Conversational Learning System Voice Command Customization
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Solution Overview
Problem
Spoken language user interface systems are often not tailored to individual users, as they are designed to support pre-defined tasks and vocabulary, which may not align with a user's specific needs or preferences.
Innovation Solution
A machine and method for user-guided modification of a command vocabulary set in a conversational learning system, allowing users to teach and learn new voice commands and actions, using a system that includes a command modification tool, a bridge module, and a central processing unit to execute the learned commands, enabling customization of the user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a pre-defined vocabulary and task set are used in the spoken language user interface system, then the system design is simplified and easier to manufacture, but the system cannot be tailored to individual users' specific needs and preferences
Solution Approach 1:
The system performs preliminary actions by pre-defining a vocabulary and task set that can be later customized. The framework is established in advance with basic structures, and then users can modify and adapt it to their needs through the teaching interface, balancing initial simplicity with future adaptability.
Solution Approach 2:
The system transitions from a static pre-defined vocabulary to a dynamic customizable one. Users can teach new commands and modify existing ones through the teaching interface, allowing the system to adapt and evolve based on individual user needs while maintaining a structured framework.
2Ease of operation
If a pre-defined task set and vocabulary are used, then the system is easier to operate initially, but it does not align with user-specific tasks and vocabulary choices
Solution Approach 1:
The system enables self-service by allowing users to teach and customize the vocabulary and tasks themselves through the teaching interface. Users can independently modify the system to match their specific needs without requiring complex reconfiguration or technical expertise.
Solution Approach 2:
The teaching interface provides feedback mechanisms that allow users to interact with the system, test commands, and refine the vocabulary and task set based on their actual usage patterns and preferences, improving alignment over time.
3Stability of the object's composition
If the command vocabulary set is fixed and pre-defined, then the system structure remains simple and stable, but it cannot accommodate user-specific vocabulary and task requirements
Solution Approach 1:
The system segments the vocabulary and task set into modular components that can be independently modified. Users can teach and customize specific commands and tasks without affecting the overall system structure, maintaining stability while enabling adaptability.
Solution Approach 2:
The teaching interface provides universal functionality that works across different user needs and scenarios. The same interface structure supports various types of customization while maintaining a consistent system framework.
Data Source
AI summary
A machine, system and method for user-guided teaching and modifications of voice commands and actions to be executed by a conversational learning system. The machine includes a system bus for communicating data and control signals received from the conversational learning system to a computer system, a vehicle data and control bus for connecting devices and sensors in the machine, a bridge module for connecting the vehicle data and control bus to the system bus, machine subsystems coupled to the vehicle data and control bus having a respective user interface for receiving a voice command or input signal from a user, a memory coupled to the system bus for storing action command sequences learned for a new voice command and a processing unit coupled to the system bus for automatically executing the action command sequences learned when the new voice command is spoken.