Voice Service Quality Inspection Based on LSTM Network

Abstract

Abstract: To solve the problem of low quality and low information processing capability of 95598 customer service center voice service quality inspection, a recommendation technology based on LSTM network was proposed. Combining the indicators of traditional sampling methods with indicators related to deep learning methods, the LSTM network was used to explore the inner relationship among various indicators in space and time. Instead of random sampling method, a representative recommendation quality inspection was used and combined with the characteristics of low problem probability in voice service to improve model performance. The experimental results illustrate that the improved model can significantly improve the quality inspection efficiency and directivity.

Key words: voice service, quality inspection, deep learning, LSTM network

CLC Number:

TM-9
F274

WU Peng, GUO Xiao-yun, CHEN Peng, WANG Zong-wei, CAO Lu, JIN Peng. Voice Service Quality Inspection Based on LSTM Network[J]. Computer and Modernization, 2020, 0(07): 76-79.

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