Extracting call-reason segments from contact center dialogs by using automatically acquired boundary expressions

To improve the performance of call-reason analysis at contact centers, we introduce a novel method to extract call-reason segments from dialogs. It is based on the following two characteristics of contact center conversations; 1) customers state their requests at the beginning of the calls, 2) agents tend to use typical phrases at the end of the call-reason segments. Our proposal acquires these typical phrases from stored speech data automatically and extracts the call-reason segment precisely by detecting the typical phrases. Experiments show that it significantly improves the performance of call-reason information retrieval since it allows the search scope to be limited to the call-reason segments of calls.