Types Of Translation Errors Research Articles

Word Segmentation in Sentence Reading by Learners of Chinese

This study adopted an experimental approach to compare two groups of third-year students learning Chinese in sentence reading comprehension with and without a word segmentation exercise at a southwestern American university. The t-test showed that the experimental group, which received a word segmentation task followed by immediate feedback before reading, outperformed the non-experimental group, which received no treatment before reading. The correlation analysis confirmed that four types of word segmentation errors were moderately correlated with four types of translation errors. This study concluded that introducing word segmentation exercises could facilitate reading comprehension. Based on the findings, pedagogical implementations were suggested.

Penerjemahan Frasa Nomina Bahasa Korea ke Bahasa Indonesia dari Buku Esai Naneun Naro Salgiro Haetda ke dalam Hidup Apa Adanya: Kesalahan dan Strategi

The purposes of this research are to identify and analyze noun phrase’s translation errors and translation strategies from Korean to Indonesian that happened in an essay book titled Hidup Apa Adanya (2020), the Indonesian translation of Naneun Naro Salgiro Haetda (나는 나로 살기로 했다) (2016) by Suhyun Kim. This research is done using a descriptive-qualitative analysis method and two theories which are Translation Criticism (1988) by Peter Newmark and Translation Strategies (2016) by Zuchridin Suryawinata and Sugeng Hariyanto. The result indicates that firstly, there are six types of translation errors, which are (1) semantic error as the most found type, (2) omission, (3) word’s class and form’s change, (4) diction error, (5) word by word translation, and (6) cultural terms error. Secondly, there are nine strategies combinations such as (1) expansion and recognized translation, (2) synonymy and transposition, the most used combination, (3) synonymy, transposition, and addition, (4) synonymy, transposition, and borrowing, (5) modulation, transposition, and subtraction, (6) modulation, componential analysis, and addition, (7) borrowing and addition, (8) borrowing and transposition, and (9) borrowing, transposition, reduction, and expansion. The result also shows that the translator did not use cultural equivalent and descriptive equivalent strategies.

A Quantitative Impact Assessment of English Translation Errors on the Authenticity of News Dissemination

Abstract To improve the accuracy of news communication between readers and audiences, it is necessary to avoid the errors generated in the process of news translation so as to make the English translation of news content expression more in line with the actual situation, thus ensuring the authenticity of news dissemination. In this paper, the MapReduce multiple regression model is constructed by optimizing the classical multiple linear regression model in terms of maximum likelihood estimation and gradient descent algorithm with the aim of reducing the errors in the process of English translation of news. This model is used to analyze the errors generated by the English translation process and finally proposes a method for improving translation accuracy based on the factors causing the errors. After testing, the F-value, P-value, and R² of the degree of fit of the MapReduce model are 54.39, 0.005, and 0.893, respectively. Furthermore, the model passed the significance test. The Pearson coefficients of the 4 types of translation errors in the MapReduce multiple linear regression model were −0.673, −0.622, −0.584, and −0.736, respectively, all of which were significantly negatively correlated with the truthfulness of news dissemination at the 1% level. The model analyzes that the three kinds of translation errors are basically between 2%-4%, 7%-20%, and 2%-4%, and puts forward reasonable opinions on the avoidance of the four kinds of errors, namely, “pragmatic translation, cultural translation, linguistic translation and text-specific translation”, which generate errors in the process of the English translation of news.

