Case Study Summary Challenges Viber, an instant messaging and Voice over IP (VoIP) app for smartphones, has implemented Machine Translation as an integrated process step within their translation workflow and is taking advantage of all available technologies. Establishing engine quality feedback loop. Customized training for project teams. Ongoing post-editor productivity testing. Link Translation was trusted to perform comprehension evaluation of the MT System aimed to provide reports to the client about the quality and productivity of their system, and to support training procedures for translators and proofreaders. Evaluation of MT output via human assessment and scoring.

Solutions The translation teams selected for this project were chosen for their expertise in the Information Technology industry. They are qualified and experienced translators, who also offered qualifications and practical experience working with Machine Translation Post Editing. Formal evaluations of technology are supported with a web-based evaluation utility. The variables studied are "intelligibility" and "fidelity". Intelligibility is a measure of how "understandable" the sentence was, and was measured on a scale of 1–9.

Fidelity was a measure of how much information the translated sentence retained compared to the original, and was measured on a scale of 0–9. Benefits Viber is taking advantage of Machine Translation technologies and Link Translation is continuously helping Viber to improve their system, providing highly reliable assessments of their machine translation technology. This way, the client is able to produce training material for their reviewers and guarantee a high quality output, saving costs and time. Each point on the scale is associated with a textual description. For example, 3 on the intelligibility scale can be described as "Generally unintelligible; it tends to read like nonsense but, with a considerable amount of reflection and study, one can at least hypothesize the idea intended by the sentence". Reports are provided to the client’s technical team to work on direct improvements to the system based on these results and create training material for external Post-Editors.

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