Modelling the effects of constraint upon speech-based human–computer interaction

Hone, Kate; Baber, Chris

doi:10.1006/ijhc.1998.0235

Cited by 11 publications

(3 citation statements)

References 18 publications

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“…Error correction methods employed in dictation systems [21], for instance, is very different from repair in dialogue systems [10]. Such techniques usually involve error recognition via the visual modality and repair through speech interaction ("respeaking") [1] or, more recently, through combinations of modalities [21,8,11].…”

Section: Related Workmentioning

confidence: 99%

Interface design strategies for computer-assisted speech transcription

Luz

Masoodian

Rogers

et al. 2008

Proceedings of the 20th Australasian Conference on Computer-Human Interaction: Designing for Habitus and Habitat

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A set of user interface design techniques for computerassisted 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.

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Section: Related Workmentioning

confidence: 99%

Interface design strategies for computer-assisted speech transcription

Luz

Masoodian

Rogers

et al. 2008

Proceedings of the 20th Australasian Conference on Computer-Human Interaction: Designing for Habitus and Habitat

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“…His work models the impact of error correction and degradation of recognition accuracy on transaction time. We have used unit-task-network models (speci"cally MicroSaint) to investigate error correction and the e!ects of constraint on speech-based interaction with computers (Baber & Hone, 1993;Hone & Baber, 1999). Examination of the issues surrounding the combination of unit-times for prediction of human performance raises questions concerning the scheduling of unit-tasks and the coordination of activity.…”

Section: Predicting Transaction Timementioning

confidence: 99%

Using critical path analysis to model multimodal human–computer interaction

Baber¹,

Mellor²

2001

International Journal of Human-Computer Studies

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“…The issue of error correction has been extensively studied in the area of spoken language dialogue systems where recognition rates and user acceptance of an imperfect input modality can be improved through clever interaction design and exploitation of domain constraints [2]. In applications such as dictation systems, for which domain-specific constraints will not readily come to the rescue of system designers, userspecific factors can sometimes be brought to bear.…”

Section: Introductionmentioning

confidence: 99%

A system for dynamic 3D visualisation of speech recognition paths

Luz

Masoodian

Rogers

et al. 2008

Proceedings of the Working Conference on Advanced Visual Interfaces

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This paper presents an interactive visualisation system that assists users of semi-automatic speech transcription systems to assess alternative recognition results in real time and provide feedback to the speech recognition back-end in an intuitive manner. This prototype uses the OpenGL libraries to implement an animated 3D visual representation of alternative recognition results generated by the Sphinx automatic speech recognition system. It is expected that displaying alternatives dynamically will facilitate early detection of recognition errors and encourage user interaction, which in turn can be used to improve future recognition performance.

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Modelling the effects of constraint upon speech-based human–computer interaction

Cited by 11 publications

References 18 publications

Interface design strategies for computer-assisted speech transcription

Interface design strategies for computer-assisted speech transcription

Using critical path analysis to model multimodal human–computer interaction

A system for dynamic 3D visualisation of speech recognition paths

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