Interactive visualisation techniques for dynamic speech transcription, correction and training

Abstract

As performance gains in automatic speech recognition systems plateau, improvements to existing applications of speech recognition technology seem more likely to come from better user interface design than from further progress in core recognition components. Among all applications of speech recognition, the usability of systems for transcription of spontaneous speech is particularly sensitive to high word error rates. This paper presents a series of approaches to improving the usability of such applications. We propose new mechanisms for error correction, use of contextual information, and use of 3D visualisation techniques to improve user interaction with a recogniser and maximise the impact of user feedback. These proposals are illustrated through several prototypes which target tasks such as: off-line transcript editing, dynamic transcript editing, and real-time visualisation of recognition paths. An evaluation of our dynamic transcript editing system demonstrates the gains that can be made by adding the corrected words to the recogniser's dictionary and then propagating the user's corrections.