Voice-Activated Appliance User Identification and Preference Management
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Solution Overview
Problem
Feature-rich appliances are challenging for novice users due to the need for extensive configuration or selection of preferences, and existing voice command systems struggle to distinguish between multiple users, providing a non-personalized experience.
Innovation Solution
An appliance with a speech-to-text module and user identification system that converts human speech into textual information, identifies enrolled users, and performs operations based on their stored preferences, allowing for personalized responses to voice commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the appliance includes multiple configurable features and options, then the appliance functionality and versatility are improved, but the ease of operation deteriorates due to extensive configuration requirements
Solution Approach 1:
The system performs preliminary actions by storing multiple user profiles with pre-configured preferences for various appliance features. When a user interacts with the appliance, the system automatically retrieves and applies the appropriate pre-configured settings based on user identification, eliminating the need for users to repeatedly configure features.
Solution Approach 2:
The appliance performs self-service by automatically identifying users through voice recognition and autonomously applying the correct preference profiles without requiring manual configuration input from users. The system serves itself by managing multiple user profiles and automatically selecting the appropriate one based on who is speaking.
2Loss of information
If the appliance requires users to select operational preferences through touch screen or buttons, then the appliance can capture user preferences, but the time required for operation increases
Solution Approach 1:
The system replaces the mechanical interaction of touch screens and physical buttons with voice-based acoustic recognition. Users simply speak their commands naturally, and the system captures preferences through speech-to-text conversion and voice pattern recognition, eliminating the need for manual navigation through menus and selection interfaces.
Solution Approach 2:
The system performs preliminary action by pre-configuring multiple user profiles with default preferences. When a user is identified through voice recognition, the system automatically applies the appropriate pre-configured profile, eliminating the need for users to spend time selecting preferences during each interaction.
3Ease of operation
If the appliance uses voice commands for operation, then the ease of operation is improved, but the ability to distinguish between multiple users and provide personalized experience deteriorates
Solution Approach 1:
The system applies local quality by creating distinct user profiles with individualized preferences for different users. Each user profile contains customized settings tailored to that specific user's preferences. The voice recognition system identifies which user is speaking and applies only that user's specific profile, ensuring personalized experience for each individual while maintaining ease of voice-based operation.
4Measurement precision
If the appliance requires users to sign in with identification, then user identification accuracy is improved, but the ease of operation deteriorates due to additional authentication steps
Solution Approach 1:
The system replaces the mechanical authentication process of entering usernames and passwords with acoustic voice recognition. The system captures voice patterns and speech characteristics to automatically identify users, maintaining high identification accuracy while eliminating the need for users to manually input authentication credentials.
Solution Approach 2:
The appliance performs self-service by automatically identifying users through their voice patterns without requiring active participation in authentication. Users simply speak their commands, and the system autonomously identifies who is speaking and retrieves the appropriate profile, making the authentication process transparent and effortless.
Data Source
AI summary
Generally the present disclosure is directed to appliances that provide a user-specific response to a received voice command. In particular, the appliance can store a plurality of voice samples respectively associated with a plurality of users. The appliance can also store one or more preferences for each of the plurality of users. For example, the preferences can be input by the user and/or learned or inferred over time. When the appliance receives a human speech signal or voice command, it can match the received speech signal against one or more of the plurality of voice samples to identify the user. The preferences stored and associated with the identified user can then be obtained and the appliance can perform any requested operations in accordance with the obtained preferences. In such fashion, the appliance can provide a user-specific response to a received voice command.