Author Archives: riilp

Technologies for Translation and Interpreting: Challenges and Latest Developments

Dr Konstantinos Chatzitheodorou, Strategic Agenda

Using technology in the translation quality assessment

19 March 2021

Abstract: The process of determining translation quality is subjective and relies on human judgments. Translation quality is affected by a variety of factors that are weighted differently in each translation task and can be viewed from different perspectives. Hence, it is not equally measurable or assessable (Almutairi, 2018). The talk will emphasize the importance of measuring translation quality and how it can be accomplished. The first part of the presentation will introduce different frameworks and software used in the process of translation evaluation focusing on error classification schemes available in both professional and academic word. The second part of the presentation will include a demonstration of Træval which is a Software-as-a-Service (SaaS) that allows humans to evaluate translation outputs. By providing an easy-to-use graphical interface, it assists researchers and users in this process. In particular, three different scenarios will be presented using the Dynamic Quality Framework – Multidimensional Quality Metrics (DQF-MQM) error typology (Lommel, 2018): an evaluation of a simple translation task, an evaluation task focused on the assessment of multi-word units, and, finally, a technology-aided evaluation task aiming to reduce subjectivity.

Dr Konstantinos Chatzitheodorou is a postdoctoral researcher at the Department of Foreign Languages, Translation and Interpreting, Ionian University. He received his PhD in Applied Translation Studies and Computational Linguistics from the Aristotle University of Thessaloniki. He holds a BA in Italian Language and Literature from the School of Italian Language and Literature, Aristotle University of Thessaloniki and an MSc in Informatics in Humanities from the Department of Informatics, Ionian University. He is also ECQA Certified Terminology Manager – Engineering. He is employed as a Computational Linguist in the private sector, assisting organizations to use language data to gain strategic insights. He has also worked as a Machine Translation Expert and Terminologist at the European Parliament – Directorate-General for Translation in Luxembourg. Over the years, Konstantinos has also contributed as a researcher to several EU projects in areas of his interest.

References

Almutairi, M.O.L., 2018. The objectivity of the two main academic approaches of translation quality assessment: arab spring presidential speeches as a case study (Doctoral dissertation, University of Leicester).

Chatzitheodorou, K. and Chatzistamatis, S, 2013. COSTA MT evaluation tool: An open toolkit for human machine translation evaluation. The Prague Bulletin of Mathematical Linguistics, 100(2013), pp.83-89.

Lommel, A., 2018. Metrics for translation quality assessment: a case for standardising error typologies. In Translation Quality Assessment (pp. 109-127). Springer, Cham.

Secară, A., 2005, March. Translation evaluation: A state of the art survey. In Proceedings of the eCoLoRe/MeLLANGE workshop, Leeds (Vol. 39, p. 44).

Technologies for Translation and Interpreting: Challenges and Latest Developments

Fardad Zabetian (CEO of KUDO)

Multilingual communication is evolving and how KUDO is part of the evolution.

12 March 2021

Abstract:

During this 45min talk, Fardad will share his journey in the world of multilingual meetings in the last 20 years, how he sees the market is evolving, the new opportunities for businesses and  interpreters . He will cover the new KUDO Marketplace and how this new system going to remove friction points in accessing interpreting services. He will cover the challenges in the new uses cases such as short notice for assignments and how technology and AI will assist interpreters to prepare in shorter time.

Bio:

A visionary entrepreneur, Fardad has founded and placed two companies among the fastest growing business in America. He has also expanded to key markets over Europe and Asia. Fardad is no stranger to big challenges. In 2012, he was part of the design and roll-out a complete makeover of the United Nation’s meeting facilities, including the general assembly hall in New York. He has also played a key supporting role as a high-end equipment provider to various iterations of the IMF/ World Bank Annual Meetings and several European Institutions. in 2016, Fardad co-founded AVAtronics, a Swiss technology company focusing on active noise canceling technology. In 2017, Fardad founded KUDO, where he now takes the meeting experience beyond the room to connect businesses and people in true border-less fashion, without language or geographic constraints.

Natural Language Processing

Dr Sanja Štajner, ReadableAI

Automatic Assessment of Conceptual Text Complexity Using Knowledge Graphs

8 March 2021

Abstract

In this talk,  I will present in depth the ideas behind our position paper on “Automatic Assessment of Conceptual Text Complexity Using Knowledge Graphs“ that was published at COLING 2018. First, I will define what we consider under conceptual complexity of texts, what is its role in text understanding, and why it is important to have an automatic way of assessing it. Next, I will introduce in details a number of graph-based measures on a large knowledge base that we proposed as features for automatic assessment of conceptual complexity, and talk about the experimental setup and results. By using a high-quality language learners corpus for English, we showed that graph-based measures of individual text concepts, as well as the way they relate to each other in the knowledge graph, have a high discriminative power when distinguishing between two versions of the same text. Furthermore, when used as features in a binary classification task aiming to choose the simpler of two versions of the same text, our measures achieved high performance even in a default setup.

Bio

Sanja Štajner is currently Chief Research Scientist at ReadableAI and Senior Research Scientist at Symanto. She has obtained her PhD in Computer Science on the topic of Data-Driven Text Simplification from University of Wolverhampton (UK), and holds a multiple Masters degree in Natural Language Processing and Human Language Technologies.

