Directional Voice Command Identification in Mixed Reality
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Solution Overview
Problem
Current voice recognition technology systems require a wake-up command and authenticate a single user based on voice identification, limiting communication between multiple users and not allowing for dynamic authentication of identities or location-based permissions within mixed reality environments.
Innovation Solution
A system that analyzes directional voice commands using natural language processing and corpus knowledge algorithms to identify users, generate scenarios, and validate locations within mixed reality environments, enabling communication between multiple AI devices without a wake-up command and allowing for context-based and location-based permissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If voice recognition systems authenticate a single user based on voice identification, then user security is maintained, but communication between multiple users is limited
Solution Approach 1:
The system dynamically adapts its authentication behavior based on the voice command content. For personalized queries, it performs user authentication; for general information queries, it allows direct processing. This dynamic approach enables the system to handle multiple user scenarios without requiring wake-up commands for each interaction.
Solution Approach 2:
The system changes the authentication parameter based on the type of voice command received. By analyzing the voice command content and determining whether user identification is necessary, the system adjusts its security level accordingly, allowing efficient communication for non-personalized queries while maintaining security for personalized interactions.
2Reliability
If wake-up commands are required for voice authentication, then user security is ensured, but communication efficiency between AI devices is reduced
Solution Approach 1:
The system performs preliminary analysis of the voice command content to determine whether authentication is necessary before executing the command. This preliminary action allows the system to skip the wake-up command step for non-personalized queries, improving communication efficiency while maintaining security for personalized interactions.
Solution Approach 2:
The system autonomously determines whether user authentication is required based on the voice command content, eliminating the need for manual wake-up commands. The system self-adjusts its authentication requirements, allowing direct processing for general queries while maintaining security protocols for personalized interactions.
3Device complexity
If single-user authentication is implemented, then system complexity is reduced, but location-based permissions and scenario generation are limited
Solution Approach 1:
The system segments the authentication process into different levels: basic voice recognition for all commands, and enhanced user identification only when necessary for personalized queries. This segmentation allows the system to maintain low complexity for general operations while enabling advanced scenario generation and location-based permissions when needed.
Solution Approach 2:
The voice recognition system is designed to handle multiple functions universally: it can process both personalized and non-personalized queries, generate scenarios based on voice commands, and implement location-based permissions all through a single unified authentication framework that adapts to different requirements.
Data Source
AI summary
Embodiments of the present invention provide a computer system a computer program product, and a method that comprises analyzing a received directional voice command by identifying a plurality of contextual factors associated with at least one user in a plurality of users using a natural language processing algorithm; dynamically identifying the at least one user in the plurality of users based on an analysis of the identified contextual factors associated with the received directional voice command; generating a plurality of scenarios within a mixed reality environment based on the analysis of the identified contextual factors associated with received directional voice command; identifying a location associated with at least one received directional voice command within a plurality of directional voice commands; and validating the location associated with the at least one received directional voice command using a corpus knowledge algorithm.