Adam Bittlingmayer


2022

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Quality Prediction
Adam Bittlingmayer | Boris Zubarev | Artur Aleksanyan
Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)

A growing share of machine translations are approved - untouched - by human translators in post-editing workflows. But they still cost time and money. Now companies are getting human post-editing quality faster and cheaper, by automatically approving the good machine translations - at human accuracy. The approach has evolved, from research papers on machine translation quality estimation, to adoption inside companies like Amazon, Facebook, Microsoft and VMWare, to self-serve cloud APIs like ModelFront. We’ll walk through the motivations, use cases, prerequisites, adopters, providers, integration and ROI.

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Machine Translate: Open resources and community
Cecilia OL Yalangozian | Vilém Zouhar | Adam Bittlingmayer
Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)

Machine Translate is a non-profit organization on a mission to make machine translation more accessible to more people. As the field of machine translation continues to grow, the project builds open resources and a community for developers, buyers and translators. The project is ruled by three values: quality, openness and accessibility. Content is open-source and welcomes open-contribution. It is kept up-to-date, and its information is presented in a clear and well-organized format. Machine Translate aims to be accessible to people from many backgrounds and, ultimately, also non-English speakers. The project covers everything about machine translation, from products to research, from development to theory, and from history to news. The topics are very diverse, and the writing is focused on concepts rather than on mathematical details.

2020

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A language comparison of Human Evaluation and Quality Estimation
Silvio Picinini | Adam Bittlingmayer
Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 2: User Track)