Automate language quality review for better translation outputs
One of the biggest challenges in deploying Custom Machine Translation is measuring translation quality.
How can you develop a formalised mechanism to determine translation quality and use this to improve translation quality during the engine training and development cycle?
More importantly, how can you formalise the measurement of translation quality that delivers usable metrics that drive a deeper understanding of how your engine will perform in production?
Only KantanLQR provides the functionality to manage:
Language Quality Review: Work with detailed segment level quality metrics that determine how accurately your engine translates your content.
Distributed Workflow: Create a Language Quality Review Project that distributes translation test-sets to reviewers using fully automated workflows - avoiding spreadsheet proliferation!
Key Performance Indicators: Use the KantanLQR built-in KPIs to formalise translation quality measurements projects for your engines. These KPIs include Translation Adequacy, Fluency, Style, Syntax and Grammar.
Customise Test Plans: Customise projects by creating a customise set of KPIs to help optimise language quality review workflows.
Real Time Data Visualisation: Use graphic visualisation technology to track, analyse and manage translation quality metrics in real time.
Productivity: Calculate and compare translation productivity across all your KantanMT engines.
Reliable Industry Standards: Use the KantanLQR built-in KPIs to create comparable MQM (Multidimensional Quality Metrics) projects that measure translation quality based on exacting industry standards.
Only KantanLQR provides a fully automated, distributive process for measuring, tracking and analysing translation quality.
Here's what our members are saying:
We are finding that KantanMT [is] an efficient and positive solution.
Mohamed Hammoud, Manager, ChromeData
Since signing up with KantanMT, we have been able to take on more work and increase capacity.