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Case Studies

Quantitative evaluations of Lilt

Lilt is designed to maximize translation productivity for individuals, teams, and businesses. It was born in an academic research lab, in which the standard of proof is empirical measurement. Read our case studies to find out how Lilt compares to your current translation platform.

SDL Trados

Added: 2 March 2016

Executive Summary: We compare human translation performance in Lilt to SDL Trados, a widely used computer-aided translation tool. Lilt generates suggestions via an adaptive machine translation system, whereas SDL Trados relies primarily on translation memory. Five in-house English-French translators worked with each tool for an hour. Client data for two genres was translated. For user interface data, subjects in Lilt translated 21.9% faster. The top throughput in Lilt was 39.5% higher than the top rate in Trados. This subject also achieved the highest throughput in the experiment: 1,367 source words per hour. For a hotel chain dataset, subjects in Lilt were 13.6% faster on average. Final translation quality is comparable in the two tools.

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Travel Portal

Added: 13 June 2016

Executive Summary: The combination of machine translation (MT) and online learning enables a new paradigm of machine assisted translation. Lilt learns from the experience, intelligence and insights of their human users, improving productivity by working in partnership, making suggestions and improving accuracy over time. The net result is that human reviewers produce far higher volumes of content, with nearly the same level of quality, for a fraction of the time and cost. Machine assistance can save customers up to one half (or more) of the price of traditional human translation services. Or, if you've been used to machine translation alone and have been unhappy with the results, watch your translation quality rise dramatically.

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