Paper Info
Title
Automatic Customer Feedback Processing: Alarm Detection In Open Question Spoken Messages
Abstract
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.
Year
Venue
Keywords
2008
INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5
Automatic Speech Recognition, Speech Understanding, Confidence Measures, Speech Mining
Field
DocType
Citations 
Confidence measures,Speech analytics,Customer feedback,Computer science,ALARM,Classification scheme,Speech recognition,Robustness (computer science),Natural language processing,Artificial intelligence,Spoken language
Conference
2
PageRank 
References 
Authors
0.43
6
4
Name
Order
Citations
PageRank
Nathalie Camelin13914.29
Géraldine Damnati218526.15
Frédéric Béchet339747.77
Renato De Mori4960161.75