Feedback strategies for error correction in speech recognition systems
International Journal of Man-Machine Studies
An overview of audio information retrieval
Multimedia Systems - Special issue on audio and multimedia
Modelling the effects of constraint upon speech-based human-computer interaction
International Journal of Human-Computer Studies
Robust information extraction from automatically generated speech transcriptions
Speech Communication - Special issue on accessing information in spoken audio
Multimodal error correction for speech user interfaces
ACM Transactions on Computer-Human Interaction (TOCHI)
Transcriber: Development and use of a tool for assisting speech corpora production
Speech Communication - Special issue on speech annotation and corpus tools
Word graph based speech rcognition error correction by handwriting input
Proceedings of the 8th international conference on Multimodal interfaces
Collaborative editing for improved usefulness and usability of transcript-enhanced webcasts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Interactive visualisation techniques for dynamic speech transcription, correction and training
Proceedings of the 9th ACM SIGCHI New Zealand Chapter's International Conference on Human-Computer Interaction: Design Centered HCI
Supporting collaborative transcription of recorded speech with a 3D game interface
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part IV
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A set of user interface design techniques for computer-assisted speech transcription are presented and evaluated with respect to task performance and usability. These techniques include error-correction mechanisms which originated in dictation systems and audio editors as well as new techniques developed by us which exploit specific characteristics of existing speech recognition technologies in order to facilitate transcription in settings that typically yield considerable recognition inaccuracy, such as when the speech to be transcribed was produced by different speakers. In particular, we describe a mechanism for dynamic propagation of user feedback which progressively adapts the system to different speakers and lexical contexts. Results of usability and performance evaluation trials indicate that feedback propagation, menu-based correction coupled with keyboard interaction and text-driven audio playback are positively perceived by users and result in improved transcript accuracy.