Home Appliance Feature Control for Ambiguous Voice Commands
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Solution Overview
Problem
Existing home appliance control methods struggle with accurately interpreting natural language commands due to variability and ambiguity in human speech, limiting flexibility and personalization, especially in aesthetic customizations like color schemes, and failing to adapt to individual user preferences or changing moods.
Innovation Solution
A method and device that dynamically interpret a wide range of natural language inputs, adapt to individual user speech patterns, and translate ambiguous commands into precise device operations, using a server with preprocessing, theme, and personalization modules to generate flexible color and function sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language commands are used for controlling home appliances, then ease of operation is improved, but measurement precision of user intent deteriorates
Solution Approach 1:
The system segments the natural language processing into multiple stages: initial command recognition, accuracy evaluation, and iterative refinement. By dividing the interpretation process into discrete steps with intermediate assessments, the system maintains ease of natural language input while improving precision through structured analysis at each segment.
Solution Approach 2:
The system implements feedback mechanisms where the accuracy of command interpretation is continuously evaluated and used to adjust subsequent processing. When initial interpretation accuracy is insufficient, the system feeds back to request clarification or alternative interpretations, thereby improving measurement precision while maintaining natural interaction.
2Reliability
If predefined command structures are used, then reliability of command interpretation is improved, but adaptability to user speech patterns deteriorates
Solution Approach 1:
The system dynamically adjusts its command structure based on the specific user and context. Rather than relying solely on rigid predefined structures, the system adapts its interpretation framework to match individual user speech patterns while maintaining the reliability of core command recognition through established protocols.
Solution Approach 2:
The system changes parameters such as acceptable variation thresholds, interpretation strictness, and pattern matching sensitivity based on the user and context. This allows the system to maintain reliability for critical commands while becoming more adaptable to varied speech patterns in appropriate situations.
3Ease of manufacture
If limited predefined color palettes are used, then ease of manufacture is improved, but adaptability to user preferences deteriorates
Solution Approach 1:
The system changes the color parameter space by generating custom color values based on thematic descriptions rather than being constrained to predefined palettes. This allows full adaptability to user preferences while maintaining ease of manufacture through systematic color generation methods and controlled application processes.
Data Source
AI summary
A method of changing a feature of a home appliance can include receiving a feature command, determining whether the feature command matches a first feature set stored in a database including predetermined feature sets, and in response to failing to match the feature command to the first feature set, providing the feature command to an artificial intelligence (AI) theme module to generate a second feature set. Also, the method can further include in response to the AI theme module failing to generate the second feature set, generating a third feature set based on personalized user information, and changing the feature of the home appliance to correspond to one of the first feature set, the second feature set, or the third feature set.