69753 - Machine Translation and Post Editing (CL1)

Course Unit Page

  • Teacher Claudia Lecci

  • Credits 5

  • Teaching Mode Traditional lectures

  • Language Italian

  • Campus of Forli

  • Degree Programme Second cycle degree programme (LM) in SPECIALISED TRANSLATION (cod. 8061)

Academic Year 2015/2016

Learning outcomes

The student should: be familiar with the theoretical principles underpinning the development and use of machine translation systems; be able to use independently the main relevant computer-based and online tools; have the specialised technical skills to carry out various types of post-editing (revision) of machine-translated texts belonging to a variety of fields, based on a range of needs. The student can design, manage and evaluate complex projects involving machine translation and post-editing which require the participation of a number of people with different skill sets, complying with professional standards. He/she is able to autonomously acquire more advanced translation-related technological knowledge and skills and to use them in a variety of fields.

Course contents

The course takes place in the second semester and consists of two closely connected and interdependent parts, one devoted to machine translation (MT), and the other to post-editing (PE).

In the first part, which is closely linked to the second one, the key theoretical principles of MT are introduced, starting with a brief overview of the major milestones in its history, from the 1940's up to the latest developments. The main architectures of MT systems are presented, from the traditional rule-based ones to the most recent statistical approaches which use parallel corpora. An in-depth look at linguistic and translation phenomena which are particularly challenging for MT processing helps to raise the students' awareness, so that they can evaluate critically and objectively the potential as well as the limitations of this technology. Complex topics concerning the evaluation of MT quality and the effectiveness of MT systems are discussed, presenting both standard human evaluation methods (e.g. fluency and adequacy judgements) and state-of-the-art automatic evaluation metrics, such as BLEU, NIST, METEOR and TER. This is followed by an exploration of related issues, such as the evaluation of the time and effort required to introduce MT into translation workflows, MT quality estimation and prediction, customisation and fine-tuning of statistical MT systems via iterative processes. On the basis of the explanations of the theoretical concepts and of the key relevant notions, these topics are also covered with practical exercises and reflective activities concerning a range of scenarios in which MT can be deployed. This helps the students to systematically consider its pros and cons, simulating the professional environments of companies and institutions that use MT software on a regular basis.

The second part, which is closely linked to the first one, focuses in particular on the PE of texts translated with MT systems, comparing this operation with other existing strategies that help make automatically translated texts useful and accessible. These include pre-editing, controlled language for the drafting of restricted input and the approach based on ‘sublanguage' for certain specialized domains, in particular when a single source text has to be automatically translated into a range of target languages. With regard to PE, different ways of intervention (minimum, medium, complete, etc.) are discussed in relation to variables such as the specific conditions of the revision task, the post-editor profile (bilingual, monolingual of the target language, expert in the field, etc.), the type of translation, the publication venue and the circulation methods planned for the revised target text, its potential readers and users, etc. Various PE strategies allowing for the improvement of the raw output provided by MT systems are also presented. The aim of these strategies is to obtain a target text which meets the specific requirements of the translation context, e.g. intervening with the minimum number of possible changes or trying to achieve high (publishable) quality for the final text, based on the circumstances. Issues relating to the quality and effectiveness of post-editing are considered according to the time gains it allows, depending on the linguistic standard required for a particular target text, which is functional to its planned use. Finally, the students are guided to explore the connections between the use of MT with post-editing and the work of professional translators who normally use computer-assisted translation tools, in particular translation memories.


Arnold, D.J., L. Balkan, S. Meijer, R. Lee Humphreys & L. Sadler (1994)Machine Translation: An Introductory Guide. London: Blackwells-NCC. Available online: www.essex.ac.uk/linguistics/external/clmt/MTbook

Bersani Berselli, G. (ed.) (2011) Usare la Traduzione Automatica. Bologna: CLUEB.

Hutchins, John (1986) Machine Translation: Past, Present, Future. Chichester: Ellis Horwood. Available online: www.hutchinsweb.me.uk/PPF-TOC.htm

Hutchins, W.J. & H.L. Somers (1992) An Introduction to Machine Translation. London: Academic Press. Available online: www.hutchinsweb.me.uk/IntroMT-TOC.htm

Hutchins, W.J. & H.L. Somers (1995) Introduccion a la Traduccion Automatica. Madrid: Visor [Spanish translation of Hutchins & Somers (1992)].

Loffler-Laurian, Anne Marie (1996) La Traduction Automatique. Vileneuve d'Ascq: Presses Universitaires du Septentrion.

Quah, C.K. (2006) Translation and Technology. Basingstoke: Palgrave MacMillan.

Somers, Harold (ed.) (2003) Computers and Translation: A Translator's Guide. Amsterdam and Philadelphia: John Benjamins.

Guerberof, Ana (2009) “Productivity and Quality in the Post–editing of Outputs from Translation Memories and Machine Translation”. Localisation Focus 7(1): 11-21. Available online: http://isg.urv.es/library/papers/2009_Ana_Guerberof_Vol_7-11.pdf

NIST (2007) Post Editing Guidelines for GALE Machine Translation Evaluation. Available online: http://projects.ldc.upenn.edu/gale/Translation/Editors/GALEpostedit_guidelines-3.0.2.pdf

O'Brien, Sharon (2002) “Teaching Post-editing: A Proposal for Course Content”. Proceedings of the 6th EAMT Workshop on “Teaching Machine Translation”. EAMT/BCS, UMIST, Manchester, UK. 99-106. Available online: http://mt-archive.info/EAMT-2002-OBrien.pdf

Poulis, Alexandros and David Kolovratnik (2012) "To Post-edit or not to Post-edit? Estimating the Benefits of MT Post-editing for a European Organization". Proceedings of the AMTA 2012 Workshop on Post-editing Technology and Practice (WPTP 2012). The Tenth Biennial Conference of the Association for Machine Translation in the Americas, October 28-November 1 2012, San Diego, CA, USA. Available online: http://amta2012.amtaweb.org/AMTA2012Files/html/9/9_paper.pdf

Teaching methods

Apart from covering the theoretical aspects, the lectures are held using a participative approach and take the form of a workshop. Theoretical aspects are presented by the lecturer and explored in more depth independently by the students through readings assigned during the course. The applied part consists of hands-on practice in the lab led by the lecturer and take-home exercises to be done autonomously or in groups by the students.

Assessment methods

Assessment will be based on a written test with theoretical and practical components lasting approximately two hours and focusing on the theoretical principles covered in class as well as their applications in professional translation, with a critical analysis of the relevant processes and potential.

Teaching tools

Lessons are held in a computer lab with Internet connection and beamer. Students will also use (online) translation software, tools and resources.

Teaching materials are made available on the Moodle platform.

Office hours

See the website of Claudia Lecci