Kyle Paice

Posts by Kyle Paice:

Case Study: SDL Trados

Abstract: 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. […]

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2017 Machine Translation Quality Evaluation Addendum

This post is an addendum to our original post on 1/10/2017 entitled 2017 Machine Translation Quality Evaluation.

Experimental Design

We evaluate all machine translation systems for English-French and English-German. We report case-insensitive BLEU-4 [2], which is computed by the mteval scoring script from the Stanford […]

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Machine Translation Tools: Comprehensive BLEU Evaluation

The language services industry offers an intimidating array of machine translation options. To help you separate the truly innovative from the middle-dwellers, your pals here at Lilt set out to provide reproducible and unbiased evaluations of these options using public data sets and a rigorous methodology.

This evaluation is […]

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Morphing into the Promised Land

Guest post by Jost Zetzsche, originally published in Issue 16–12–268 of The Tool Box Journal.

 

Some of you know that I’ve been very interested in morphology. No, let me put that differently: I’ve been very frustrated that the translation environment tools we use don’t offer morphology. There are some exceptions — such as […]

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