International Journal of Man-Machine Studies
Feedback strategies for error correction in speech recognition systems
International Journal of Man-Machine Studies
Modeling error recovery and repair in automatic speech recognition
International Journal of Man-Machine Studies
Data-entry by voice: facilitating correction of misrecognitions
Interactive speech technology
Patterns of entry and correction in large vocabulary continuous speech recognition systems
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Model-based and empirical evaluation of multimodal interactive error correction
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Ten myths of multimodal interaction
Communications of the ACM
Providing integrated toolkit-level support for ambiguity in recognition-based interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Taming recognition errors with a multimodal interface
Communications of the ACM
Multimodal error correction for speech user interfaces
ACM Transactions on Computer-Human Interaction (TOCHI)
INTERACT '90 Proceedings of the IFIP TC13 Third Interational Conference on Human-Computer Interaction
Error recovery in a blended style eye gaze and speech interface
Proceedings of the 5th international conference on Multimodal interfaces
Multimodal error correction for continuous handwriting recognition in pen-based user interfaces
Proceedings of the 11th international conference on Intelligent user interfaces
Audio-visual speech modeling for continuous speech recognition
IEEE Transactions on Multimedia
Multimodal Chinese text entry with speech and keypad on mobile devices
Proceedings of the 13th international conference on Intelligent user interfaces
Multi-modal text entry and selection on a mobile device
Proceedings of Graphics Interface 2010
Understanding, Manipulating and Searching Hand-Drawn Concept Maps
ACM Transactions on Intelligent Systems and Technology (TIST)
Stroke++: A new Chinese input method for touch screen mobile phones
International Journal of Human-Computer Studies
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In recognition-based user interface, users' satisfaction is determined not only by recognition accuracy but also by effort to correct recognition errors. In this paper, we introduce a crossmodal error correction technique, which allows users to correct errors of Chinese handwriting recognition by speech. The focus of the paper is a multimodal fusion algorithm supporting the crossmodal error correction. By fusing handwriting and speech recognition, the algorithm can correct errors in both character extraction and recognition of handwriting. The experimental result indicates that the algorithm is effective and efficient. Moreover, the evaluation also shows the correction technique can help users to correct errors in handwriting recognition more efficiently than the other two error correction techniques.