Telephone quality inspection method and device based on artificial intelligence, equipment and storage medium

Abstract

The invention relates to the field of artificial intelligence, and provides a telephone quality inspection method and device based on artificial intelligence, equipment and a storage medium. The method comprises the following steps: acquiring a plurality of call records to be processed; marking a corresponding score for each call record to be processed; converting the plurality of call records tobe processed into a plurality of pieces of text information to be processed through a preset sequence neural network model; performing word segmentation to be processed on the text information througha language technology platform LTP technology to obtain a plurality of core keywords and frequency corresponding to the core keywords; taking the frequency of the core keywords as an input xi, takingthe marked call score as an ideal output yi, and inputting the ideal output yi into a neural network to obtain a target neural network; deploying the target neural network to a client; and receivingcall information input by the user, calculating the score of the call information through the ideal weight, and returning the score of the call information to the user. Thus, telephone quality inspection is more efficient.

Description

technical field [0001] The invention relates to the monitoring field, in particular to an artificial intelligence-based telephone quality inspection method, device, equipment and storage medium. Background technique [0002] In the operation of call centers, various indicators such as connection rate, call duration, complaint rate, and customer satisfaction are very important. These data directly correspond to the gap in business quality between different personnel. Nowadays, many monitoring and quality inspections are conducted through manual sampling. Quality inspectors are responsible for quality monitoring, process management, index management, on-site follow-up, report writing, Cultural construction is also responsible for the quality inspection of multiple links such as knowledge base management, business training, and employee feedback and guidance. The standards can be the same, the index settings can be the same, and the results may be different. The key is that th...

AI Technical Summary

Problems solved by technology

These data directly correspond to the gap in business quality between different personnel. Nowadays, many monitoring and quality inspections are conducted through manual sampling. Quality inspectors are responsible for quality monitoring, process management, index management, on-site follow-up, report writing, Cultural construction is also responsible for the quality inspection of multiple links such as knowledge base management, business training, and employee feedback and guidance.

The standards can be the same, the index settings can be the same, and the results may be different. The key is that the quality inspectors use the standards for different purposes, methods, and ideas, and the accuracy of the quality inspection results is low.

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