Portable NLP Interface for Appliances
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Solution Overview
Problem
Conventional voice-based digital assistants for controlling multiple appliances face issues such as high power consumption, internet connectivity requirements, privacy concerns, and inefficiencies due to complex natural language processing models that are difficult to train and upgrade, leading to low accuracy and limited mobility.
Innovation Solution
A portable voice control apparatus with a built-in voice communication interface, data communication interface, and natural-language processing module that uses multiple NLP models for different appliances, allowing for offline operation, customizable, and adaptable to various appliance types, reducing the need for constant listening and internet connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional voice-based digital assistants use complex NLP models to interpret a wide range of voice commands, then the versatility of command handling is improved, but the manufacturing precision and training difficulty worsen
Solution Approach 1:
The patent segments the monolithic complex NLP model into multiple specialized NLP models, each trained for specific appliance types or functions. This segmentation allows each model to focus on a narrower domain, improving recognition accuracy for specific tasks while maintaining overall system versatility through model selection based on detected appliance context.
2Speed
If conventional voice-based digital assistants require constant listening to speech commands, then the responsiveness to user input is improved, but the power consumption increases
Solution Approach 1:
The system implements periodic action by having the voice control apparatus activate the voice communication interface only upon detecting a predefined triggering event (such as a wake word or user initiation), rather than constantly listening. This approach maintains responsiveness when needed while significantly reducing power consumption during idle periods.
3Power
If conventional voice-based digital assistants connect to internet servers for NLP processing, then the processing power and model complexity are improved, but the privacy concerns and device complexity increase
Solution Approach 1:
The patent extracts the essential NLP processing capability from external internet servers and embeds it directly into the voice control apparatus through multiple specialized NLP models. This extraction eliminates the need for constant internet connectivity and server dependence, reducing privacy concerns and system complexity while maintaining adequate processing power for appliance control tasks.
4Adaptability or versatility
If conventional voice-based digital assistants use comprehensive NLP models, then the range of interpretable commands is improved, but the training time and upgrade difficulty worsen
Solution Approach 1:
The patent segments the comprehensive NLP model into multiple specialized models that can be independently trained and updated. This segmentation reduces the training time for each individual model since they focus on specific domains, while the collection of models collectively maintains comprehensive command interpretation capability across different appliance types.
Data Source
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AI summary
A method and system of customizing a portable voice-based control user interface for multiple types of appliances. The method performed at a user device includes establishing a data communication connection with a voice control apparatus (702); detecting a first user request to update a NLP module of the voice control apparatus (704); establishing a connection to a NLP model server (708); displaying a listing of appliance types and a respective listing of appliance functions for each appliance type, in a graphical user interface of the user device (710); receiving user selection of a first set of appliance functions for a first appliance type and a second set of appliance functions for a second appliance type (712); downloading, from the NLP model server, a first NLP model for the first set of appliance functions for the first appliance type, and a second NLP model for the second set of appliance functions for the second appliance type (716); and integrating the first NLP model and second NLP model into the NLP module of the voice control apparatus (718).