DocumentCode
1239814
Title
Boosting with prior knowledge for call classification
Author
Schapire, Robert E. ; Rochery, Marie ; Rahim, Mazin ; Gupta, Narendra
Author_Institution
Dept. of Comput. Sci., Princeton Univ., NJ, USA
Volume
13
Issue
2
fYear
2005
fDate
3/1/2005 12:00:00 AM
Firstpage
174
Lastpage
181
Abstract
The use of boosting for call classification in spoken language understanding is described in this paper. An extension to the AdaBoost algorithm is presented that permits the incorporation of prior knowledge of the application as a means of compensating for the large dependence on training data. We give a convergence result for the algorithm, and we describe experiments on four datasets showing that prior knowledge can substantially improve classification performance.
Keywords
learning (artificial intelligence); natural languages; speech processing; AdaBoost algorithm; call classification; spoken dialogue application; spoken language understanding; Boosting; Convergence; Humans; Learning systems; Loss measurement; Natural languages; Robustness; Speech recognition; Text categorization; Training data; Boosting; call classification; dialogue systems; learning systems; prior knowledge; spoken language understanding;
fLanguage
English
Journal_Title
Speech and Audio Processing, IEEE Transactions on
Publisher
ieee
ISSN
1063-6676
Type
jour
DOI
10.1109/TSA.2004.840937
Filename
1395962
Link To Document