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Recurrent Neural Learning for Helpdesk Call Routing

  • Sheila Garfield
  • Stefan Wermter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2415)

Abstract

In the past, recurrent networks have been used mainly in neurocognitive or psycholinguistically oriented approaches of language processing. Here we examine recurrent neural networks for their potential in a difficult spoken language classification task. This paper describes an approach to learning classification of recorded operator assistance telephone utterances. We explore simple recurrent networks using a large, unique telecommunication corpus of spontaneous spoken language. Performance of the network indicates that a semantic SRN network is quite useful for learning classification of spontaneous spoken language in a robust manner, which may lead to their use in helpdesk call routing.

Keywords

Recurrent Neural Network Primary Move Recurrent Network Dialogue System Precision Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Sheila Garfield
    • 1
  • Stefan Wermter
    • 1
  1. 1.University of SunderlandSunderlandUK

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