In this course you will:

- understand the principles behind how MT systems work, covering rule-based, statistical and hybrid systems
- learn how to plan the preparation of the resources required to build MT systems using well-established open-source development platforms
- familiarize yourself with the key variables to consider when deciding if/how/why you could use MT, depending on your own language pairs, specialization areas and clients

Description

This course aimed at translators, LSPs and project managers debunks the myths about machine translation (MT) and explains the challenges involved in setting up customized MT systems. Participants are guided through the key steps in the process of successfully integrating MT into their translation workflows, to reduce turnaround times and offer competitive rates without sacrificing the quality of the final product.

This course explains how translators, LSPs and project managers can turn machine translation (MT) from a dreaded foe into a powerful ally. By learning the strengths and weaknesses of this much talked about but little understood technology, you will be able to assess if, why and how you could use MT as part of your business, depending on your language pairs, specialization areas and type of clients.
The main approaches to MT system design are presented in a non-technical accessible way, including the well-established rule-based architectures and the increasingly popular statistical and hybrid approaches, which rely on parallel corpora and translation memory databases. You will be alerted to the key factors to consider when assessing the actual potential and the limitations of MT, balancing the pros and cons of introducing it into your own translation workflows, especially with regard to the initial investment and its expected return.

Upload Date

May 13, 2015

Trainer Bio

Federico Gaspari - Federico Gaspari is associate professor of English linguistics and translation studies at the University for Foreigners ‘Dante Alighieri’ of Reggio Calabria (Italy), where he is coordinator of the two-year Masters-level Programme in ‘Interpreting and Cross-Cultural Mediation Studies’ and director of the ‘Dante Alighieri’ University Language Centre. Since 2010 he has been a visiting postdoctoral researcher at Dublin City University (Ireland), where he has worked on 4 European research projects focusing on machine translation evaluation (CoSyne, QTLaunchPad, MLi and currently TraMOOC). After graduating in translation studies from the University of Bologna at Forlì (Italy) he completed an MSc and a PhD in machine translation at the University of Manchester (UK) and has held lecturing and research positions at the Universities of Manchester, Salford, Bologna at Forlì and Macerata. His teaching and research interests include translation technologies (with a special focus on machine translation, post-editing and translation quality evaluation), technical and specialised translation, translation theory, corpus linguistics, corpus-based translation studies and English linguistics. He has published widely on these subjects and is a regular speaker at international conferences on these topics.

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Carlos Marques

over 3 years ago

Very good tips on how to evaluate if the MT you are using serves as an efficient tool for the material you are translating.

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