a. Android Developers. (2017). https://developer.android.com/index.html.Google Scholar
- Google. 2017b. Cloud Speech API. (2017). https://cloud.google.com/speech.Google Scholar
- Masataka Goto, Katunobu Itou, and Satoru Hayamizu. 2002. Speech Completion: On-demand Completion Assistance Using Filled Pauses for Speech Input Interfaces. In Proceedings of the 7th International Conference on Spoken Language Processing (ICSLP '02). World Academy of Science, Engineering and Technology (WASET), 1489--1492.Google ScholarCross Ref
- Toshiyuki Hagiya, Toshiharu Horiuchi, and Tomonori Yazaki. 2016. Typing Tutor: Individualized Tutoring in Text Entry for Older Adults Based on Input Stumble Detection. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '16). ACM, 733--744. Google ScholarDigital Library
- Caitlin Kelleher and Randy Pausch. 2005. Stencils-based tutorials: Design and evaluation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '05). ACM, 541--550. Google ScholarDigital Library
- Taku Kudoh, Tsuyoshi Fukui, Takashi Okamoto, and Matt Francis. 2017. lucene-gosen. (2017). https://github.com/lucene-gosen.Google Scholar
- Rock Leung, Charlotte Tang, Shathel Haddad, Joanna Mcgrenere, Peter Graf, and Vilia Ingriany. 2012. How older adults learn to use mobile devices: Survey and field investigations. ACM Transactions on Accessible Computing 4, 3 (2012), 11:1--11:33. Google ScholarDigital Library
- Yuan Liang, Koji Iwano, and Koichi Shinoda. 2014. Simple Gesture-based Error Correction Interface for Smartphone Speech Recognition. In Proceedings of the 15th Annual Conference of the International Speech Communication Association International Conference on Science and Technology for Humanity (INTERSPEECH '14). International Speech Communication Association (ISCA), 1194--1198.Google ScholarCross Ref
- Roger W. Morrell, Denise C. Park, Christopher B. Mayhorn, and Catherine L. Kelley. 2000. Effects of age and instructions on teaching older adults to use eldercomm, an electronic bulletin board system. Educational Gerontology 26, 3 (2000), 221--235.Google ScholarCross Ref
- Jun Ogata and Masataka Goto. 2005. Speech Repair: Quick Error Correction Just by Using Selection Operation for Speech Input Interfaces. In Proceedings of the 9th European Conference on Speech Communication and Technology (Eurospeech '05). International Speech Communication Association (ISCA), 133--136.Google ScholarCross Ref
- Pei-Luen Patrick Rau and Jia-Wen Hsu. 2005. Interaction Devices and Web Design for Novice Older Users. Educational Gerontology 31, 1 (2005), 19--40.Google ScholarCross Ref
- Wendy A. Rogers, Elizabeth F. Cabrera, Ne Walker, D. Kristen Gilbert, and Arthur D. Fisk. 1996. A survey of automatic teller machine usage across the adult lifespan. Human Factors (1996), 38,1; 156--166.Google Scholar
- Yuan Tang. 2016. TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning. In arXiv. 1612.04251.Google Scholar
Index Terms
- Voice Input Tutoring System for Older Adults using Input Stumble Detection
Recommendations
Older Adults and Voice Interaction: A Pilot Study with Google Home
CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing SystemsIn this paper we present the results of an exploratory study examining the potential of voice assistants (VA) for some groups of older adults in the context of Smart Home Technology (SHT). To research the aspect of older adults' interaction with voice ...
Recruiting Older Adults in the Wild: Reflections on Challenges and Lessons Learned from Research Experience
PervasiveHealth '18: Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for HealthcareIt is important to understand the older adults prior to the design process. The understanding can better facilitate design conversations between the researchers and the older adults. In this paper, we discussed our experiences of building a relationship ...
Older Adults' Digital Gameplay
Background. Empirical evidence suggests that digital gameplay can enhance social interaction and improve cognition for older adults. However, if digital games are to be effectively used as interventions to address age-related challenges, it is important ...
Comments