Introducing Machine Translation in the Translation Classroom : a Survey on Students' Attitudes and Perceptions

The translation sector is going under major changes that will undoubtedly be accentuated in the future owing to the development of automation and artificial intelligence, and more specifically, of machine translation. Technology also plays a crucial role in the translation process and has a significant impact on translation competence. Therefore, it is of utmost importance that translator programs incorporate new translation technology into their curriculums in order to ensure that students are made aware of their usefulness in order to fulfil industry employment needs. This piece of research strives at mapping how and what for translation students use MT, and what are their attitudes and perceptions towards its use. Findings of a qualitative analysis indicate that undergraduate students have a positive general attitude towards MT and its many advantages, whereas they show preoccupation when MT professional issues are addressed.El sector de la traducció està experimentant grans canvis que, sens dubte, s'accentuaran en el futur gràcies al desenvolupament de l'automatització i la intel·ligència artificial i, més concretament, a la traducció automàtica. La tecnologia també juga un paper crucial en el procés de traducció i té un impacte significatiu en la competència traductora. Per això, és importantíssim que els programes de traducció incorporin noves tecnologies per tal de garantir que els estudiants prenguin consciència de la seva utilitat a l'hora de satisfer les necessitats laborals del sector. Aquest treball prova de determinar com i per què els estudiants de traducció fan servir la TA, i quina és la conducta i la percepció respecte al seu ús. Els resultats d'una anàlisi qualitativa indiquen que els estudiants de grau tenen una actitud generalment positiva cap a la TA i els nombrosos avantatges que ofereix, però que es mostren preocupats quan aborden els problemes professionals associats.El sector de la traducción está experimentando grandes cambios que, sin duda alguna, se acentuarán en el futuro gracias al desarrollo de la automatización y la inteligencia artificial y, más concretamente, a la traducción automática. La tecnología también desempeña un papel crucial en el proceso de traducción y tiene un impacto significativo en la competencia traductora. Por eso, es importantísimo que los programas de traducción incorporen nuevas tecnologías para garantizar que los estudiantes sean conscientes de su utilidad a la hora de satisfacer las necesidades laborales del sector. Este trabajo intenta determinar cómo y por qué motivo los estudiantes de traducción utilizan la TA, y cuál es la conducta y la percepción respecto a su uso. Los resultados de un análisis cualitativo indican que los estudiantes de grado tienen una actitud generalmente positiva hacia la TA y sus numerosas ventajas, pero que se muestran preocupados cuando abordan los problemas profesionales asociados

The multilingual university website (MUW) genre ecology: content analysis and translation processes

A partir del análisis de contenidos de las webs universitarias españolas y de los procesos de traducción de los mismos, esta aportación pretende identificar los retos que la internacionalización ha supuesto para estas instituciones y las soluciones técnicas, organizativas y traductológicas que han aplicado hasta el momento para la gestión de sus contenidos multilingües, especialmente en el caso de las universidades de comunidades autónomas con dos lenguas oficiales. Aplicando técnicas de análisis de género textual se estudia la situación comunicativa de la web universitaria multilingüe (WUM), haciendo especial hincapié en los procesos de localización y traducción de sus contenidos. La noción de ecología de géneros, como conglomerado de géneros complejo, que funciona con esquemas de cognición distribuida y autoría compartida ha articulado el estudio empírico de las macroestructuras, los contenidos multilingües y las estrategias empleadas por cada universidad para traducir sus webs. El análisis realizado pone de manifiesto que los procesos de creación de contenidos multilingües requieren estrategias de actuación integrales, la definición de responsables únicos de la gestión, y del control de la calidad y la dotación de los recursos necesarios para ajustarse a las características de multifuncionalidad, dinamismo, interactividad y adaptabilidad que hemos identificado en las webs universitarias monolingües. Finalmente, se apuntan propuestas para mejorar los procesos de creación, gestión y control de los contenidos multilingües y se definen los perfiles de traductor especializado que requieren este tipo de webs institucionales.This article analyses the content of Spanish university websites and the processes involved in translating them, with the aim of identifying the challenges internationalisation poses for these institutions and the technical, organisational and translation-related solutions that have been adopted for managing their multilingual content, particularly in the case of universities in autonomous communities with two official languages. It examines the communicative situation of the multilingual university website (MUW) genre by applying textual genre analysis, with special emphasis on translation and localisation processes. The empirical study of the macrostructures, multilingual content and strategies used by each university to translate its website is articulated through the notion of a genre ecology, as a complex conglomerate of genres based on distributed cognition and shared authorship. The analysis shows that the processes involved in creating multilingual content require adopting comprehensive translation and localisation strategies, establishing sole decision-makers for translation management and quality control, and providing the necessary resources to ensure the multifunctionality, dynamicity, interactivity and adaptability we have identified in monolingual university websites. Finally, we offer suggestions for improving the creation, management and control of multilingual content and define the profiles of the specialised translators required for this type of institutional website

