AI Joke Generation via Keyword Segmentation and Dynamic Assembly
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Solution Overview
Problem
Current computational humor systems, such as AI virtual assistants, are limited in generating original, contextually integrated, and human-like jokes, often relying on prewritten content rather than ad-libbing newly created jokes during interactions.
Innovation Solution
A system and method that utilize databases and servers to select topic keywords from received text, generate punch words, and create jokes by adding bridge words, with machine learning language models to predict and rank humor, ensuring the generated jokes are original, contextually integrated, and humorous.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If AI virtual assistants use prewritten jokes from databases, then joke delivery is reliable and consistent, but originality and contextual integration are lost
Solution Approach 1:
The joke generation process is divided into distinct components: topic extraction from context, keyword identification, punch line generation using wordplay rules, and joke assembly. This segmentation allows each component to be optimized independently while maintaining overall reliability
Solution Approach 2:
The system transitions from static prewritten joke databases to dynamic real-time generation. The joke structure adapts to incoming context by extracting relevant topics and generating appropriate punch lines on demand, enabling both reliability through structured processes and adaptability through contextual responsiveness
2Adaptability or versatility
If computational humor systems generate original jokes in real-time, then contextual integration and originality improve, but system complexity increases
Solution Approach 1:
The system employs universal components that handle multiple aspects of joke generation: topic extraction mechanisms work across different context types, wordplay generation applies consistent rules to various keywords, and joke assembly uses standardized templates. This universality manages complexity by reusing the same mechanisms across different joke types and contexts
Solution Approach 2:
The system adjusts generation parameters such as topic selection, keyword weighting, and punch line complexity based on contextual input. By dynamically changing these parameters rather than restructuring the entire system, the patent achieves high contextual integration with manageable complexity
3Manufacturing precision
If joke generation uses multiple components (topic, angle, punch line), then joke quality improves, but generation time and processing complexity increase
Solution Approach 1:
The system performs preliminary topic extraction and keyword identification before punch line generation. By preparing these components in advance and using efficient lookup mechanisms for wordplay pairs, the system reduces overall generation time while maintaining the three-component joke structure quality
Solution Approach 2:
The system uses template-based joke assembly where proven joke structures are replicated and adapted to new topics. This copying of effective joke patterns maintains structural quality while significantly reducing processing time compared to creating entirely new joke structures each time
Data Source
AI summary
Methods for generating jokes include coupling one or more servers with one or more databases having words stored therein; receiving text at the server(s) from an external source communicatively coupled with the server(s) through a telecommunications network; in response to receiving the text at the server(s): selecting one or more topic keywords of the topic sentence using the server(s); generating one or more punch words with the server(s) using words stored in the database related to the topic keyword(s); adding bridges to the punch word(s), using the server(s), to generate one or more jokes; communicating a signal to a first computing device through the telecommunications network using the server(s); and in response to receiving the signal at the first computing device, displaying or speaking one of the one or more jokes using the first computing device. Systems for generating jokes include networked computer components configured to carry out the methods.