Patterns of entry and correction in large vocabulary continuous speech recognition systems
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Dasher—a data entry interface using continuous gestures and language models
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
Phrase sets for evaluating text entry techniques
CHI '03 Extended Abstracts on Human Factors in Computing Systems
Text entry using a dual joystick game controller
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Five-key text input using rhythmic mappings
Proceedings of the 9th international conference on Multimodal interfaces
Parakeet: a continuous speech recognition system for mobile touch-screen devices
Proceedings of the 14th international conference on Intelligent user interfaces
Speech dasher: fast writing using speech and gaze
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Designing and evaluating text entry methods
CHI '12 Extended Abstracts on Human Factors in Computing Systems
SpeeG: a multimodal speech- and gesture-based text input solution
Proceedings of the International Working Conference on Advanced Visual Interfaces
Vision-based handwriting recognition for unrestricted text input in mid-air
Proceedings of the 14th ACM international conference on Multimodal interaction
Proceedings of the 14th ACM international conference on Multimodal interaction
Web on the wall: insights from a multimodal interaction elicitation study
Proceedings of the 2012 ACM international conference on Interactive tabletops and surfaces
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With the emergence of smart TVs, set-top boxes and public information screens over the last few years, there is an increasing demand to no longer use these appliances only for passive output. These devices can also be used to do text-based web search as well as other tasks which require some form of text input. However, the design of text entry interfaces for efficient input on such appliances represents a major challenge. With current virtual keyboard solutions we only achieve an average text input rate of 5.79 words per minute (WPM) while the average typing speed on a traditional keyboard is 38 WPM. Furthermore, so-called controller-free appliances such as Samsung's Smart TV or Microsoft's Xbox Kinect result in even lower average text input rates. We present SpeeG2, a multimodal text entry solution combining speech recognition with gesture-based error correction. Four innovative prototypes for the efficient controller-free text entry have been developed and evaluated. A quantitative evaluation of our SpeeG2 text entry solution revealed that the best of our four prototypes achieves an average input rate of 21.04 WPM (without errors), outperforming current state-of-the-art solutions for controller-free text input.