THE STRATEGY OF DEVELOPING STUDENTS’ TRANSLATION SKILL THROUGH ANALYSIS TECHNIQUE OF MACHINE ASSISTED TRANSLATION (MAT) AND MANUAL TRANSLATION (MT)

Machine-Assisted Translation (MAT) is a sophisticated intellectual technology made by man as a means of instant translation. One of them is Google Translate. This research is a case study with a qualitative approach. This research is to find out the following questions. 1) about the implementation of teaching techniques by applying MAT and MT analysis in the Translation course; 2) about perceptions of students of learning techniques using MAT and MT analysis in the Translation course; and 3) about the strategy of students in doing MT. The research data collection techniques were obtained from classroom observations, interviews with lecturers on Translation subjects, and documents from the results of student translations. All of these were conducted online because Covid had not passed. The object of his research was a lecturer in the Translation subject and 10 students from the Translation class. The data analysis technique used the data credibility test through the triangulation of techniques and sources. The result and the finding of this study are that the lecturer implements the MAT and MT analysis in the translation course with various stages. Meanwhile, students have the perception that the translation technique with the MAT and MT analysis strategy is very beneficial for their translation results. The strategy carried out by students in translating is using MAT and MT analysis in addition to using special translation techniques

Exploring the Differences between Human and Machine Translation

Chinese second language learners of English often use Machine Translators (MT) to translate personal and professional messages from their first language to English. MT’s are not perfect and have historically create messages that lack the cohesiveness and authenticity of natively written English. This paper describes our attempts to quantify the differences between human translation and machine translation in a specific scope with that hope that both MTs and post editing systems can be benefited through awareness of common error and differences between human and machine translations. In order to achieve this we implemented existing algorithms designed to identify common errors in machine translated sentences and a sentence dependency analysis to identify key differences between the translations. With this information further work targeting the underlying causes of these errors can be developed

Natural emotion vocabularies and borderline personality disorder

Background Emotion dysregulation is a characteristic central to borderline personality disorder (BPD). Valuably, verbal behaviour can provide a unique perspective for studying emotion dysregulation in BPD, with recent research suggesting that the varieties of emotion words one actively uses (i.e., active emotion vocabularies [EVs]) reflect habitual experience and potential dysregulation therein. Accordingly, the present research examined associations between BPD and active EVs across two studies. Methods Study 1 (N = 530) comprised a large non-clinical sample recruited from online forums, whereby BPD traits were measured via self-report. Study 2 (N = 64 couples) consisted of mixed-gender romantic couples in which the woman had a BPD diagnosis, as well as a control group of couples. In both studies, participants’ verbal behaviours were analysed to calculate their active EVs. Results Results from both studies revealed BPD to be associated with larger negative EV (i.e., using a broad variation of unique negative emotion words), which remained robust when controlling for general vocabulary size and negative affect word frequency in Study 2. The association between BPD and negative EV was insensitive to context. Limitations Limitations of this research include: 1) the absence of a clinical control group; 2) typical constraints surrounding word-counting approaches; and 3) the cross-sectional design (causality cannot be inferred). Conclusions Our findings contribute to BPD theory as well as the broader language and emotion literature. Importantly, these findings provide new insight into how individuals manifesting BPD attend to and represent their emotional experiences, which could be used to inform clinical practice

Analysing Google Translate: Detection of mistakes by L2 students as a tool with didactic potential

Resumen.- Si hacemos un estudio diacrónico del papel que ha tenido la traducción en la comunicación entre culturas y civilizaciones a lo largo de la historia, nos encontraremos con que, desde principios del siglo XXI, se cuenta con una útil y omnipresente herramienta de los traductores automáticos. De entre todos ellos, destaca Google Translate, como un popular instrumento; pero perfectible. El presente estudio tiene en cuenta su amplio margen de mejora, atiende a las fortalezas y debilidades de dicha herramienta detallando la tipología de errores más frecuentes, partiendo de una cuidada y variada selección de textos, en función de los diferentes registros y tipología, y clasificados en función de su dificultad, estableciendo tres grupos. A partir de ese primer corpus, se hace una segunda selección encaminada a proponer esos textos a alumnos de español L1 aprendices de inglés como L2 con el fin de evaluar su nivel de detección de estos errores. Así, la parte teórica viene acompañada de un estudio pormenorizado de los errores que el traductor comete a partir del corpus inicial de textos y de un estudio de campo, llevado a cabo en abril de 2017 en la Escuela de Idiomas, que evidencia las implicaciones y repercusiones didácticas que el análisis de textos incorrectamente traducidos puede tener en el aula. Abstract.- If we do a diachronic study about the role translation has had in the communication between different cultures and civilizations throughout history, we find that, from the beginning of the XXI century, machine translation devices have become useful and omnipresent tools. Among all of them, Google Translate positions itself as a widely-used gadget, but it still perfectible. The present study considers its large scope for improvement, reflects on the strengths and weaknesses of the tool outlining the most frequent mistake typologies. To do so, there is a meticulous and varied selection of texts composed of different registers and typologies which are arranged in three groups according to their difficulty. From this first corpus, there is a second selection aimed at introducing these texts to L1 Spanish students learning English as an L2 in order to assess their capacity to detect these mistakes. Thus, the theoretical part is accompanied by a careful examination of the mistakes that Google makes and by a fieldwork, conducted in the School of Languages in April 2017, that reveals the didactic implications and repercussions which the analysis of incorrectly translated texts can have in the classroom

