Robot Voice Command Processing Using Image-Audio Region Segmentation
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Solution Overview
Problem
Existing robot systems for processing voice commands are complex, power-intensive, and prone to inaccurate processing, often requiring processor-intensive tasks and high power consumption, especially when distinguishing between voice commands and other sounds.
Innovation Solution
A robot system that uses image data and audio data to differentiate between sounds from specific regions in an environment, processing sounds from one region as voice commands based on the presence of predetermined inanimate objects, while processing sounds from another region differently, thereby reducing unnecessary processing and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot processes all received sounds as potential voice commands, then it does not miss any voice commands, but it increases processing time and power consumption due to analyzing non-voice sounds
Solution Approach 1:
The system segments the environment into multiple regions based on image data and object detection. Each region is assigned different processing priorities - regions containing inanimate objects have their sounds filtered out, while regions with potential users receive full voice command processing. This segmentation allows the robot to process only relevant sounds, reducing power consumption while maintaining reliable voice command detection.
2Measurement precision
If the robot uses complex processing algorithms to distinguish voice commands from other sounds, then it improves voice command accuracy, but it increases device complexity and computational requirements
Solution Approach 1:
The system performs preliminary actions by capturing image data and detecting inanimate objects before processing audio signals. Regions containing detected inanimate objects are pre-marked for filtering, so when audio processing occurs, the robot only needs to check whether a sound originates from a pre-identified non-voice region. This preliminary spatial mapping simplifies the audio processing complexity while maintaining high identification accuracy.
3Adaptability or versatility
If the robot continuously analyzes image data to identify regions for voice command processing, then it improves adaptability to environment changes, but it increases processing time and computational load
Solution Approach 1:
The system implements periodic action by updating image data and region identification at scheduled intervals rather than continuously. The robot captures images and detects inanimate objects at specific time periods, maintaining environmental adaptability while significantly reducing processing time and computational load compared to continuous analysis. This periodic updates approach balances adaptability with efficiency.
Data Source
AI summary
A robot obtains image data representative of an environment comprising a first region and a second region. A microphone receives sound from the environment. The robot determines, using the image data and audio data derived based on the received sound, whether the sound is received from the first region, and outputs a control signal for controlling the robot based on the audio data. Sounds received from the first region are processed as voice commands on the basis that one of the first region and the second region comprises a predetermined type of inanimate object. Sounds received from the second region are processed in a different manner.