Contextual Dialogue Routing for Accurate Skill Selection
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Solution Overview
Problem
Conventional dialogue systems rely on user statement input and intent to generate responses, often routing input to incorrect skills, leading to inefficiencies and inaccuracies in response generation.
Innovation Solution
A system that utilizes contextual information, such as user identity, location, and user profile data, to determine the appropriate skill for routing user input within the dialogue system, employing machine learning models to improve routing accuracy and response quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the dialogue system relies on user statement input and intent to generate responses, then the system can process user queries, but the input may be routed to incorrect skills leading to reduced accuracy
Solution Approach 1:
The system performs preliminary extraction of contextual information from user statements before routing to skills. The contextual information component analyzes the statement to extract relevant context (location, user profile, device information) in advance, which then guides accurate routing to the appropriate skill, preventing misrouting and improving reliability.
Solution Approach 2:
The patent introduces a contextual information component as an intermediary between the user statement input and the skill routing mechanism. This intermediary extracts and processes contextual information, which then informs the routing decision, ensuring that the statement is directed to the correct skill while preserving relevant contextual details that would otherwise be lost.
2Productivity
If the dialogue system uses only user statement input for response generation, then the system structure remains simple, but routing performance deteriorates
Solution Approach 1:
The system segments the response generation process into distinct components: a contextual information component that extracts context from user statements, and a dialogue component that uses this context to generate responses. This segmentation allows each component to specialize in its function, improving overall efficiency while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The contextual information component serves multiple functions within the system: it extracts contextual data for routing decisions, provides context for response generation, and can be applied across different dialogue scenarios. This multi-functionality improves productivity by reusing the same component for various tasks without proportionally increasing system complexity.
Data Source
AI summary
Techniques that facilitate a dialogue system based on contextual information are provided. In one example, a system includes a contextual information component and a dialogue routing component. The contextual information component determines contextual information associated with a user identity based on a statement related to communication information received by a computing device associated with the user identity. The dialogue routing component generates a path traversal for a dialogue system based on the contextual information to facilitate generation of a response to the statement by the dialogue system.