Localization Table Token Matching for Translation Redundancy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
App developers face challenges in translating text for international and multicultural users due to manual translation errors, high costs of hiring professional translators, and redundant translations across multiple apps, with existing systems failing to efficiently manage and reuse already translated content.
Innovation Solution
A network-based system with a Conversion Management (CM) computing device that receives input text strings and locale identifiers, converts them into searchable tokens, compares these tokens to a localization table, and identifies matching translations for automatic language conversion, preventing redundant translations and enabling efficient reuse of existing translations across apps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual translation or machine translation service is used, then translation can be performed, but translation errors occur and quality is insufficient
Solution Approach 1:
The system enables self-service translation by allowing app developers to automatically retrieve translations through the localization table without needing to manually translate or hire professionals. The automated lookup process based on locale identifiers and text tokens provides consistent, error-free translation retrieval.
Solution Approach 2:
The system implements feedback mechanisms where translation results are stored in the localization table and can be retrieved consistently for future use. This feedback loop ensures that translation accuracy is maintained across multiple applications and updates.
2Reliability
If professional translators are hired, then translation quality improves, but cost becomes prohibitive
Solution Approach 1:
The system creates reusable translation copies stored in the localization table. Instead of paying professional translators for each translation task, the system stores translated text as reusable data that can be accessed multiple times across different apps, dramatically reducing costs.
Solution Approach 2:
The localization table serves multiple functions: it stores translations for multiple languages, supports multiple applications, and provides a universal lookup mechanism. This multi-functionality eliminates the need for separate translation services for each app, reducing overall costs.
3Adaptability or versatility
If translations are performed for each app separately, then translation needs are met, but redundant translations occur and efficiency decreases
Solution Approach 1:
The system merges translation operations across multiple applications by using a single shared localization table. Instead of maintaining separate translation databases for each app, the system combines them into one unified resource that serves all applications, eliminating redundancy.
Solution Approach 2:
The localization table is designed as a universal data structure that can serve multiple applications simultaneously. The same table stores translations for different apps, and the lookup mechanism works universally across all applications, improving efficiency.
4Adaptability or versatility
If existing translations are not reused, then translation flexibility is maintained, but time and money are wasted on redundant work
Solution Approach 1:
The system performs preliminary action by pre-storing translations in the localization table before they are needed. When a translation is required, the system can immediately retrieve it from the pre-computed table rather than performing the translation work at the moment of need, saving time.
Solution Approach 2:
The system enables self-service translation retrieval where the automated lookup process instantly provides translations without requiring manual intervention or time-consuming translation processes, allowing developers to quickly access needed translations.
Data Source
AI summary
A conversion management (CM) computing device is provided. The CM computing device includes a processor in communication with a memory. The processor is causes the CM computing device to receive, from an app developer device, a plurality of input locale identifiers and an input text string, convert the input text string into at an input text token, compare the input locale identifiers and the input text token to a localization table that includes a plurality of entries. Each entry includes a stored text token, a stored locale identifier, and a translated text string. The processor further causes the CM computing device to identify a matching entry included within the localization table for the input locale identifiers. The matching entry includes a stored locale identifier matching one of the input locale identifiers, a stored text token matching the text token, and an associated translated text string.