Manuaali "KoGloss: korpuspõhine kollaboratiivne konstruktsioonide glossaarium ülikoolide keeleõppes ja kutsetegevuses" tõlge ja tõlkeanalüüs masintõlke seisukohast

Käesoleva magistritöö eesmärgiks on tarbeteksti tõlke näitel välja selgitada, kas ja millisel määral on töö koostamise ajal (aastatel 2016 kuni 2017) kättesaadav masintõlge abiks tõlkimisel saksa-eesti suunal. Selle eesmärgi elluviimiseks on tõlgitud saksa keelest eesti keelde „KoGloss, korpuspõhine kollaboratiivne konstruktsioonide glossaarium ülikoolide keeleõppes ja kutsetegevuses“ manuaal. Tegu on tekstiga, mida võiks lugeda „keskmisest keerulisemaks“. Seejuures ei eeldata, et masintõlge oleks suuteline andma kohe ideaalset tõlget. Analüüsimisel keskendutakse eelkõige sellele, kas masintõlge aitab selle laadse teksti tõlkimisel aega ja vaeva kokku hoida või mitte. Idee KoGlossi manuaali tõlkimise jaoks andis minu juhendaja Terje Loogus, kes on samuti selle projekti liige. Minul endal oli soov teha midagi praktilist, mis oleks seotud minu elukutse valikuga. Minu päris algne plaan oli tõlkida ühte saksakeelset romaani, kuid see ei läinud kokku tõlkeõpetuse magistritöö nõuetega. Seega langes minu valik käesoleva teema kasuks.http://www.ester.ee/record=b477714

STUDENTS’ PERCEPTION OF USING E-DICTIONARY IN E-LEARNING ENGLISH DURING PANDEMIC AT SMAN 1 TANDUN

ABSTRAK Yelda Oktriviani (2022): Pendapat Siswa Terhadap Penggunaan E-Dictionary dalam E-Learning Selama Pandemi di SMAN 1 Tandun Penelitian ini dilakukan berdasarkan studi pendahuluan pada siswa kelas 10 SMAN 1 Tandun yang mana itu menunjukkan beberapa permasalahan terkait penggunaan E-Dictionary. Beberapa permasalahannya adalah banyak siswa yang menggunakan E-Dictionary untuk membantu mereka dalam mencari terjemahan kata dan kalimat, namun ada juga yang tidak menggunakan E-Dictionary dan lebih memilih menggunakan kamus kertas. Oleh karena itu, peneliti ingin mengkaji bagaimana persepsi siswa terhadap penggunaan E-Dictionary. Penelitian ini merupakan penelitian deskriptif kuantitatif yang bertujuan untuk mengidentifikasi persepsi siswa terhadap penggunaan E-Dictionary dalam E-Learning Bahasa Inggris selama pandemi di SMAN 1 Tandun. Populasi dalam penelitian ini adalah siswa kelas 10 SMAN 1 Tandun yang terdiri dari 6 kelas. Teknik pengambilan sampel dalam penelitian ini menggunakan simple random sampling. Jadi, jumlah sampel dalam penelitian ini adalah 34 siswa dari total populasi. Kuesioner digunakan sebagai alat pengumpulan data dalam penelitian yang terdiri dari 20 pernyataan yang diadaptasi dari penelitian terdahulu yang dilakukan oleh Wati (2020) and Marjun (2021). Dalam penelitian ini, peneliti menggunakan program SPSS untuk menganalisis data. Hasil dari analisis data menunjukkan persepsi siswa terhadap penggunaan E-Dictionary berada pada kategori sangat positif dengan persentase 53%. Key words: Students’ Perception, E-Learning, and E-Dictionar