Oznur Alkan, Massimilliano Mattetti, et al.
INFORMS 2020
This paper studies the effect of word-error-rate (WER) on an automated quality monitoring application for call centers. The system consists of a speech recognition module and a call ranking module. The call ranking module combines direct question answering with a maximum-entropy classifier to automatically monitor the calls that enter a call center, and label them as "good" or "bad". We find that, in the monitoring regime where only a small fraction of the calls are monitored, we achieve 80% precision and 50% recall in classifying whether a call belongs to the bottom 20%. Additionally, the correlation between human and computer-generated scores turns out to be highly sensitive to word error rate. ©2006 IEEE.
Oznur Alkan, Massimilliano Mattetti, et al.
INFORMS 2020
Rajesh Balchandran, Leonid Rachevsky, et al.
INTERSPEECH 2009
Casey Dugan, Werner Geyer, et al.
CHI 2010
Elaine Hill
Human-Computer Interaction