Types of Translation Errors in The Translation Feature of Local Guide Reviews on Google Map

Translation errors can occur due to the delivery of a translated source language that the target language cannot accept. Moreover, the need for more attention to new terms adopted by a language means that translation errors often occur. Therefore, this study aims to describe and correct errors in the translation results in the see translation feature in local guide reviews on Google Maps. Sources of data in this study were taken from the Google Maps application and the results of interviews. Researchers used a qualitative descriptive approach with thematic analysis techniques to describe the types of errors. Documentation and interview techniques were used for data collection. From the research results, 194 errors were found in the results of the translation. Based on orthography taxonomy, 19 types of errors were found, with a percentage of 9.79%. Then, in the lexis taxonomy, 36 data were found with a percentage of 18.54%. In the grammar taxonomy, 23 data were found with a percentage of 11.85%. In the semantic taxonomy, 91 data were found with a percentage of 46.88%. And the last one, namely discourse taxonomy, found 25 data with a percentage of 12.88%. From the research findings, the most common type of error found is in the semantic taxonomy. This research implies that by knowing these errors, the creator of the translation application can produce a better translation and know the techniques for improving the translation results in accordance with the context of reviews made by local guides on the Google Maps application, which in general discussing the service, atmosphere and conditions of a place.

Types of Translation Errors from Indonesia Language into English in Pharmacy Journal Articles

The study analyzed the types of errors based on ATA Error Categories version 2021 on the three submitted journal articles translated by lecturers of Clinical Pharmacy and Pharmacy Community of Akademi Farmasi Surabaya. It aimed to find the types of errors often made by pharmacy lecturers in translating the articles from the Indonesian language into English so that the results of this study can help them identify and avoid errors in translation. The study used the descriptive qualitative, using the content analysis method. The objects of this study were three journal articles in the Indonesian language (ST) and English (TT). The data focused on the translation errors based on ATA Error Categories in the words or phrases level. The results showed there were 14 types of errors found, namely: literalness (31.05%), usage (22.22%), punctuation (7.84%), terminology (7.52%), verb form (6.86%), grammar (6.54%), capitalization (3.59%), parts of speech (3.59%), syntax (3.27%), style (2.94%), register (2.29%), omission (1.31%), cohesion (0.65%), and ambiguity (0.33%). The study recommended that translators have sufficient knowledge about the target language mechanics, produce clear renditions of the source text, and maintain the writing quality of the target text.

TYPES OF TRANSLATION ERRORS IN A LITERARY TEXT TRANSLATION (BASED ON THE A. NURPEISOV’S TRILOGY “BLOOD AND SWEAT”)

The article is aimed to determine the main types of translation errors and consider the consequences of their appearance in the text, as well as the result of a distorted perception of the text of the translation by the addressee. The existing classifications of translation errors are summarized. By comparing an authorized translation of the trilogy of the Kazakh writer A. Nurpeisov “Blood and sweat” into Russian with the text of the English translation, made by Catherine Fitzpatrick, the main types of translation errors were identified and highlighted. Almost all groups and types of errors indicated in different classifications were found in the English translation of the above mentioned novel. It is concluded, that the study of the phenomenon of translation error requires a profound multi-aspect analysis.

Surface Translation Errors in Literary and Scientific Texts: A Case Study

This study aims at investigating the most frequently occurred surface translation errors made by Bahdini EFL university students in literary and scientific texts. This is conducted via applying the error analysis technique, which is considered a vital part of EFL research. By using a quantitative and qualitative method, the researchers limited their literature review and data analysis to only the translation errors that are related to the surface structure of sentences by Dulay et al. (1982), excluding other types of translation errors (i.e., linguistic, comparative, and communicative). The data have been extracted from literary and scientific texts that have been translated by 50 EFL juniors and seniors from the English Department, University of Zakho. The researchers implemented a process of coding for finding out translation errors, and tabulated their frequencies and percentages on Excel bar charts. The results show that out of the total of 307 surface translation errors, misformation in scientific texts recorded the highest percentage. In contrast, misordering had the lowest percentage in literary texts. Further, addition and omission manifested variability in percentages. This study will be valuable for teachers to design better syllabi for teaching translation, and for learners to develop their linguistic skills when learning a second language.

