18081076. CONTENT GENERATION simplified abstract (Amazon Technologies, Inc.)
Contents
- 1 CONTENT GENERATION
CONTENT GENERATION
Organization Name
Inventor(s)
Robinson Piramuthu of Oakland CA (US)
Sanqiang Zhao of Santa Clara CA (US)
Yadunandana Rao of Sunnyvale CA (US)
Zhiyuan Fang of San Jose CA (US)
CONTENT GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18081076 titled 'CONTENT GENERATION
Simplified Explanation
The patent application describes techniques for generating content associated with a user input/system generated response. Natural language data is generated based on the user input, with ambiguous references to entities replaced with the corresponding entity. Entities in the data are extracted, and image data representing the entity is determined. Background image data associated with the entities and the portion is also determined, along with attributes that modify the entities in the sentence. Spatial relationships between entities are extracted, and image data representing the natural language data is generated based on the background image data, entities, attributes, and spatial relationships. Video data is then generated based on the image data, including animations of the entities moving.
- Natural language data generation based on user input
- Replacement of ambiguous references with corresponding entities
- Extraction of entities and determination of image data
- Background image data determination
- Extraction of attributes modifying entities
- Extraction of spatial relationships between entities
- Generation of image and video data based on the above information
Potential Applications
The technology described in this patent application could be applied in various fields such as virtual reality, augmented reality, content creation, and interactive storytelling.
Problems Solved
This technology solves the problem of efficiently generating content associated with user inputs or system responses, particularly in scenarios where natural language data needs to be converted into visual representations.
Benefits
The benefits of this technology include improved user engagement, enhanced visualization of data, and the ability to create dynamic and interactive content based on user interactions.
Potential Commercial Applications
The potential commercial applications of this technology include virtual reality content creation tools, interactive storytelling platforms, and augmented reality applications for education and entertainment.
Possible Prior Art
One possible prior art for this technology could be systems or methods for generating visual content based on textual inputs, such as image captioning algorithms or natural language processing tools.
Unanswered Questions
How does this technology handle complex or abstract concepts in natural language data?
This article does not provide specific details on how the technology processes and represents complex or abstract concepts in the generated content.
What are the limitations of the spatial relationship extraction in this technology?
The article does not address any potential limitations or challenges in accurately extracting spatial relationships between entities in the natural language data.
Original Abstract Submitted
Techniques for generating content associated with a user input/system generated response are described. Natural language data associated with a user input may be generated. For each portion of the natural language data, ambiguous references to entities in the portion may be replaced with the corresponding entity. Entities included in the portion may be extracted, and image data representing the entity may be determined. Background image data associated with the entities and the portion may be determined, and attributes which modify the entities in the natural language sentence may be extracted. Spatial relationships between two or more of the entities may further be extracted. Image data representing the natural language data may be generated based on the background image data, the entities, the attributes, and the spatial relationships. Video data may be generated based on the image data, where the video data includes animations of the entities moving.