Sanja is one of the most cited researches in the field of Text Simplification, with over 80 peer-reviewed articles in international journals and top-tier NLP/AI conferences, holds several awards at international conferences for her work in text simplification, and is regularly invited as a speaker across academia and industry. She has served as an area chair, reviewer, and member of the scientific committee in many top-tier international NLP/AI conferences, and was the lead organizer of two shared tasks in the field of text simplification (QATS 2016 and CWI 2018).

Technologies for Translation and Interpreting: Challenges and Latest Developments

Dr Arda Tezcan, Ghent University

Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation

8 January 2021

Abstract:

Even though Machine Translation (MT) quality may have increased considerably over the past years, most notably with advances in the field of Neural Machine Translation (NMT), Translation Memories (TMs) still offer some advantages over MT systems. They are not only able to translate previously seen sentences ‘perfectly’ but they also offer ‘near perfect’ translation quality when highly similar source sentences are retrieved from

the TM. As a result, in Computer-Assisted Translation (CAT) workflows, the MT system is often used as a back-off mechanism when the TM fails to retrieve high fuzzy matches above a certain threshold, even though it has been shown that this basic integration method is not always the most optimal TM-MT combination strategy.

We present a simple yet powerful data augmentation method for boosting Neural Machine Translation (NMT) performance by leveraging information retrieved from a Translation Memory (TM). Tests on the DGT-TM data set for multiple language pairs show consistent and substantial improvements over a range of baseline systems. The results suggest that this method is promising for any translation environment in which a sizeable TM is available and a certain amount of repetition across translations is to be expected, especially considering its ease of implementation.    

Technologies for Translation and Interpreting: Challenges and Latest Developments

Prof Lynne Bowker, School of Translation & Interpretation, University of Ottawa

Machine translation literacy in the context of non-professional translation

18 December 2020

We recently passed the 70th anniversary of Weaver’s Memorandum (1949), which is widely acknowledged as having launched machine translation (MT) research. A lot has happened in that 70-year period, including the introduction of free, online machine translation accessible to anyone with an internet connection. Through university-based translator education programs and professional development opportunities offered by professional translators associations, language professionals have numerous opportunities to learn more about how to interact effectively with MT tools. But these tools are no longer solely in the hands of language professionals; they are also “in the wild”. How and why are non-professional users employing MT? What do they need to be aware of to use it effectively? What support is available to non-professional users of MT? Why should developers care about non-professional users? In this talk, we will explore the notion of “machine translation literacy”, examine some of the needs of non-professional MT users, consider the social responsibility of translators toward non-professional users, and discuss the results of two different efforts to deliver MT literacy training to non-professional users (one as part of a workshop offered through a university library, and one as part of a first-year university course on translation for non-language professionals).

Bio-sketch

Lynne Bowker is a certified (French-English) translator and holds a PhD in Language Engineering from the University of Manchester Institute of Science and Technology (UK). She is Full Professor at the School of Translation and Interpretation at the University of Ottawa (Canada), with a cross-appointment to the School of Information Studies. She is the author of Computer-Aided Translation Technology (University of Ottawa Press, 2002) and co-author of both Working with Specialized Language: A Practical Guide to Using Corpora (Routledge, 2002) and Machine Translation and Global Research (Emerald, 2019). In 2020, she was elected to the Royal Society of Canada in recognition of her contributions to research in translation technologies.

Technologies for Translation and Interpreting: Challenges and Latest Developments

Andrzej Zydroń, XTM International (CTO)

AI and Language Technology: De-demonizing AI

16 December 2020

AI gets a lot of attention generally due to the stunning results that can be achieved, in fields such as medicine, automotive technology, diagnostic systems and of course translation. AI systems can seemingly outperform human beings in a wide range of tasks, from playing Chess, Go or even poker, to face and voice recognition. What is often lacking though, is a more realistic understanding of what intelligence is and the actual limitations that exist given the computing tools at our disposal.

The reality is much more prosaic: most of the mathematical basis of what is termed AI is not complicated and generally rooted in early 18th century mathematics, namely work done by Euler and Bayes.

Although some of the achievements of AI based systems may seem phenomenal, they are achieved through processing of gigantic amounts of data which would normally be beyond human capability. The presentation looks at what actually constitutes AI and how it relates to general human intelligence and what implications this has for the translation industry in general.

Andrzej Zydroń MBCS CITP

CTO and co-founder @ XTM International, Andrzej Zydroń is one of the leading IT experts on Localization and related Open Standards. Zydroń sits/has sat on the following Open Standard Technical Committees:

  1. LISA OSCAR GMX
  2. LISA OSCAR xml:tm
  3. LISA OSCAR TBX
  4. W3C ITS
  5. OASIS XLIFF
  6. OASIS Translation Web Services
  7. OASIS DITA Translation
  8. OASIS OAXAL
  9. ETSI LIS
  10.  DITA Localization
  11. Interoperability Now!
  12. Linport

Zydroń has been responsible for the architecture of the essential word and character count GMX-V (Global Information Management Metrics eXchange) standard, as well as the revolutionary xml:tm standard which will change the way in which we view and use translation memory. Zydroń is also head of the OASIS OAXAL (Open Architecture for XML Authoring and Localization technical committee.

Zydroń has worked in IT since 1976 and has been responsible for major successful projects at Xerox, SDL, Oxford University Press, Ford of Europe, DocZone and Lingo24.