Patterns of entry and correction in large vocabulary continuous speech recognition systems
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Multimodal error correction for speech user interfaces
ACM Transactions on Computer-Human Interaction (TOCHI)
Conversational interface technologies
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Text Entry Systems: Mobility, Accessibility, Universality
Text Entry Systems: Mobility, Accessibility, Universality
On the benefits of confidence visualization in speech recognition
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Captioning for deaf and hard of hearing people by editing automatic speech recognition in real time
ICCHP'06 Proceedings of the 10th international conference on Computers Helping People with Special Needs
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HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: interaction modalities and techniques - Volume Part IV
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This paper describes changes in user error correction strategies over time in the use of large vocabulary desktop automatic speech recognition (ASR) systems. Users with minimal practice with such systems were found to have considerable difficulty with error correction [1,2]. Users with more extensive use were found to have improved overall performance compared to initial use subjects. This is attributed to development of multimodal strategies for error correction rather than to significantly improved speech recognition rates or use of speech-based error correction techniques. These results point to the importance of multimodal interaction in the acceptance of speech recognition technology.