IVR Conversation Controller Optimizing Session Duration
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Solution Overview
Problem
Interactive voice response systems face challenges in optimizing user interaction session duration due to inefficiencies in predicting silence intervals, turn transitions, Text to Speech processes, natural language understanding, and conversation path design, leading to user frustration and increased operational costs.
Innovation Solution
A system and method that utilize a conversation controller to automatically optimize user interaction sessions by monitoring sessions, analyzing user data, and dynamically adjusting ASR, NLU, and TTS models to improve intent fulfillment, reduce uncertainty, and enhance user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adaptation and execution of ASR and NLU pipeline is performed for each classified case, then customization and precision are improved, but device complexity and maintenance difficulty increase significantly
Solution Approach 1:
The system performs self-learning and self-optimization through automated machine learning pipelines that continuously adapt ASR and NLU models based on conversation data, eliminating the need for manual adaptation for each classified case while maintaining high precision
Solution Approach 2:
The system dynamically adjusts model parameters and conversation path parameters based on learned patterns from data, allowing automatic optimization of classification precision without manual intervention for each case
2Measurement precision
If multiple turn transitions are used in conversation, then user intent understanding is improved, but interaction session duration increases
Solution Approach 1:
The system performs preliminary analysis of user intent using NLU models before initiating multiple turn transitions, allowing it to determine when additional turns are necessary and when direct fulfillment is possible, thereby reducing unnecessary interaction duration while maintaining accuracy
Solution Approach 2:
The system uses feedback from sentiment analysis and conversation monitoring to adjust the conversation path in real-time, enabling faster convergence to intent fulfillment by recognizing when additional turns provide diminishing returns
3Loss of time
If automated conversation optimization is implemented, then user journey duration is reduced, but system complexity and monitoring requirements increase
Solution Approach 1:
The conversation controller performs multiple functions including sentiment analysis, error detection, model selection, and conversation path optimization within a single unified system, reducing overall complexity compared to separate specialized systems for each function
Solution Approach 2:
The system automatically monitors and optimizes conversation sessions without requiring external intervention, using self-learning mechanisms to reduce complexity over time as the system becomes more autonomous in its optimization decisions
Data Source
AI summary
The present invention describes a system and a method for monitoring and optimizing a user interaction session within an interactive voice response system during a human-computer interaction, the user interaction management system (100) for monitoring and optimizing the user interaction session comprising a conversation controller module (109), the conversation controller module (109) receives the audio features and processes outputs of ASR and NLU during the user interaction session to optimize the user interaction session duration. According to an embodiment of the present invention, the conversation controller may suggest the TTS to increase the rate of speech. According to yet another embodiment, the conversation controller may suggest the TTS to decrease the rate of speech.