Voice Assistant Disambiguation via Context-Aware Response Alteration
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Solution Overview
Problem
In multi-user scenarios with AI voice assistance systems, concurrent voice command responses can cause user confusion due to ambiguity, and adding extensive disambiguating information lengthens replies, irritating users.
Innovation Solution
The system predicts ambiguity by analyzing user identities, activity contexts, and historical interactions, dynamically adjusting responses by adding user names, activity names, or modifying tone/texture/pitch to disambiguate responses and provide timely, user-specific feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If extensive disambiguating information is added to responses, then response clarity is improved, but response length increases causing user irritation
Solution Approach 1:
The system applies disambiguation selectively based on the specific context and user identity rather than adding uniform disambiguating information to all responses. It determines the minimal necessary disambiguation (e.g., adding only user name, activity name, or both) based on the predicted ambiguity level for each specific response scenario.
Solution Approach 2:
The system performs partial disambiguation by adding only the necessary identifying information (user name, activity name, or both) rather than extensive disambiguating details. This partial action approach provides sufficient clarity to reduce ambiguity while keeping responses concise and avoiding user irritation.
2Reliability
If user-specific information is added to responses, then user confusion is reduced, but response processing time increases
Solution Approach 1:
The system performs user identification and activity context determination in advance before generating the final response. By pre-processing the disambiguation information (identifying user identity and current activity context beforehand), the system reduces the processing time required during response generation while still providing accurate user-specific responses.
Solution Approach 2:
The system combines user identification and activity context determination into a unified disambiguation process. By merging these functions and predicting ambiguity based on both factors together, the system efficiently generates user-specific responses without requiring separate processing steps, thereby reducing overall processing time.
Data Source
AI summary
Disambiguating question answering responses by receiving voice command data associated with a first user, determining a first user identity according to the first user voice command data, determining a first user activity context according to the first user voice command data, determining a first response for the first user, receiving voice command data associated with a second user, determining a second user identity according to the second user voice command data, determining a second user activity context according to the second user voice command data, determining a second response for the second user, determining a predicted ambiguity between the first response and the second response, altering the first response according to the predicted ambiguity, and providing the first response and the second response.