Errors in translation made

The study aims to identify the common errors made by students in their third year at Faculty of English Language Teacher Education (FELTE), University of Foreign Languages and International Studies (ULIS) during translation tasks.

3p vijaychest 16-05-2024 3 0   Download

The objectives of this research were to examine types of translation errors in translation from Thai into English, to determine the types of translation errors that are most common, and to find possible explanations for the causes of errors. The results of this study will be used to improve translation teaching and the course “Translation from Thai into English”.

6p guernsey 28-12-2021 17 1   Download

This article investigates common errors that Vietnamese students often make in the process of translating Vietnamese sentence structures into English. The analysis focuses on the types and frequency of errors in translating Vietnamese structures into the English language such as sentences with elliptical subjects, passive sentences, subordinate clauses in complex sentences, and negative sentences.

5p nguyenmyhuyen90 28-02-2021 39 2   Download

The major instruments utilized in the study included document observations, questionnaires and interviews. The combination of both quantitative and qualitative methods enabled the researchers to triangulate the data in order to attain the most reliable findings. It is expected that the study will be of benefits to not only wouldbe translators but also translation teachers at FELTE, ULIS, VNU.

11p miulovesmile4 19-11-2018 48 2   Download

An investigation into common errors in Vietnamese english translation made by third year english major students at Thu Dau Mot university. This study aims to investigate students’ common errors in Vietnamese-English translation. Eighty-two third-year English major students (69 female, 13 male) of the Foreign Language Faculty, Thu Dau Mot University participated in the study.

11p lehasiphuong 22-05-2018 118 5   Download

We present a Hebrew to English transliteration method in the context of a machine translation system. Our method uses machine learning to determine which terms are to be transliterated rather than translated. The training corpus for this purpose includes only positive examples, acquired semi-automatically. Our classifier reduces more than 38% of the errors made by a baseline method. The identified terms are then transliterated. We present an SMTbased transliteration model trained with a parallel corpus extracted from Wikipedia using a fairly simple method which requires minimal knowledge. .

9p bunthai_1 06-05-2013 38 1   Download

This paper presents a pilot study of the use of phrasal Statistical Machine Translation (SMT) techniques to identify and correct writing errors made by learners of English as a Second Language (ESL). Using examples of mass noun errors found in the Chinese Learner Error Corpus (CLEC) to guide creation of an engineered training set, we show that application of the SMT paradigm can capture errors not well addressed by widely-used proofing tools designed for native speakers.

8p hongvang_1 16-04-2013 41 1   Download

State-of-the-art statistical machine translation (MT) systems have made significant progress towards producing user-acceptable translation output. However, there is still no efficient way for MT systems to inform users which words are likely translated correctly and how confident it is about the whole sentence. We propose a novel framework to predict wordlevel and sentence-level MT errors with a large number of novel features. Experimental results show that the MT error prediction accuracy is increased from 69.1 to 72.2 in F-score. ...

9p hongdo_1 12-04-2013 44 4   Download

This is the text of my doctoral dissertation, completed under the direction of the late Dr. David Edwin Pingree of Brown University. He worked extensively on this text and made countless corrections and suggestions. It is much more his work than mine. Suffice it to say that all errors the reader may encounter are mine alone. Whatever the reader finds useful or worthwhile in this text is Dr. Pingree's. Released under the GNU verbatim license quoted above.

0p window1234 22-12-2012 37 3   Download