A Misclassification Reduction Approach for Automatic Call Routing

Abstract

Abstract. Automatic call routing is one of the most important issues in the call center domain. It can be modeled -once performed the speech recognition of utterances-as a text classification task. Nevertheless, in this case, texts are extremely small (just a few words) and there are a great number of narrow call-type classes. In this paper, we propose a text classification method specially suited to work on this scenario. This method considers a new weighting scheme of terms and uses a multiple stage classification approach with the aim of balance the rate of rejected calls (directed to a human operator) and the classification accuracy. The proposed method was evaluated on a Spanish corpus consisting of 24,638 call utterances achieving outstanding results: 95.5% of classification accuracy with a rejection rate of just 8.2%.