Intelligent Call Priority System for Support Centers Based on Emotion Recognition in Speech

In today's business world, many transactions are conducted over the phone or online, and call centers play a crucial role in managing communications and resolving customer issues. These centers act as an intermediary between companies and customers, aiming to address problems, correct mistakes, and increase customer satisfaction. One of the key aspects of research in call centers is the automation of their operations. Call center agents interact with numerous users throughout the day, who experience various emotional states such as stress, anger, fear, anxiety, and happiness. At different times, a large number of calls are connected to call centers, all of which must be answered and processed. When all agents are busy handling calls, incoming calls are placed on hold without considering their urgency. The goal of this research is to improve First Call Resolution (FCR) and distribute calls based on their urgency and wait time. This proposed method can be applied to elderly care service centers, emergency medical centers, travel safety centers, and complaints departments for ride-hailing services. The suggested approach is based on emotion detection in users' speech, where calls with emotions such as fear, sadness, and anger are given higher priority, while calls with neutral or happy emotions are assigned lower priority. This experiment was conducted in a simulated call center, and the results demonstrate a significant improvement in reducing Average Wait Time (AWT) for high-priority calls, particularly those expressing anger and fear

کلیدواژه ها:

Emotion Recognition ، Affective Computing ، Human-Computer Interaction ، Customer Service