The Analysis of Short Story Translation Errors (A Case Study of Types and Causes)

Translation of short stories as a literary work has become a trend lately because the short story provides entertainment and education for the readers. However, the translation process has been complicated because translators must be able to convey the message without changing the purposes of a source language. The preliminary observation discovered numerous errors made by students when they translate Indonesian short stories into English. Thus, this study aims to analyze the types and causes of translation errors in translating the short story. The descriptive qualitative approach is applied in document analysis. Data collection was carried out through translation tests and interviews. Then, the collected data were classified and analyzed by using Mathieu's (200 translations issues' theory (2003). The results discovered that the types of translation errors were a number of linguistic issues including grammatical issues, lexical choices, rhetorical problems, pragmatic problems, and cultural issues. The errors made were caused by the lack of vocabularies, misinterpretation of an idiomatic expression, figurative language, and implicit meaning, dissimilarities among cultural references and terms, the influence of the first language, and misunderstanding of English structure rules.

Document-Level Machine Translation – Ensuring Translational Consistency of Non-Local Phenomena

In this thesis, we study the automatic translation of documents by taking into account cross-sentence phenomena. This document-level information is typically ignored by most of the standard state-of-the-art Machine Translation (MT) systems, which focus on translating texts processing each of their sentences in isolation. Translating each sentence without looking at its surrounding context can lead to certain types of translation errors, such as inconsistent translations for the same word or for elements in a coreference chain. We introduce methods to attend to document-level phenomena in order to avoid those errors, and thus, reach translations that properly convey the original meaning. Our research starts by identifying the translation errors related to such document-level phenomena that commonly appear in the output of state-of-the-art Statistical Machine Translation (SMT) systems. For two of those errors, namely inconsistent word translations as well as gender and number disagreements among words, we design simple and yet effective post-processing techniques to tackle and correct them. Since these techniques are applied a posteriori, they can access the whole source and target documents, and hence, they are able to perform a global analysis and improve the coherence and consistency of the translation. Nevertheless, since following such a two-pass decoding strategy is not optimal in terms of efficiency, we also focus on introducing the context-awareness during the decoding process itself. To this end, we enhance a document-oriented SMT system with distributional semantic information in the form of bilingual and monolingual word embeddings. In particular, these embeddings are used as Semantic Space Language Models (SSLMs) and as a novel feature function. The goal of the former is to promote word translations that are semantically close to their preceding context, whereas the latter promotes the lexical choice that is closest to its surrounding context, for those words that have varying translations throughout the document. In both cases, the context extends beyond sentence boundaries. Recently, the MT community has transitioned to the neural paradigm. The finalstep of our research proposes an extension of the decoding process for a Neural Machine Translation (NMT) framework, independent of the model architecture, by shallow fusing the information from a neural translation model and the context semantics enclosed in the previously studied SSLMs. The aim of this modification is to introduce the benefits of context information also into the decoding process of NMT systems, as well as to obtain an additional validation for the techniques we explored. The automatic evaluation of our approaches does not reflect significant variations. This is expected since most automatic metrics are neither context- nor semantic-aware and because the phenomena we tackle are rare, leading to few modifications with respect to the baseline translations. On the other hand, manual evaluations demonstrate the positive impact of our approaches since human evaluators tend to prefer the translations produced by our document-aware systems. Therefore, the changes introduced by our enhanced systems are important since they are related to how humans perceive translation quality for long texts.

Issues in Interactive Translation Practice on Twitter

I used my Twitter account to tweet images of English and Arabic texts to be translated by my student followers who are translation major. My followers translated the texts and corrected the translation errors, tweeted and re-tweeted their translations and corrections for feedback. I gave feedback on the location and types of translation errors, tweeted prompts, translation tips and resources while followers were re-thinking and working on their answers. The followers reported that they benefited from the variety of translation tips, feedback and dictionaries tweeted. Further pedagogical issues, reflections and recommendations on interactive translation practice via Twitter are given.

