Using Semantic Similarity In Automated Call Quality Evaluator For Call Centers

Conversation between the agent and client are being evaluated manually by a quality assurance officer QA. This job is only one of the responsibilities being done by a QA and particularly eat ups a lot of time for them which lead to late evaluation results that may cause untimely response of the company to concerns raised by their clients. This research developed an application software that automates and evaluates the quality assurance in business process outsourcing companies or customer service management implementing sentence similarity. The developed system includes two modules speaker diarization which includes transcription and question and answer extraction and similarity checker which checks the similarity between the extracted answer and the answer of the call center agent to a question. The system was evaluated for Correctness of the extracted answers and accurateness of the evaluation for a particular call. Audio conversations were tested for the accuracy of the transcription module which has an accuracy of 27.96. The Precision Recall and F-measure of the extracted answer was tested as 78.03 96.26 and 86.19 respectively. The Accuracy of the system in evaluating a call is 70.