Combining prior knowledge and boosting for call classification in spoken language dialogue
Marie Rochery, Robert E. Schapire, Mohammad Asifur Rahim, N. Gupta, Giuseppe Riccardi, Srinivas Bangalore, Hiyan Alshawi, S. Douglas · IEEE International Conference on Acoustics Speech and Signal Processing · 2002
Data collection and annotation are major bottlenecks in rapid development of accurate syntactic and semantic models for natural-language dialogue systems. In this paper we show how human knowledge can be used when designing a language understanding system in a manner that would alleviate the dependence on large sets of data. In particular, we extend BoosTexter, a member of the boosting family of algorithms, to combine and balance hand-crafted rules with the statistics of available data. Experiments on two voice-enabled applications for customer care and help desk are presented.