Context-Aware Software Localization Interface for Translation Accuracy
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Solution Overview
Problem
Localization experts face challenges in accurately localizing software applications without sufficient context data, leading to ambiguous translations due to the inability to distinguish between similar resource phrases with different meanings, such as 'Enter' referring to a button click or granting access.
Innovation Solution
A system that provides context information about an application's interface, including editable and non-editable portions, allows localization experts to highlight and modify localizable elements, and includes a rating for priority, ensuring accurate translation by preserving context and providing a What You See Is What You Get (WYSIWYG) editing facility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If only a list of resources to be localized is provided to the localization expert, then the localization process is simplified and faster, but the translation accuracy decreases due to ambiguous meaning of resources
Solution Approach 1:
The system performs preliminary action by automatically capturing interface snapshots and extracting context information before the localization process begins. This pre-prepared context is then provided to the localization expert along with the resources to be localized, enabling accurate translation without slowing down the overall process.
Solution Approach 2:
The patent introduces an intermediary component that acts as a bridge between the application interface and the localization expert. This intermediary automatically generates context information including snapshots, text strings, and interface elements, thereby mediating between the raw application data and the human translator to ensure accurate understanding without requiring the expert to manually gather context.
2Measurement precision
If context information is provided to help distinguish between similar resource phrases, then translation accuracy improves, but the complexity of the localization process increases
Solution Approach 1:
The system implements self-service by automatically generating and organizing context information without requiring manual intervention. The application interface is automatically captured, text strings are extracted, and context data is structured and presented to the localization expert, thereby reducing process complexity despite providing comprehensive context.
Solution Approach 2:
The context information is segmented into distinct, manageable components including interface snapshots, text strings, and metadata about interface elements. This segmentation allows the localization expert to process information in organized chunks rather than dealing with a monolithic complex dataset, reducing perceived complexity while maintaining comprehensive context.
3Adaptability or versatility
If non-editable text strings in the interface are made localizable, then more content can be translated, but the interface modification complexity increases
Solution Approach 1:
The patent introduces an intermediary that handles the complexity of making non-editable text strings localizable. This intermediary component automatically identifies, extracts, and manages translatable elements within the interface, shielding the localization expert from the underlying complexity while expanding localization coverage to previously non-editable content.
Solution Approach 2:
The system creates copies of non-editable text strings and interface elements that can be independently localized without modifying the original interface structure. These copied elements are presented to the localization expert for translation, allowing extensive localization coverage while keeping the original interface intact and managing complexity through duplication rather than direct modification.
Data Source
AI summary
Applications can be localized by localization experts to allow them to be used by a broader customer base. The localization can be done given interface context to produce more applicable results. A localization expert may determine that certain content within the interface context should be localized, however is not localizable by the expert. The localization expert may indicate that the content is localizable and the developer may receive the indication and provide the localization expert with updated interface context allowing localization of the previously un-localizable content.