Voice Assistant Context Queue for Command Accuracy
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Solution Overview
Problem
Users face challenges with seamless and timely interactions with cloud-based resources through local computing devices, particularly when relying on voice assistant services, as they often require additional context to accurately interpret voice commands, leading to errors or requests for clarification.
Innovation Solution
A voice assistant system that utilizes a context queue to share information between content providers and voice assistant services, leveraging user profiles and interaction data to determine the context of voice requests, allowing for augmented responses and transactions without relying on graphical interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If voice assistant services are used to interact with cloud-based resources, then hands-free operation and accessibility are improved, but accuracy and reliability deteriorate due to lack of context leading to errors and clarification requests
Solution Approach 1:
The system performs preliminary actions by proactively determining context from multiple sources (application state, user profile, recent interactions) before the voice command is fully processed. This allows the voice assistant to pre-load relevant information that will be needed to accurately interpret the command, reducing errors and clarification requests.
Solution Approach 2:
The patent introduces context determination as an intermediary layer between the voice input and the command execution. This intermediary process gathers and synthesizes information from various sources (application context, user profile, environmental data) to bridge the gap between the voice command and the intended action, improving accuracy without requiring graphical interfaces.
2Reliability
If additional context is gathered from multiple sources to improve voice command accuracy, then reliability is improved, but system complexity and processing time increase
Solution Approach 1:
The context determination system is segmented into multiple independent components that gather information from different sources (application state, user profile, recent interactions, environmental context). Each component operates independently and contributes its specific data to the overall context, making the complex system manageable and maintainable while improving accuracy.
Solution Approach 2:
The context determination mechanism is designed as a universal system that can draw from multiple data sources and adapt to different scenarios. The same context determination framework works across various applications and situations, reducing the need for application-specific customizations and managing system complexity through a unified approach.
3Measurement precision
If context information is stored and processed from multiple applications, then voice assistant accuracy is improved, but information management complexity and data privacy concerns increase
Solution Approach 1:
An intermediary context determination layer is introduced that acts as a secure gateway between multiple applications and the voice assistant. This intermediary selectively gathers and processes context information according to defined rules and privacy policies, managing the complexity of information flow and data protection while maintaining high context understanding accuracy.
Solution Approach 2:
The system applies local quality by tailoring the amount and type of context information gathered from each specific application based on its relevance and sensitivity. Not all applications contribute the same level of detail, and privacy-sensitive applications have restricted access rules, allowing accurate context understanding while managing information complexity and privacy concerns.
Data Source
AI summary
A voice assistant service (VAS) may receive an audio request from a user via a first device via a voice assistant application executed by the first device. The VAS may determine that the audio request references a context queue that stores log information about user-interaction with a second device. The VAS may analyze the log information from the context queue to determine a context of the audio request as a supplemented request. The VAS may determine a response based on the supplemented text request. The response may be an audio response and/or an action, such as a computing action. The VAS may provide an audible response to the voice assistance application for output to the user.