Voice emotion recognition and application system for conversations of call center

Abstract

The invention discloses a voice emotion recognition and application system for conversations of a call center. The system comprises a voice processing module, a voice keyword detection module, an emotion model set module, an emotion classification module and a business application module, wherein the voice processing module is used for extracting voice information and preprocessing the voice information; the voice keyword detection module is used for recognizing voice data of a voice feature analysis submodule as emotion keywords and topic keywords, and obtaining emotion data information and reflected problem data information; the emotion model set module is used for dynamically capturing and tracking emotion states of callers; the emotion classification module is used for judging emotioncategories of voices in to-be-detected conversations; and the service application module is used for providing response assistance for the customer service personnel and providing management assistance for the management personnel. The voice emotion recognition and application system for conversations of call centers is capable of enabling the customer service personnel to accurately understand the emotions of customers, providing effective response plans, and accurately evaluating the customer service personnel.

Description

technical field [0001] The invention relates to the technical field of audio data processing, in particular to a speech emotion recognition and application system for calls in a call center. Background technique [0002] In modern enterprises, the call center bears the important responsibility of maintaining enterprise customer relationship and business marketing, so it is of great significance to monitor the voice service quality of the call center. Emotional analysis of call voice can identify the emotional state of customer service and customers in customer service calls, so as to effectively track and monitor the quality of service. In the existing call center call emotion recognition schemes, most of them use speech recognition technology to convert speech into text content, and then perform emotion analysis based on the text. On the one hand, this method relies on the accuracy and robustness of the speech recognition model, and there is a certain conversion error rate...

AI Technical Summary

Problems solved by technology

[0003] At present, in call center call emotion recognition, there are also schemes based on voice classification. These schemes basically only use a single model when using the emotion classification model. Due to the diversity of callers, scenes and call content, the emotion recognition effect of a single model is often It is difficult to achieve good stability, and only emotion recognition can be performed, and key information reflected by customers in problematic calls cannot be found in time

The service quality of the customer service personnel in the call center is often manually scored by the customer. The above scoring method is often inaccurate and completely depends on the customer's subjectivity or the customer service personnel's requirements for customer scoring, so that the customer follows the customer service personnel. Scoring, sometimes customers do not score calls in order to save time, which is not conducive to the development of enterprises and cannot really understand customers

Since customer service personnel are often not professional technicians, they sometimes cannot deal with the product defects raised by customers well; and in the face of customers with diverse emotions, it is difficult for customer service personnel to adopt effective handling methods, especially for Novice customer service staff

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