Evaluation of predictive text and speech inputs in a multimodal mobile route guidance application

Authors:
Aleksi Melto;Markku Turunen;Anssi Kainulainen;Jaakko Hakulinen;Tomi Heimonen;Ville Antila
Affiliations:
University of Tampere, Finland;University of Tampere, Finland;University of Tampere, Finland;University of Tampere, Finland;University of Tampere, Finland;University of Tampere, Finland
Venue:
Proceedings of the 10th international conference on Human computer interaction with mobile devices and services
Year:
2008

Citing 3
Cited 3

Fisheye menus

UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
Mobile text entry: relationship between walking speed and text input task difficulty

Proceedings of the 7th international conference on Human computer interaction with mobile devices & services
Spoken and multimodal communication systems in mobile settings

COST 2102'07 Proceedings of the 2007 COST action 2102 international conference on Verbal and nonverbal communication behaviours

User expectations and user experience with different modalities in a mobile phone controlled home entertainment system

Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services
A comparison of speech and GUI input for navigation in complex visualizations on mobile devices

Proceedings of the 12th international conference on Human computer interaction with mobile devices and services
Hype or Ready for Prime Time?: Speech Recognition on Mobile Handheld Devices MASR

International Journal of Handheld Computing Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present initial results from an evaluation of a multimodal interface for a mobile route guidance application providing public transport information in Finland. The application includes a range of input and output modalities, such as speech input and output, a fisheye GUI, and contextual predictive text input. The application has been in public pilot use for almost a year. In this paper we present results from a formal user evaluation, focusing on predictive text input and speech input and output. Speech input outperformed other input methods, even with high error rates and slow response times. However, the domain specific predictive text input was the preferred method, surpassing users' expectations.