人工智能音频分析:深度学习检测呼叫记录异常，提高呼叫中心效率
Abstract:
Deep learning, a subfield of machine learning, is a state-of-the-art technology that has possibilities to solve many problems in computer vision and natural language processing. In recent years, we have witnessed a rise in the application of deep learning models in audio processing, most of which, however, are limited to the music industry.
Deep learning’s use cases in audio processing can be further expanded for businesses. This paper will focus specifically on how audio analysis leveraging deep learning can detect anomalous conversations in a call center record. Such a use case promises to help companies saves massive time, effort and cost in managing the quality of their helpdesks operations. According to our research, 95% human efforts can be saved by incorporating AI-based call analysis with traditional manual operation. This statistic can bear remarkable financial meaning to companies whose helpdesk is a crucial part of their business.
Created by: AI Research & Development Team, FPT Software
Content:
1. Introduction
2. The Connection between Customer Retention & Call Center
The question we want to help business answer is: How to detect and address phone calls where customers show signs of negative emotions without being dependent on the spoken languages?
3. AI to Optimize Audio Analysis in Call Centers
• Solution architecture
• The process
• The methodology
4. The potential impacts
5. Conclusion
Fill the form to download the full paper, Deep Learning to Detect Anomalies in Call Records & Enhance the Efficiency of Call Centers (PDF–2 MB).