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Information Retrieval for Call Center Quality Assurance

Abstract Details

2020, Master of Science, Ohio State University, Computer Science and Engineering.
For businesses that employ them, call centers are the main point of customer interactions. Therefore, well-run call centers and high customer satisfaction are intricately related. Currently, the Safe Auto call center relies on human review of calls, i.e. call center managers will randomly select calls, listen to them, and then provide a score based on agent performance. This process is both costly and limited in scope. We propose an automated call scoring system. First, our system performs Automatic Speech Recognition on the audio files, outputting text transcripts. To improve our transcription accuracy, we employ a custom Safe Auto Language Model. The transcripts are then converted into a matrix format using the Doc2Vec algorithm. In order to compute a label, our model then compares the calls we are attempting to classify with a historical record of calls that have been scored by call center managers. We are able to correctly label calls with an 80% accuracy. Our system improves upon the prior method by scoring all calls, instead of a subset, by cutting down on human labor costs, and by freeing up call center managers’ time.
Jeremy Morris (Advisor)
Rajiv Ramnath (Committee Member)
42 p.

Recommended Citations

Citations

  • McMurtry, W. F. (2020). Information Retrieval for Call Center Quality Assurance [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587036885211228

    APA Style (7th edition)

  • McMurtry, William. Information Retrieval for Call Center Quality Assurance. 2020. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1587036885211228.

    MLA Style (8th edition)

  • McMurtry, William. "Information Retrieval for Call Center Quality Assurance." Master's thesis, Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587036885211228

    Chicago Manual of Style (17th edition)