Context-Based Dictionaries for Audiobook Search
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Solution Overview
Problem
Conventional multimedia audiobook systems rely on general dictionaries that provide uniform definitions for words, regardless of context, leading to confusion for users who need context-specific explanations.
Innovation Solution
The development of context-based dictionaries that utilize linguistic and non-linguistic information, defined by tags, words, phrases, descriptions, environments, emotions, sentiments, multimedia objects, or content, to provide customized definitions and attributes that enhance searching and user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If general dictionaries are used to provide uniform definitions for words, then the dictionary structure remains simple and easy to maintain, but user understanding deteriorates due to lack of context-specific explanations
Solution Approach 1:
The patent segments the dictionary into multiple context-specific dictionaries (e.g., character dictionary, setting dictionary, plot dictionary, theme dictionary) rather than using a single general dictionary. Each dictionary contains entries relevant to specific contexts, allowing the system to provide targeted information while maintaining manageable structure through organization by context type.
Solution Approach 2:
The patent applies local quality by providing different dictionary entries and levels of detail appropriate to each specific context. Instead of uniform definitions for all words, the system provides context-specific explanations tailored to character motivations, setting descriptions, plot developments, or thematic elements, thereby improving information relevance without requiring complete redesign of the entire dictionary system.
2Productivity
If context-based dictionaries with multiple attributes are created, then searching effectiveness improves, but system complexity increases due to multiple dictionaries and processing requirements
Solution Approach 1:
The patent implements multi-functionality by enabling a single search query to potentially retrieve information from multiple context-specific dictionaries (character, setting, plot, theme). The search function is designed to be universal, automatically determining which dictionaries are relevant based on the query and returning synthesized results, thereby improving searching effectiveness without requiring separate search systems for each context type.
Solution Approach 2:
The patent introduces an intermediary processing layer that manages the complexity of multiple dictionaries. This intermediary system analyzes search queries, determines relevant context types, retrieves appropriate dictionary entries, and synthesizes coherent results. This mediator approach allows the system to handle multiple dictionaries efficiently without exposing users to the underlying complexity.
3Ease of operation
If synchronized multimedia content presentation is implemented, then user engagement improves, but processing time and system resources increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and indexing dictionary entries along with their associated multimedia content (images, audio, video) before user interaction. Context information is extracted and organized in advance, allowing the system to quickly retrieve and present relevant synchronized content during actual use without requiring real-time processing of all content, thereby reducing perceived processing time while maintaining high user engagement.
Data Source
AI summary
A method, non-transitory computer-readable storage medium and system is disclosed for using context-based dictionaries to search through multimedia data using input that specifies tags, words, phrases, descriptions, environments, emotions, sentiments, multimedia objects or content, or other relevant attributes. The system retrieves original content, analyzes and processes it, and presents to the user synchronized multimedia content and text content that is automatically tagged for searching. The system creates dictionaries containing word definitions and information that have been customized according to context; in addition, the system creates textual and non-linguistic attributes that enable and enhance searching functions; moreover, it enables modification of the dictionary entries as well as its searching functions through a feedback loop that may include input from human users and artificial intelligence programs; furthermore, the system may be used to create or modify a linguistic or a multimedia instantiation of a story.