Translation Server Crowdsourcing Incentives
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Solution Overview
Problem
Current translation technologies face limitations in improving translation rates, as they rely primarily on user intention and do not effectively leverage collective input from multiple devices connected through a network.
Innovation Solution
A method and system for a translation server that categorizes translation requests and incentivizes user participation by offering rewards, allowing multiple users to contribute translated content through a network, thereby enhancing translation quality and rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional grammar-based translation methods are used, then translation accuracy is maintained at acceptable levels, but translation rate and coverage are limited
Solution Approach 1:
The patent merges traditional grammar-based translation methods with statistical translation engines and crowd-sourced user translations. The translation server combines multiple translation approaches (grammar method, statistical translation, and user-contributed translations) to achieve both high translation rate and improved accuracy. This consolidation allows the system to leverage the strengths of each method while mitigating their individual limitations.
Solution Approach 2:
The patent implements feedback mechanisms where users receive rewards based on the quality and utility of their translations. The system collects translation data from users, analyzes it to identify high-quality contributions, and uses this feedback to improve the statistical translation engine. This continuous feedback loop enables the system to learn from user inputs and progressively improve translation accuracy while maintaining high productivity.
2Productivity
If statistical translation engines are used to improve translation rate, then translation coverage increases, but translation accuracy for niche topics deteriorates
Solution Approach 1:
The patent applies local quality by providing specialized translation support for different topic domains. The system identifies niche topics through user search patterns and translation requests, then directs these to users with relevant expertise. This ensures that translations for specific domains (medical, legal, technical) maintain high accuracy while the overall system maintains broad coverage through statistical translation for common topics.
Solution Approach 2:
The patent segments the translation task into different categories based on topic domain and difficulty level. The translation server divides requests into general translations (handled by statistical engines) and specialized translations (handled by expert users). This segmentation allows the system to maintain high coverage for general topics while ensuring accuracy for niche subjects through targeted user involvement.
3Productivity
If crowd-sourcing translation is implemented to increase participation, then translation rate improves, but system complexity increases
Solution Approach 1:
The patent makes the translation server multi-functional by integrating multiple capabilities into a single system: grammar-based translation, statistical translation, crowd-sourced translation, quality evaluation, and reward management. This universal platform handles diverse translation needs through unified interfaces and processing logic, improving translation rate while managing complexity through consolidation rather than proliferation of separate systems.
Solution Approach 2:
The patent implements self-service mechanisms where the system automatically evaluates translation quality, determines user rewards, and manages the crowd-sourcing process without requiring manual intervention. The translation server autonomously analyzes translation data, identifies high-quality contributions, calculates rewards based on predefined criteria, and distributes incentives. This automation reduces operational complexity while maintaining high translation productivity.
4Reliability
If user rewards are provided to incentivize participation, then translation quality improves, but operational cost increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting reward levels based on translation quality metrics and user performance. The system evaluates translation accuracy, fluency, and domain appropriateness, then scales rewards accordingly. This ensures that high-quality translations receive appropriate compensation while minimizing overall operational costs. The reward parameters are continuously optimized based on translation quality data and cost-effectiveness analysis.
Data Source
AI summary
Provided are a method by which a translation server collects translated content from at least one device, and a translation server therefor. The translation server may provide, to users using at least one device, a translation request category for participation in translation, and collect translated content from the users. The translation server may provide rewards to the users providing the translated content.