Translation Errors Across Genres: A Research Perspective

Abstract Even if there may be types of translation errors which have a rather general character, in most of the cases they are closely related to the genre that the text to be translated represents. The paper offers an analysis of the translation errors contained by the assignments of 30 MA students in Translation Studies from the West University of Timisoara, Romania. The assignments consist in the translation from English into Romanian of texts belonging to three different genres: travel guides, legislation, and medical case reports. The errors are analyzed both quantitatively and qualitatively, with a view to arriving at conclusions of relevance for the improvement of the training process.

Analysis of the Types of Translation Errors by the Google Translator

Analysis of the Types of Translation Errors by the Google Translator

THE SOURCE OF ERRORS IN INDONESIAN-ENGLISH TRANSLATION

<p>This research aimed to identify types of translation errors and to find out the sources of errors (interlingual and intralingual errors) in Indonesian-English translation written by the students. The type of this research was descriptive research which used Error Analysis procedures to identify and analyze the students’ error. The findings showed that the types of grammatical errors made by the students in their translation were three types, namely global errors, local errors, and other errors. The most frequent error made by the students was local errors and the fewest error made by the students was other errors. Then, this research revealed that mostly errors occurred in students’ translation were caused by intralingual error. Meanwhile, only few errors were caused by interlingual error. The errors occured due students’ incomplete knowledge of the target language.</p>

Measuring Semantic Preservation in Machine Translation with HCOMET: Human Cognitive Metric for Evaluating Translation

Human ranking of machine translation output is a commonly used method for comparing different innovations in machine translation research. Theoretically simple, the comparison of multiple translations is, in effect, cognitively complex, requiring judges to balance the weight of different types of translation errors in the context of the whole sentence. This cognitive complexity is made evident through low intra- and inter- annotator agreements, which call into question the reliability of such ranking metrics. HMEANT (Lo and Wu, 2011) attempted to decrease the complexity of ranking by dividing sentences into smaller semantic units whose translation alignments were more objective, rendering the task cognitively simpler. However, HMEANT does not discern how these semantic units are related and relies heavily on language-dependent verb frames – a significant problem for a translation metric. This project defines a new set of human metrics focusing on HCOMET (Human COgnitive Metric for Evaluating Translation). HCOMET, attempting to overcome the limitations of HMEANT, employed a new cognitively-informed annotation scheme and new scoring guidelines. While the inter-annotator agreement did not surpass that of HMEANT, the conceptual framework of HCOMET allows for a much more detailed analysis of semantic adequacy in machine translation.

Cross-cultural adaptation of the Health Education Impact Questionnaire: experimental study showed expert committee, not back-translation, added value

ObjectivesTo assess the contribution of back-translation and expert committee to the content and psychometric properties of a translated multidimensional questionnaire. Study Design and SettingRecommendations for questionnaire translation include back-translation and expert committee, but their contribution to measurement properties is unknown. Four English to French translations of the Health Education Impact Questionnaire were generated with and without committee or back-translation. Face validity, acceptability, and structural properties were compared after random assignment to people with rheumatoid arthritis (N = 1,168), chronic renal failure (N = 2,368), and diabetes (N = 538). For face validity, 15 bilingual people compared translations quality with the original. Psychometric properties were examined using confirmatory factor analysis (metric and scalar invariance) and item response theory. ResultsQualitatively, there were five types of translation errors: style, intensity, frequency/time frame, breadth, and meaning. Bilingual assessors ranked best the translations with committee (P = 0.0026). All translations had good structural properties (root mean square error of approximation <0.05; comparative fit index [CFI], ≥0.899; and Tucker–Lewis index, ≥0.889). Full measurement invariance was observed between translations (ΔCFI ≤ 0.01) with metric invariance between translations and original (lowest ΔCFI = 0.022 between fully constrained models and models with free intercepts). Item characteristic curve analyses revealed no significant differences. ConclusionThis is the first experimental evidence that back-translation has moderate impact, whereas expert committee helps to ensure accurate content.

