Parallel Voice and Emotion Recognition for Contact Center Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Contact centers face high operator turnover rates and challenges in managing workload and information security due to stressful customer interactions, with existing technologies struggling to implement real-time filtering in communications without delaying processes.
Innovation Solution
A contact center support system that includes a control unit executing voice recognition, emotion recognition, and filtering processes in parallel, enabling real-time communication filtering and minimizing delays in phone calls between operators and customers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If filtering processes are applied to communications between operators and customers, then information security and workload reduction are improved, but communication delays increase
Solution Approach 1:
The system performs voice recognition and emotion recognition in advance of the filtering process. By pre-processing the voice data to extract content and emotional information, the system can then quickly filter the communication based on pre-analyzed characteristics rather than processing everything sequentially, thus reducing overall delay while maintaining security.
Solution Approach 2:
The filtering process is divided into multiple independent recognition modules (voice recognition, emotion recognition, filtering) that operate in parallel rather than sequentially. Each module processes specific aspects of the communication simultaneously, allowing the system to maintain information security through comprehensive filtering while minimizing total processing time.
2Measurement precision
If multiple recognition and filtering processes are executed sequentially, then processing accuracy is maintained, but communication speed decreases
Solution Approach 1:
The system segments the communication processing into distinct parallel processes: voice recognition, emotion recognition, and filtering. Each process operates independently on different aspects of the voice data, allowing accurate processing of all components simultaneously rather than sequentially, thus maintaining precision while improving speed.
Solution Approach 2:
The system transitions from sequential time-based processing to parallel dimension-based processing. By executing voice recognition, emotion recognition, and filtering in parallel dimensions, the system achieves both high accuracy and fast communication speed without the trade-off present in sequential processing.
Data Source
AI summary
A contact center support system is a system that supports a contact center and includes a control unit that executes a plurality of processes for communication performed between an operator of the contact center and a customer, in which the communication includes a call between the operator and the customer, the plurality of processes include at least a voice recognition process of recognizing at least a content of the customer's utterance from a voice of the call, an emotion recognition process of recognizing at least the customer's emotion from the voice of the call, and a filtering process of filtering the content of the utterance of the customer and/or the operator in the call, and the control unit simultaneously executes the processes included in the plurality of processes in parallel.