Natural Language Game Configuration via Speech and Vision
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Solution Overview
Problem
The complexity of tabletop games and the need for sophisticated programming to configure voice-enabled gaming systems pose challenges for game developers, who may lack the necessary programming skills or resources to create systems that can guide and participate in games through spoken interactions and camera interfaces.
Innovation Solution
A tabletop game system that leverages speech processing, computer vision, and natural language generation to ingest and process natural language rules, allowing game developers to teach the system game rules without dedicated coding, using APIs, text data, and image data to build a logical model for guiding and participating in games.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sophisticated programming is used to configure voice-enabled gaming systems, then the system functionality and intelligence are improved, but the device complexity and programming requirements increase
Solution Approach 1:
The patent introduces natural language as an intermediary between the user and the gaming system. Instead of requiring users to program complex voice recognition systems, they can simply speak natural language to configure and control the system. The system processes this natural language input through speech-to-text conversion and natural language processing to achieve the desired functionality, thereby reducing programming requirements while maintaining system capability.
Solution Approach 2:
The system enables self-service configuration through natural language processing. Users can teach the system game rules and configure gameplay parameters by speaking naturally, without needing to write code or perform complex technical setup. The system automatically processes these inputs, converts speech to actionable commands, and configures itself based on user instructions.
2Ease of operation
If natural language processing is implemented for game configuration, then ease of operation is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing by converting speech to text and pre-processing the natural language input before full analysis. This preliminary action prepares the data in advance, allowing for more efficient subsequent processing and reducing the overall time required for natural language configuration tasks.
Solution Approach 2:
The system applies partial processing to natural language inputs by identifying and processing only the most critical and relevant portions of user speech. Rather than analyzing every aspect of the input equally, the system focuses on key configuration parameters and commands, thereby reducing processing time while maintaining ease of operation for essential functions.
Data Source
AI summary
This disclosure describes a tabletop game assistant system configured to ingest and guide tangible games (such as board games, card games, etc.) using natural language interaction and image capture/visual display components. The system can include features enabling a game developer to “teach” the system the rules of a game using natural language, such as written instructions, to reduce or eliminate the need for writing dedicated code. The system may process images of a game board and/or tokens such as game pieces and/or cards to further generate game data in the form of a logical game model. The system can use the game data to guide human players of the game and, in some cases, participate as a player itself. The system may further be configured to observe a game and detect invalid actions, answer questions regarding the rules, and suggest moves. The system may provide additional utilities such as generating a random output (e.g., rolling virtual dice) and learning to recognize new game pieces.