The Moses Decoder is one of many open source components that help to make Slate™ possible. These instructional videos cover advanced concepts. Learn the academic fundamentals of statistical machine translation (SMT). Then watch the Slate videos to compare how Slate automates meticulous Moses tasks.
This screencast uses the Moses SMT system trained earlier to bulk translate a set of test data for which the BLEU score is calculated based on the available reference translations. In the second part of the screencast the trained Moses system is optimized for lower memory use and translation speed.
This presentation provides a contrast between automated evaluation and human evaluation of machine translation output. We explain how automated evaluation is useful in the development of MT systems and then go on to describe the automated metrics BLEU, TER, GTM and Meteor.
This presentation describes different strategies of human evaluation for MT output, how to use them for error analysis for the improvement of MT systems and how to apply them in an industry setting to achieve the desired project goals.
Translation of complex document formats is common in the language industry. This presentation explains how the Okapi Framework and the Moses for Localization open source project can be used to translate these file formats using machine translation. We also address how to translate web pages with Moses and how to integrate Moses MT systems into content management or translation workflows using available web APIs.
Previous demos showed how to translated single sentences and collections of sentences. This demo shows how to translate complex document formats using a combination of the Okapi Framework, Moses for Localization and Moses. The second half demonstrates the use of two web APIs that are available for Moses – the Moses Server XML-RPC API and the Moses for Localization REST API.