Context-Based Dictionaries for Multimedia Audiobook Search
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Solution Overview
Problem
Conventional multimedia dictionaries provide general definitions for words, overwhelming users with multiple meanings and requiring them to discern the appropriate definition from the context, whereas multimedia content often benefits from context-specific definitions that incorporate linguistic and non-linguistic attributes.
Innovation Solution
A context-based dictionary system that processes multimedia content to provide definitions customized to specific contexts, utilizing tags, words, phrases, descriptions, environments, emotions, sentiments, and multimedia objects, enabling enhanced searching and user feedback for dictionary entry modification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional dictionaries provide general definitions for all words, then comprehensive information coverage is achieved, but user confusion increases due to multiple meanings and lack of context relevance
Solution Approach 1:
The patent segments dictionary information by creating context-specific entries that divide general word definitions into contextually relevant portions. Each context-based entry contains only the definitions and information applicable to that specific context, separating relevant from irrelevant information automatically.
Solution Approach 2:
The patent applies local quality by making dictionary entries context-dependent, where each context-based entry has customized information tailored to its specific context. The dictionary provides different information quality and detail levels based on the local context in which the word appears.
2Adaptability or versatility
If context-based dictionaries with multiple attributes are created, then searching capability is enhanced, but system complexity increases
Solution Approach 1:
The patent creates a universal context-based dictionary system that handles multiple types of contexts (linguistic, multimedia, emotional, environmental) through a unified framework. The same dictionary structure and attribute system serves multiple searching and retrieval functions across different media types and context categories.
Solution Approach 2:
The patent utilizes parameter changes by incorporating multiple attributes (emotional state, environmental context, multimedia type, etc.) that can be adjusted and filtered to change the dictionary's behavior and output. These parameters enable flexible searching without requiring separate systems for each context type.
3Measurement precision
If user feedback loops are implemented for dictionary modification, then dictionary accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent implements feedback mechanisms where user interactions (corrections, preferences, usage patterns) are continuously collected and used to refine context-based dictionary entries. The system processes feedback to automatically adjust and improve dictionary accuracy over time through learned patterns and user preferences.
Solution Approach 2:
The patent performs preliminary actions by pre-processing and organizing context attributes, multimedia metadata, and potential dictionary entries before they are needed for querying. This advance preparation reduces processing time during actual use by having information ready and structured for rapid retrieval and comparison.
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.