Boosting with prior knowledge for call classification

Robert E. Schapire, Marie Rochery, Mazin Rahim, Narendra Gupta

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)174-181
Number of pages8
JournalIEEE Transactions on Speech and Audio Processing
Issue number2
StatePublished - Mar 2005
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Acoustics and Ultrasonics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


  • Boosting
  • Call classification
  • Dialogue systems
  • Learning systems
  • Prior knowledge
  • Spoken language understanding


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