Software UI Text Change Detection for Translation Efficiency
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Solution Overview
Problem
Traditional methods for translating software applications are inefficient and costly, requiring extensive manual verification and rebuilding of the entire application each time text changes, due to lack of context and scalability issues as the number of languages increases.
Innovation Solution
A system and method that compares new and previously accepted screenshots and hierarchy files to identify changed text, presenting only the changed text to translators for verification, highlighting the changes for focus and reducing the need to rebuild the entire application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional translation methods are used to translate all text in software applications, then translation completeness is improved, but time consumption and cost increase significantly
Solution Approach 1:
The patent segments the translation verification process by comparing screenshots to identify only the specific text elements that have changed since the last version. Instead of verifying all text in the application, the system divides the work into discrete changed elements, allowing translators to focus solely on those portions. This segmentation resolves the contradiction by maintaining translation completeness for changed text while dramatically reducing overall time consumption.
Solution Approach 2:
The patent performs preliminary actions by automatically capturing screenshots, comparing them to identify changed text, and preparing translation requests before human translators begin work. The system pre-processes the application by detecting text changes through screenshot comparison and hierarchy file analysis, so that translators receive only the necessary changed text with full context already prepared. This preliminary automation reduces the manual time investment required while ensuring no translation is missed.
2Measurement precision
If translators manually verify all text in the software application, then translation accuracy is improved, but productivity decreases
Solution Approach 1:
The patent extracts only the changed text elements from the complete application by comparing screenshots and analyzing hierarchy files. The system takes out the specific text portions that have changed and isolates them for translation verification, while excluding all unchanged text. This extraction maintains translation accuracy for the changed elements while significantly improving productivity by eliminating the need to verify unchanged text manually.
Solution Approach 2:
The patent creates visual copies of the application interface through screenshots, which are then compared to identify text changes. These screenshot copies provide translators with contextual visual representations of where the changed text appears in the application, enabling accurate translation verification without requiring translators to manually navigate through the entire application. This copying approach maintains accuracy while boosting productivity.
3Loss of information
If the entire software application is rebuilt each time text changes, then translation context is preserved, but development time increases
Solution Approach 1:
The patent segments the application reconstruction process by using screenshot comparisons to identify only the specific user interface portions where text has changed. Instead of rebuilding the entire application, the system focuses reconstruction efforts on the segmented changed areas, preserving translation context where needed while avoiding unnecessary rebuilding of unchanged portions. This segmentation resolves the contradiction between maintaining context and reducing development time.
Solution Approach 2:
The patent performs preliminary screenshot capture and text change detection before the translation and rebuilding process. By having screenshots already captured and changed text already identified, the system eliminates the need for time-consuming full application rebuilds to verify text context. The preliminary actions provide the necessary context information in advance, allowing faster processing while maintaining translation accuracy.
Data Source
AI summary
Disclosed herein are systems and methods for translating and verifying text in a variety of different languages for the same software application. When the text in the application changes. embodiments of the disclosure may include translating and/or verifying only the text that has changed. The system may compare the new screenshot(s) with previously accepted screenshot(s) to locate the text that has changed. The text that has not changed (since the last accepted translation) may not be translated and/or verified once accepted by a translator. The system may highlight the text that has changed so that the translator may focus only on the relevant portions of the user interface and not have to search for the text that has changed. For rejected translations. the system may repeat the process. translating and/or verifying only the rejected text (instead of translating/verifying all text again).