Turkish LVCSR system for call center conversations

This paper presents a Turkish large vocabulary continuous speech recognition (LVCSR) system that automatically transcribes the agent-customer conversations of call centers. The aim is to increase the recognition performance of the system in order to retrieve correct statistics from the call center conversations. For this reason, a confidence metric which is calculated from the outputs of two decoders that uses different language model units is also proposed. Tested on real call center data, the system results in 22.5% word error rate on agent speech, and 40.7% word error rate on customer speech. When the proposed confidence metric is used, customer and agent word recognition rates absolutely increases up to 19.4%, and 12.3% respectively, while nearly 70% of the call data is still covered.