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A critical analysis of two statistical spoken dialog systems in public use

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1 Author(s)
Williams, J.D. ; Microsoft Res., Redmond, WA, USA

This paper examines two statistical spoken dialog systems deployed to the public, extending an earlier study on one system [1]. Results across the two systems show that statistical techniques improved performance in some cases, but degraded performance in others. Investigating degradations, we find the three main causes are (non-obviously) inaccurate parameter estimates, poor confidence scores, and correlations in speech recognition errors. We also find evidence for fundamental weaknesses in the formulation of the model as a generative process, and briefly show the potential of a discriminatively-trained alternative.

Published in:

Spoken Language Technology Workshop (SLT), 2012 IEEE

Date of Conference:

2-5 Dec. 2012