Amol Thakkar, Andrea Antonia Byekwaso, et al.
ACS Fall 2022
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.
Amol Thakkar, Andrea Antonia Byekwaso, et al.
ACS Fall 2022
Dimitrios Christofidellis, Giorgio Giannone, et al.
MRS Spring Meeting 2023
Carla F. Griggio, Mayra D. Barrera Machuca, et al.
CSCW 2024
Praveen Chandar, Yasaman Khazaeni, et al.
INTERACT 2017