Full-Media Translation Using a Virtual Map for Cross-Media Coherence
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Solution Overview
Problem
Current digital translators struggle to provide seamless translation of documents containing multiple types of media, leading to a frustrating user experience due to the separation of different digital translation techniques for various media types.
Innovation Solution
A system that utilizes processor units to separate documents into elements, determine attributes, create a virtual map identifying relationships between these elements, and adjust translations based on these relationships to maintain coherence across different media types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate digital translation techniques are used for different media types, then each media type can be translated using specialized algorithms, but the translation process becomes fragmented and user experience deteriorates
Solution Approach 1:
The patent combines multiple separate translation techniques for different media types (text, image, audio, video) into a unified translation system. The virtual map integrates all media elements and their relationships, allowing the system to translate documents with multiple media types seamlessly as a cohesive unit rather than separate fragmented processes, thereby improving user experience while maintaining translation quality.
Solution Approach 2:
The system creates a universal translation platform that handles multiple media types through a single integrated architecture. The virtual map serves as a multi-functional data structure that stores relationships between text, images, audio, and video elements, enabling one system to perform multiple translation functions that were previously handled by separate specialized systems.
2Manufacturing precision
If documents are separated into elements for translation, then translation precision can be improved, but the complexity of managing relationships between elements increases
Solution Approach 1:
The patent segments the document into discrete elements (text, image, audio, video) while maintaining their relationships through a virtual map. This segmentation allows each element to be translated with high precision using appropriate media-specific algorithms, while the virtual map manages the complexity of relationships between elements through a structured data organization approach.
Solution Approach 2:
The virtual map acts as an intermediary data structure that mediates between the segmented elements and the translation process. It stores and manages relationships between elements, allowing the system to access connection information when needed without requiring complex direct management of all element relationships, thus reducing overall system complexity.
3Stability of the object's composition
If translations are adjusted based on relationships between elements, then coherence across media types is maintained, but the translation process becomes more complex
Solution Approach 1:
The system performs preliminary analysis of element relationships and creates the virtual map before the actual translation occurs. By pre-establishing the structural relationships between text, image, audio, and video elements, the system can efficiently adjust translations to maintain coherence without requiring complex real-time relationship analysis during the translation process itself.
Solution Approach 2:
The system uses the virtual map to provide feedback about element relationships during translation adjustments. When translating an element, the system consults the virtual map for relationship information and adjusts the translation accordingly to maintain coherence with related elements, creating a feedback loop that ensures consistent translation across all media types.
Data Source
AI summary
A computer implemented method for translating a document. A number of processor units separate the document into elements having media types. The number of processor units determine attributes for the elements. The number of processor units create a virtual map identifying relationships between the elements using the attributes. The number of processor units translate the elements into a target language based on media types for the elements. The number of processor units adjust translations for the elements based on the relationships between the elements using the virtual map to create adjusted translations for the elements. The number of processor units generate the translated document using the adjusted translations for the elements and the virtual map.