An investigation of English-Irish machine translation and associated resources

As an official language in both Ireland and the European Union (EU), there is a high demand for English-Irish (EN-GA) translation in public administration. The difficulty that translators currently face in meeting this demand leads to the need for reliable domain-specific user-driven EN-GA machine translation (MT). This landscape provides a timely opportunity to address some research questions surrounding MT for the EN-GA language pair. To this end, we assess the corpora available for training data-driven MT systems, including publicly-available data, data collected through EU-supported data collection efforts and web-crawling, showing that though Irish is a low-resource language it is possible to increase the corpora available through concerted data collection efforts. We investigate how increased corpora affect domain-specific (public administration) statistical MT (SMT) and neural MT (NMT) systems using automatic metrics. The effect that different SMT and NMT parameters have on these automatic values is also explored, using sentence-level metrics to identify specific areas where output differs greatly between MT systems and providing a linguistic analysis of each. With EN-GA SMT and NMT automatic evaluation scores showing inconclusive results, we investigate the usefulness of EN-GA hybrid MT through the use of monolingual data as a source of artificial data creation via backtranslation. We evaluate these results using automatic metrics and linguistic analysis. Although results indicate that the addition of artificial data did not have a positive impact on EN-GA MT, repeated experiments involving Scottish Gaelic show that the method holds promise, given suitable conditions. Finally, given that the intended use-case of EN-GA MT is in the workflow of a professional translator, we conduct an in-depth human evaluation study for EN-GA SMT and NMT, providing a human-derived assessment of EN-GA MT quality and comparison of EN-GA SMT and NMT. We include a survey of translator opinions and recommendations surrounding EN-GA SMT and NMT as well as an analysis of data gathered through the post-editing of MT output. We compare these results to those generated automatically and provide recommendations for future work on EN-GA MT, in particular with regards to its use in a professional translation workflow within public administration

Low-Resource Unsupervised NMT:Diagnosing the Problem and Providing a Linguistically Motivated Solution

Unsupervised Machine Translation hasbeen advancing our ability to translatewithout parallel data, but state-of-the-artmethods assume an abundance of mono-lingual data. This paper investigates thescenario where monolingual data is lim-ited as well, finding that current unsuper-vised methods suffer in performance un-der this stricter setting. We find that theperformance loss originates from the poorquality of the pretrained monolingual em-beddings, and we propose using linguis-tic information in the embedding train-ing scheme. To support this, we look attwo linguistic features that may help im-prove alignment quality: dependency in-formation and sub-word information. Us-ing dependency-based embeddings resultsin a complementary word representationwhich offers a boost in performance ofaround 1.5 BLEU points compared to stan-dardWORD2VECwhen monolingual datais limited to 1 million sentences per lan-guage. We also find that the inclusion ofsub-word information is crucial to improv-ing the quality of the embedding

Google Translate: A helpful aide? A mixed method sequential explanatory study on the usage and effects of Google Translate in three Norwegian EFL classes

This thesis investigates how learners in Norway use Google Translate to aid them in EFL writing as well as how the usage of Google Translate affects the quality of the texts they write. A mixed method study was used in three Norwegian EFL classes situated in the same school along with learner stimulated recall interviews and teacher interviews. The aim of the study was to determine how effective Google Translate is at helping Norwegian learners at different performance levels and to see how dependant these learners are on Google Translate to help them in EFL writing. Two writing sessions were conducted to gather data on learners’ usage of Google Translate and determine whether the translation tool had any effect on the quality of their written products. The first writing session consisted of learners using dictionaries to help them translate from Norwegian to English, and in total, 33 learners participated in this writing session. In the second writing session, learners were encouraged to use Google Translate as they would normally to help in EFL writing, and 33 learners participated in this writing session, 22 of whom used Google Translate. By comparing vocabulary, syntax errors, subject-verbal concord errors, essay length, and spelling mistakes between the texts from the two writing sessions of learners who used Google Translate in the second writing session, comments could be made on the effectiveness Google Translate has on the quality of learners’ texts. A separate analysis was conducted of how Google Translate was being used by learners in the second writing session, i.e. how many times Google Translate was used to translate words, phrases, sentences, entire texts or for other purposes. Based on the analysis comparing two sets of 22 learners’ screen recorded videos and the learners’ writing along with information from stimulated recall interviews and teacher interviews, it seems that learners’ current usage of Google Translate does not affect the quality of their written product in a positive nor negative way, except for syntax related errors which lowered for all learner groups from the first to the second writing session. Google Translate mostly serves as a quicker alternative to dictionaries as it provides translations at a much fast speed compared to dictionaries. Further, learners mostly use Google Translate to aid in the translation of words and phrases, rarely using it to translate whole sentences or longer texts. However, there is a disparity between lower performing learners, average performing learners, and higher performing learners in how much they use the tool. Furthermore, there is a lack of training given to learners and teachers on how to use Google Translate as an efficient translation tool. Both learners and teachers that participated in the study reported a lack of training received on proper usage of the tool and reviewing 31 screen recorded videos from the second writing session, it was clear that learners lacked knowledge of the many capabilities the tool has to offer. There has previously been concern amongst teachers that Google Translate hinders learners in learning English as the translation tool produces incorrect output or that learners use the tool to translate large amounts of text. However, statements from teacher interviews reveal that these teachers seem to have become more acceptant of the translator being used in their class. Previous studies also reveal that Google Translate has reached the point where it has the capability of providing output equivalent to the minimum level of accuracy required for university entrance, thereby providing output better than what most learners in primary school could produce themselves (Mundt & Groves, 2015; Stapleton & Leung, 2019). Finally, based on the analysis of 64 screen recordings, the author of this thesis argues that Google Docs and other word processors should be a greater concern for teachers than Google Translate and other tools that aid in translation. This is due to a substantial number of learners who participated in the study being heavily dependent on the grammatical and spelling correction tools that the software provides, making it difficult for teachers to assess whether learners know various grammatical rules and possess the ability to apply these rules in written texts

Proceedings of the 17th Annual Conference of the European Association for Machine Translation

Proceedings of the 17th Annual Conference of the European Association for Machine Translation (EAMT