Automatic topic detection of recorded voice messages

We present an approach to automatic classification of spontaneously spoken voice messages. During overload periods at call-centers customers are offered a call-back at a later time. A speech dialog asks them to describe their concern on a voice box. The identified topics correspond to the supported service categories, which in turn determine the agent group the customer message is routed to. Our multistage classification process includes speech-to-text, stemming, keyword spotting, and categorization. Classifier training and evaluation have been performed with real-life data. Results show promising performance. The pilot will be launched in a field test.