Voice Command Suggestions Based on User Identity
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Solution Overview
Problem
Users interacting with computing systems face complexity in learning and remembering numerous voice commands, especially in multi-turn conversations, due to inadequate learning support from traditional help and tutorial systems.
Innovation Solution
A system that identifies user identity and provides personalized, context-specific, and parameterized voice-command suggestions through a graphical user interface, dynamically changing suggestions based on user interaction and contextual states to facilitate efficient voice command usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional help and tutorial systems are used, then users can access information about voice commands, but the information is either superficial or overwhelming, failing to provide suitable learning support
Solution Approach 1:
The system provides personalized voice command suggestions tailored to each user's identity, preferences, and usage context. Instead of presenting a uniform list of all possible commands, the system dynamically adjusts the information presented based on the specific user's needs and situation, making the learning experience both sufficient and not overwhelming.
Solution Approach 2:
The system automatically identifies user identity and selects appropriate voice command suggestions without requiring users to manually search through help documentation. The system serves itself by autonomously determining what information is most relevant and presenting it in an appropriate format, reducing the burden on users to find and process information.
2Adaptability or versatility
If multiple voice commands are provided for different contexts and turns, then the system becomes more versatile, but the complexity of learning and remembering commands increases
Solution Approach 1:
The system segments the comprehensive set of voice commands into personalized subsets based on user identity, preferences, and current context. By dividing the full command set into relevant portions for each user, the system maintains versatility while presenting only the necessary commands to learn, reducing cognitive load.
Solution Approach 2:
The voice command suggestions dynamically adapt to changing user identities, preferences, and contextual states. The system continuously adjusts which commands are suggested based on real-time information about the user, making the learning process more manageable by focusing on currently relevant commands rather than requiring memorization of all possible commands.
3Productivity
If personalized voice command suggestions are provided based on user identity, then learning efficiency improves, but the system complexity increases
Solution Approach 1:
The system uses feedback about user identity, preferences, and usage patterns to continuously refine and personalize voice command suggestions. By incorporating feedback loops that adapt to user characteristics and usage behavior, the system achieves high learning efficiency while managing complexity through data-driven personalization rather than complex rule-based systems.
Data Source
AI summary
A computing system is configured to listen to user speech and translate the user speech into voice commands that control operation of the computing system. The identity of a user interacting with the computing system is determined, and a voice command is selected from a set of voice commands based on the user identity. A voice-command suggestion corresponding to the voice command is selected and presented via a display. If the user speaks the voice-command suggestion, the computing system executes the voice command corresponding to the voice-command suggestion.