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LILT Analytics V2

LILT Analytics Overview

LILT Analytics V2 provides comprehensive insights into the performance and accuracy of AI translations over time. This article will guide you through the various metrics and visualizations available in LILT Analytics.

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Overview Page

AI Accuracy

AI Accuracy provides insights into the accuracy of AI suggestions across 3 models and workflows: Unadapted AI (pure MT), Adapted AI (LILT Contextual AI model with Data Sources), and Verified Translation (human in the loop).

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AI Accuracy

  • Unadapted AI (Green): Represents the raw AI translation accuracy without any modifications.

  • Adapted AI (Blue): Shows the AI translation accuracy after adjustments and improvements from Fine Tuned Data Sources.

  • Verified Translation (Red): Indicates the accuracy of translations verified by human translators.

AI Accuracy Per Language Pair

The "AI Accuracy Per Language Pair" table provides detailed accuracy metrics for different language pairs over several months. This table helps identify which language pairs have higher or lower accuracy and track their performance trends.

Quality Metrics

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Quality Overview

Average Quality Score

The average quality score is based on a MQM quality framework and showcases the resulting scores here for both overall and MoM for individual language pairs.

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Errors per 1k words + Model Size

Errors Per 1k Words

The "Errors Per 1k Words Over Time" table categorizes errors into major, neutral, and minor types, helping to understand the common issues in translations. This is a breakdown of the MQM framework.

Model Size Over Time

The "Model Size Over Time" chart tracks the growth of the LILT AI model in terms of the number of words from January 2024 to June 2024. This metric shows how the AI model expands its knowledge base to improve translation accuracy.

Connector Jobs

The "Connector Jobs" table provides insights into the performance of various connectors, including their AI accuracy, volume, and submission errors. This information helps identify which connectors perform well and which may need improvements.

On-Time Delivery (OTD) and Words Per Hour (WPH)

  • OTD Over Time: Tracks the on-time delivery performance of translations over several months.

  • WPH Over Time: Monitors the words processed per hour, indicating the efficiency of the translation process.

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OTD and WPH metrics

OTD Per Language Pair

The "OTD Per Language Pair" table provides a breakdown of on-time delivery performance for different language pairs.

Conclusion

LILT Analytics offers a detailed view of translation accuracy, quality, and efficiency. By monitoring these metrics, users can identify areas for improvement, track progress over time, and ensure high-quality translations across various language pairs and connectors.

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