Multilingual Translation System Concept Database Iterative Refinement
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Solution Overview
Problem
Conventional bilingual translation approaches require isolated processes for each source language and target language, leading to inefficiencies and increased cognitive effort for translators due to ambiguity in source language terms, which are not effectively leveraged across multiple target languages.
Innovation Solution
A multilingual translation system utilizing a concept database with multilingual vectors and metadata to inform translations across multiple target languages, where human input during translation processes is used to disambiguate terms and correct errors, allowing for iterative refinement of translation recommendations based on previous decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional bilingual translation approaches are used for each source language and target language pair, then translation processes are simple and isolated, but translation efficiency decreases and cognitive effort increases due to repeated disambiguation work
Solution Approach 1:
The patent merges multiple bilingual translation processes into a single multilingual translation system. Instead of treating each language pair independently, the system combines them into an integrated framework where a source language text is translated into multiple target languages simultaneously, sharing common processing components and knowledge bases.
Solution Approach 2:
The translation system achieves multi-functionality by enabling a single source language input to be translated into multiple target languages through a unified process. The system uses universal components such as a shared concept database, common disambiguation mechanisms, and reusable translation memories that serve all language pairs, reducing redundant work and improving efficiency.
2Ease of operation
If translators work independently on each target language without sharing information, then translation processes are simple and isolated, but the same disambiguation work is repeated across multiple languages increasing cognitive effort
Solution Approach 1:
The system implements feedback mechanisms where translation decisions made for one target language are fed back into the system and made available to translators working on other target languages. The concept database and translation memory store disambiguation decisions and contextual information, allowing subsequent translators to leverage previous work rather than repeating the same analytical processes.
Solution Approach 2:
The patent introduces intermediary components such as the concept database and translation memory that mediate between translators working on different target languages. These intermediaries store and share contextual information, disambiguation decisions, and translation patterns, enabling translators to access previously made decisions without direct communication, thus reducing cognitive load and time expenditure.
3Productivity
If a multilingual translation system with shared concept database is used, then translation efficiency improves through information sharing, but system complexity and initial setup requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing source language text to identify concepts, entities, and contextual information before actual translation into target languages. The concept database is pre-populated with multilingual terminology and relationships, and translation memories are pre-filled with existing translation pairs, reducing the complexity of real-time processing during the translation phase.
Solution Approach 2:
The patent segments the translation system into distinct functional modules including concept identification, disambiguation, translation memory lookup, and target language generation. This modular segmentation allows each component to handle specific tasks independently, making the overall complex system more manageable and easier to implement despite its multifunctional capabilities.
4Reliability
If human translators review and correct computer translations for each language pair separately, then translation quality improves through human feedback, but the time and resources required increase significantly
Solution Approach 1:
The patent merges the human review process across multiple language pairs into a unified workflow. Translators review and correct translations in a centralized system where their corrections and feedback are automatically applied to all relevant target languages, rather than performing separate review processes for each language pair, thus maintaining quality while reducing total review time.
Data Source
AI summary
Computer-assisted multilingual translations may utilize a concept database storing entries for a plurality of concepts, the entries including multilingual vectors of counterpart expressions for the respective concepts in a source language and multiple target languages. In various embodiments, for a given content item having an associated source-language expression, a set of concepts whose database entries match at least the source-language expression is identified, and target-language expressions for the identified concepts are used to iteratively update the set of concepts by identifying therein a subset of concepts that also match a user-selected one of the target-language expressions.