Recurrent Neural Learning for Helpdesk Call Routing

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.

@InProceedings{GW02,
 	 author =  {Garfield, Sheila and Wermter, Stefan},
 	 title = {Recurrent Neural Learning for Helpdesk Call Routing},
 	 booktitle = {Proceedings of the International Conference on Artificial Neural Networks},
 	 journal = {None},
 	 editors = {Dorronsoro, Jose R.},
 	 number = {}
 	 volume = {}
 	 pages = {296--301},
 	 year = {2002},
 	 month = {Aug},
 	 publisher = {Springer},
 	 doi = {10.1007/3-540-46084-5_49},
 }