Voice Command Control for Autonomously Motile Devices
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Solution Overview
Problem
Current systems for controlling autonomously motile devices lack efficient methods for interpreting and executing user commands in a multi-device environment, particularly in scenarios where devices are distributed across different networks and locations, leading to limitations in seamless interaction and task execution.
Innovation Solution
A speech-processing system that integrates automatic speech recognition and natural language understanding, allowing devices to interpret voice commands and execute tasks by utilizing a wakeword detection mechanism, enabling distributed processing across user devices, autonomously motile devices, and remote systems to coordinate actions effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If speech-processing components are distributed across multiple devices and networks, then system versatility and adaptability improve, but device complexity and coordination difficulty increase
Solution Approach 1:
The speech-processing system is divided into separate components distributed across different devices: wake word detection on the autonomously motile device, speech recognition on user devices, and natural language understanding on remote systems. This segmentation allows each component to operate independently on suitable hardware, improving system adaptability while managing complexity through modular architecture.
Solution Approach 2:
The speech-processing components are designed to be universally applicable across multiple device types and network configurations. The same wake word detection mechanism can operate on various autonomously motile devices, and the distributed architecture supports different network topologies, making the system versatile and adaptable to diverse environments.
2Measurement precision
If wake word detection is implemented continuously, then command detection accuracy improves, but energy consumption increases
Solution Approach 1:
Instead of continuous processing, the system uses periodic wake word detection followed by conditional speech recognition. The autonomously motile device periodically checks for wake words and only activates full speech recognition processing when triggered, maintaining high detection accuracy while significantly reducing energy consumption during idle periods.
Solution Approach 2:
The wake word detection serves as a preliminary filtering stage that prepares the system for more intensive speech processing. By performing this preliminary check continuously at low power and only activating full processing when needed, the system maintains readiness for accurate command detection while managing energy consumption effectively.
Data Source
AI summary
An autonomously motile device may be controlled by speech received by a user device. A first speech-processing system associated with the user device may determine that audio data includes a representation of a command; a second speech-processing system associated with the autonomously motile device may determine that the command should be executed by the autonomously motile device. A network connection is established between the user device and the autonomously motile device, and a device manager authorizes execution of the command.