Virtual Caller System for Agent Assessment
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Solution Overview
Problem
Existing customer service systems face challenges in providing equally timely, efficient, and enjoyable experiences across various communication channels, including audio calls and electronic messages, especially when handling complex tasks or critical situations involving multiple relationships and medication-related inquiries.
Innovation Solution
The implementation of a virtual caller system that generates utterances to assess agent effectiveness, incorporating configuration settings such as task type, criticality, and relationship, to ensure consistent and high-quality customer service interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If customer service is provided through multiple communication channels (audio calls, electronic messages), then user accessibility to agents is improved, but consistency and quality of service interactions deteriorate
Solution Approach 1:
The virtual caller system serves multiple communication channels (audio calls, electronic messages) through a single unified platform, enabling consistent service delivery across diverse channels while maintaining the ability to adapt to channel-specific requirements
2Measurement precision
If virtual caller system replicates real-user scenarios with multiple relationships and medication-related inquiries, then assessment accuracy is improved, but system complexity increases
Solution Approach 1:
The virtual caller system segments complex assessment scenarios into distinct components including task type, criticality level, and relationship parameters. This modular segmentation enables accurate replication of real-user scenarios while managing system complexity through organized, manageable modules
3Reliability
If configuration settings include task type, criticality, and relationship parameters, then service quality is improved, but device complexity increases
Solution Approach 1:
The system applies different configuration parameters (task type, criticality, relationship) to specific local aspects of customer service interactions rather than uniformly across all interactions. This enables high service quality for complex scenarios while maintaining simplicity for routine interactions
Data Source
AI summary
Method starts with a processor receiving configuration settings including an identified task, a relationship data, and a criticality value. Processor initializes a communication session with an agent client device. The communication session is between a virtual caller associated with the system and the agent client device. Processor then processes an audio signal of the communication session to generate an agent utterance and generates a transcribed agent utterance based on the agent utterance using a speech-to-text processor. Processor generates a virtual caller utterance using a task-specific virtual caller neural network associated with the identified task. The virtual caller utterance can be generated based on the transcribed agent utterance. Processor then causes the virtual caller utterance to be played back in the communication session to the agent client device. Other embodiments are disclosed herein.