Multi-Device Voice Control Using Context-Aware Command Scripts

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Solution Overview

Problem

Existing systems for controlling multiple devices with speech commands require predefined phrases, leading to user frustration due to erroneous commands and recognition issues as the number of connected devices increases.

Innovation Solution

A method and system that generate a command script by processing a natural language input, modify it based on contextual data, and control devices using command signals, incorporating machine-learning models to handle ambiguities and variations in user phrasing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If predefined phrases are required for device control, then command recognition accuracy is improved, but user convenience deteriorates due to the need to remember specific device names and phrases

Engineering Contradiction:

Improvecommand recognition accuracyVSAvoiduser convenience

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system changes the parameter of language processing from rigid predefined phrases to flexible natural language understanding. The machine learning model processes varied user phrasings and contextual data to accurately identify device control intentions, achieving both high recognition accuracy and user convenience.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the mechanical matching system (predefined phrase verification) with an intelligent system (machine learning model). This substitution allows the system to understand natural language variations and contextual nuances, eliminating the need for users to remember specific device names while maintaining accurate command recognition.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If the number of connected devices increases, then system versatility is improved, but command ambiguity and errors increase

Engineering Contradiction:

Improvesystem versatilityVSAvoidcommand accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system introduces contextual data as an intermediary element between the user's speech command and the device control. This intermediary includes information about device locations, usage patterns, and relationships, which the machine learning model processes to disambiguate commands when multiple devices are present, maintaining high command accuracy despite increased system versatility.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements feedback mechanisms where contextual data from device usage patterns and locations is continuously fed back into the machine learning model. This feedback loop enables the system to learn from historical data and improve its ability to accurately interpret commands in complex environments with multiple devices.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12548564B2System and method for controlling a plurality of devices

Publication Date: 2026.02.10 QORVO PARIS

AI summary

Provided is a system and method for controlling a plurality of devices. The method includes generating a command script by processing a text string with at least one model, the text string including a natural language input by a user, modifying the command script based on contextual data, the command script including a configuration for at least one device, generating at least one command signal based on the command script, and controlling at least one device based on the at least one command signal.