Networked Translation System Using Segmentation and Merging
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Solution Overview
Problem
Existing machine translation programs are ineffective for difficult or less-studied languages, particularly for informal and colloquial communications, and human translators cannot ensure constant availability and quick response for internet applications.
Innovation Solution
A networked language translation system that combines human and machine translators, utilizing a web-based platform with a segmentation module, processing module, terminology search module, and user interface to facilitate efficient and accurate translations by aggregating resources from multiple translators and leveraging Translation Memory technology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If machine translation programs are used for difficult or less-studied languages, then translation speed and availability are improved, but translation quality deteriorates
Solution Approach 1:
The patent segments the translation process into distinct phases: machine translation for initial rapid output and human translation for quality refinement. The source text is divided into segments that can be processed independently, allowing machine translation to provide quick results while human translators focus on improving quality for difficult languages and colloquial content.
Solution Approach 2:
The patent merges machine translation and human translation into a unified system. Machine translation provides the baseline translation and speed, while human translators review and refine the output. The system combines the productivity of machine translation with the quality of human translation, allowing both to work together rather than replacing one another.
2Measurement precision
If human translators are used for accurate translation, then translation quality is improved, but availability and response time deteriorate
Solution Approach 1:
The patent applies preliminary machine translation before human translation. The machine translation module processes the source text first, providing an initial translation that human translators can then review and refine. This preliminary action reduces the workload for human translators and enables faster overall response time while maintaining quality.
Solution Approach 2:
The patent introduces machine translation as an intermediary between the source text and the final human translation. The machine translation output serves as a mediator that human translators review and improve upon, allowing human translators to focus on quality enhancement rather than producing translations from scratch, thus maintaining both quality and availability.
3Measurement precision
If a large team of translators works on content, then translation quality and coverage are improved, but system complexity and coordination difficulty increase
Solution Approach 1:
The patent creates a universal translation platform that handles multiple languages and translation types through a single integrated system. The platform provides standardized interfaces for both machine and human translation, allowing a large team of translators to work on diverse content without increasing operational complexity. The system manages multilingual content uniformly across all languages.
Solution Approach 2:
The patent implements self-service mechanisms where the system automatically manages translation workflows, assigns tasks to appropriate translators, and coordinates progress without requiring complex manual coordination. The platform autonomously handles the complexity of managing large teams across multiple languages, reducing the coordination burden on individual users.
Data Source
AI summary
A networked language translation system and method allowing access by a distributed network of human and machine translators that communicate electronically to provide for the translation of material. The system and method provide a way to aggregate the resources of a large number of intermittently available, mixed competency translators, human or machine, in order to provide high-quality translations.