9th Annual Conference of the International Speech Communication Association

Brisbane, Australia
September 22-26, 2008

Automatic Customer Feedback Processing: Alarm Detection in Open Question Spoken Messages

Nathalie Camelin (1), Geraldine Damnati (2), Frédéric Bechet (1), Renato De Mori (1)

(1) LIA, France; (2) Orange Labs, France

This paper describes an alarm detection system dedicated to process automatically customer feedbacks in call-centers. Previous studies presented a strategy that consists in the robust detection of subjective opinions about a particular topic in a spoken message. In the present study, we focus on the alarm detection problem in a customer spoken feedback application. We want to characterize each customer's survey with a degree of emergency. All the messages considered as urgent need a quick answer from the call-center service in order to satisfy the customer. The strategy proposed is based on a classification scheme that takes into account all the features that can characterize a survey: answers to the closed questions, topics and opinions detected in the open question spoken message, confidence scores from the Automatic Speech Recognition (ASR) and Spoken Language Understanding (SLU) modules. A field trial realized among real customers has shown that despite the ASR robustness issues, our system efficiently ranks the most urgent messages and brings a finer analysis on the surveys than the one provided by processing the closed questions alone.

Full Paper

Bibliographic reference.  Camelin, Nathalie / Damnati, Geraldine / Bechet, Frédéric / Mori, Renato De (2008): "Automatic customer feedback processing: alarm detection in open question spoken messages", In INTERSPEECH-2008, 475-478.