A Corpus-based Approach to Translation Error Analysis. a Case-study of Romanian EFL Learners

The aims of this study are to identify the error patterns produced by EFL students in Business and Public Administration at an intermediate level of English language proficiency, who translate journalistic texts; to analyse these errors quantitatively and qualitatively and to assess the pedagogical implications of findings. The corpus under inquiry consisted of 30 students’ translated journalistic texts (ca. 15,000 words). The identified errors were classified into three main types: linguistic, comprehension and translation errors. They also revealed useful insights into methodological approaches, on how best to develop students’ awareness of their own types of translation errors.

A conjoint analysis framework for evaluating user preferences in machine translation

Despite much research on machine translation (MT) evaluation, there is surprisingly little work that directly measures users' intuitive or emotional preferences regarding different types of MT errors. However, the elicitation and modeling of user preferences is an important prerequisite for research on user adaptation and customization of MT engines. In this paper we explore the use of conjoint analysis as a formal quantitative framework to assess users' relative preferences for different types of translation errors. We apply our approach to the analysis of MT output from translating public health documents from English into Spanish. Our results indicate that word order errors are clearly the most dispreferred error type, followed by word sense, morphological, and function word errors. The conjoint analysis-based model is able to predict user preferences more accurately than a baseline model that chooses the translation with the fewest errors overall. Additionally we analyze the effect of using a crowd-sourced respondent population versus a sample of domain experts and observe that main preference effects are remarkably stable across the two samples.

Translating Tourism Texts in the Light of the Skopos Theory

The present paper aims to explore the activity of translating Chinese tourism texts into English within the framework of the skopos theory, with two culture-related tourism texts in China as examples. First, the basic principles of the skopos theory are outlined, followed by discussion of their application in translating tourism texts. An attempt is then made to analyze two types of translation errors in English translations of tourism texts. They are cultural translation errors and pragmatic translation errors. The paper concludes with two approaches to solve the problems. One of the them is to enhance translators’ awareness of applying skopos to translation. Another is to enhance the translators’ bilingual abilities and ethical standards.

Mit akulturowości tekstów nieliterackich na przykładzie literatury z dziedziny psychologii

The language function is one of the criteria for dividing translated texts into literary and non-literary ones. The latter are supposedly acultural, i.e. free from cultural and intertextual references. Such an approach may lead to translation errors. Translators who focus entirely on that branch of knowledge that a given text refers to and on related terminology may overlook cultural and intertextual elements. Th is not only ignores the intention of introducing them into the text, but also changes the meaning of passages in which they are included. The analysis of two books concerning psychology and psychotherapy: Systems of Psychotherapy. A Transtheoretical Analysis and Personality Disorders in Modern Life provides ample examples of introducing implicit references to the Bible and literary masterpieces into psychological discourse. Despite the label of scientific texts, American psychological literature is characterized by numerous hidden quotations from other sources, thus becoming deeply rooted in the intertextual space, in order to allow readers to imagine psychic conditions described. Consequently, in translating such texts, translators cannot limit themselves to a thorough knowledge of psychology, psychotherapy and terminology connected with those areas, but must also be observant enough to notice intertextual traces and then be able to localize them and interpret them correctly. Otherwise the translation may alter the original meaning or introduce ambiguity which is not welcome in such texts.This paper analyses selected examples of intertextuality in psychological literature and their translations. In each case, editorial intervention was required since the lack of recognition of such elements or their incorrect interpretation resulted in various types of translation errors. The conclusion off ered from this discussion is that translators must bear in mind that all texts are of a hybrid nature, and a narrow specialized approach may not guarantee an error-free translation.

GACcodonGGC: a very favorable context for translation errors?

A survey of the literature on the effect of codon context on translation fidelity suggests that contexts such as GACcodonGGC are strong, but not unique, promotors of several types of translation errors.