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ICASSP
2009
IEEE

From rule-based to statistical grammars: Continuous improvement of large-scale spoken dialog systems

13 years 7 months ago
From rule-based to statistical grammars: Continuous improvement of large-scale spoken dialog systems
Statistical Spoken LanguageUnderstandinggrammars (SSLUs) are often used only at the top recognition contexts of modern large-scale spoken dialog systems. We propose to use SSLUs at every recognition context in a dialog system, effectively replacing conventional, manually written grammars. Furthermore, we present a methodology of continuous improvement in which data are collected at every recognition context over an entire dialog system. These data are then used to automatically generate updated context-specific SSLUs at regular intervals and, in so doing, continually improve system performance over time. We have found that SSLUs significantly and consistently outperform even the most carefully designed rule-based grammars in a wide range of contexts in a corpus of over two million utterances collected for a complex call-routing and troubleshooting dialog system.
David Suendermann, Keelan Evanini, Jackson Liscomb
Added 17 Aug 2010
Updated 17 Aug 2010
Type Conference
Year 2009
Where ICASSP
Authors David Suendermann, Keelan Evanini, Jackson Liscombe, Phillip Hunter, Krishna Dayanidhi, Roberto Pieraccini
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