Wearable Image Context for Ambiguous XR Voice Commands
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Solution Overview
Problem
Existing XR devices struggle with initiating actions using verbal commands that include vague language, such as demonstrative pronouns like 'this' and 'that', leading to ambiguity and inefficiency in user interactions.
Innovation Solution
The XR device employs a model that combines natural language processing with computer vision to supplement verbal commands with sensor and image data, using APIs to identify and execute actions based on user intent, even with ambiguous terms, by leveraging a neural network or alternative models to refine processing and determine relevant objects in the user's environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If verbal commands with vague language (e.g., demonstrative pronouns) are used, then user interaction becomes more natural and intuitive, but ambiguity increases and action identification becomes unreliable
Solution Approach 1:
The patent introduces an image processing intermediary that captures visual context from the environment and combines it with the verbal command. The image serves as a mediator that disambiguates vague pronouns by identifying referenced objects visually, allowing the system to resolve ambiguity while maintaining natural interaction. For example, when a user says 'move that object,' the image processing identifies which object is being referred to based on visual context.
Solution Approach 2:
The patent merges multiple input modalities (verbal commands and visual image data) into a unified processing framework. By combining the semantic information from speech with the spatial and contextual information from images, the system creates a more robust interpretation of user intent. This multi-modal merging allows vague verbal references to be resolved through visual confirmation.
2Adaptability or versatility
If traditional verbal command processing is used, then device complexity remains low, but the system cannot resolve ambiguous references in commands
Solution Approach 1:
The patent implements a universal processing framework that handles both simple and complex commands through a single integrated system. The same image processing and model application infrastructure that resolves ambiguous pronouns also enhances the interpretation of all verbal commands, providing multi-functionality. This universal approach allows the system to handle diverse command types without requiring separate specialized processing paths.
Solution Approach 2:
The system performs preliminary image capture and processing before final command interpretation. By pre-processing the visual context and preparing object identification data in advance, the system reduces the complexity of the final decision-making process. The model is applied to images and commands in advance to identify potential objects and their characteristics, making the final action selection more efficient.
3Measurement precision
If image processing and model application are applied to every command, then object identification accuracy improves, but processing time increases
Solution Approach 1:
The patent applies image processing and model application selectively rather than universally to all commands. When a command contains ambiguous references or object identifiers, the system triggers image processing to resolve the ambiguity. For straightforward commands without ambiguous references, the system may proceed with minimal or no image processing, thus avoiding unnecessary processing time while maintaining high accuracy when needed.
Data Source
AI summary
According to at least one implementation, a method includes identifying a command from a user of a device. In response to the command, the method further includes identifying an image associated with a gaze of the user and identifying an action based on an application of a language model to the command and the image, the application of the language model including an identification of an object for the command in the image.