scholarly journals English-Turkish Literary Translation Through Human-Machine Interaction

2021 ◽  
pp. 171-203
Author(s):  
Mehmet Şahin ◽  
Sabri Gürses
Keyword(s):  
Machine Translation ◽  
Literary Translation ◽  
Literary Texts ◽  
Human Machine Interaction ◽  
Negative Attitudes ◽  
Positive Direction ◽  
Translation Practice ◽  
Turkish Language ◽  
Machine Interaction ◽  
Language Pair

This article investigates perceptions of technology-mediated translations of literary texts by two groups: translation students and professional literary translators. The participants post-edited an excerpt from a classic Dickens novel into Turkish using a machine translation (MT) system of their choice. The analysis of the post-edited texts, participants’ answers to survey questions, and interviews with professional translators suggest that MT is currently a long way from being an essential part of any literary translation practice for the English–Turkish language pair. Translators’ interactions with MT and negative attitudes toward it may change in a positive direction as MT improves and translation practice evolves.

scholarly journals Explicitation and Implicitation as Translation Universals and Their Occurrences in the Slovene Translations of Anglo-American Literary Texts

2014 ◽  
Vol 11 (2) ◽  
pp. 101-114
Author(s):  
Uroš Mozetič
Keyword(s):  
Literary Translation ◽  
Literary Texts ◽  
Translation Practice ◽  
Anglo American

The paper examines explicitation/implicitation as one of the most prevailing occurrences in Slovene literary translation practice. Drawing on the received typology of explicitation – obligatory, optional, pragmatic and translation-inherent − the paper seeks to identify the reasons for, and consequences of, certain (in)adequate translation processes, suggesting more adequate solutions where possible. An analysis of the examples selected from the corpus of Slovene translations is introduced by a detailed discussion of the explicitation and implicitation phenomena.

Defining language dependent post-editing guidelines for specific content

Babel ◽  
2020 ◽  
Vol 66 (4-5) ◽  
pp. 811-828
Author(s):  
Seung-Hye Mah
Keyword(s):  
Machine Translation ◽  
Early Stage ◽  
Rapid Development ◽  
Literary Translation ◽  
Literary Texts ◽  
Specific Content ◽  
Critical Elements ◽  
Stylistic Elements ◽  
To Come ◽  
Translation Systems

Abstract The rapid development of neural machine translation systems and the emergence of the e-book have broadened the scope of text types that can be translated by machines. At the early stage of the machine’s infiltration into the translation field, target texts were mainly technical texts such as patents, instruction manuals, etc. Literary texts have been considered as the last bastion of human translation because the machine translation (MT) has produced word-for-word translation, unsuitable for literary texts with distinct stylistic elements. However, it turns out that the field of literary translation was not immune to the rise of MT. Style is one of the critical elements in literary texts, but it has been dismissed in the existing MT post-editing guidelines. Therefore, this research attempts to provide methodological ideas about how to come up with a machine translation post-editing guideline (MTPE) for style improvement especially for language pairs with divergent syntax and semantics like English and Korean. First, the linguistic and cultural differences in writing styles are sorted out based on previous research. Second, the different ways in which human translators address writing style are investigated. Third, the strategies that human translators employ in their translations are applied to machine translation post-editing to demonstrate how the strategies can be incorporated into English-Korean MTPE to improve style. This preliminary research would lay the groundwork for refining post-editing style guidelines and for accumulating manually post-edited data for style improvement, which would be conducive to building and customizing automatic post-editing systems.

scholarly journals Man vs Machine: A Comparison of Linguistic, Cultural, and Stylistic Levels in Literary Translation

2021 ◽  
Vol 4 (2) ◽  
pp. 70-77
Author(s):  
Mohammed Juma Zagood ◽  
Alya Al-Nuaimi ◽  
Aysha Al-Blooshi
Keyword(s):  
Machine Translation ◽  
Short Story ◽  
Human Mind ◽  
Literary Translation ◽  
Literary Texts ◽  
Advantages And Disadvantages ◽  
Clear Vision ◽  
Open Window ◽  
Different Levels

This study aims to remark the differences between human translation (HT) and machine translation (MT) on linguistic, cultural, and stylistic levels when translating English literary texts into Arabic. To accomplish the goal of this study, a comparison between the Arabic HT and MT of Saki’s (1914) short story ‘The Open Window’ is conducted. The study focuses on comparing the two translations (HT and MT) on linguistic, cultural, and stylistic levels to identify the differences between HT and MT in translating literary texts. Throughout this comparison, it is found out that both HT and MT have their advantages and disadvantages on different levels. It has also been found out that MT is unable to identify cultural items and consequently mistranslate them. It is, therefore, concluded that MT can work proficiently on certain levels besides the intervention of the human mind. The findings of this study provide translators using MT with a clear vision on the points of strength and weaknesses in translating literary texts. 

Factored Statistical Machine Translation for German-English

2018 ◽  
Vol 5 (1) ◽  
pp. 37-45
Author(s):  
Darryl Yunus Sulistyan
Keyword(s):  
Machine Translation ◽  
English Language ◽  
Statistical Machine Translation ◽  
New Model ◽  
Language Pair

Machine Translation is a machine that is going to automatically translate given sentences in a language to other particular language. This paper aims to test the effectiveness of a new model of machine translation which is factored machine translation. We compare the performance of the unfactored system as our baseline compared to the factored model in terms of BLEU score. We test the model in German-English language pair using Europarl corpus. The tools we are using is called MOSES. It is freely downloadable and use. We found, however, that the unfactored model scored over 24 in BLEU and outperforms the factored model which scored below 24 in BLEU for all cases. In terms of words being translated, however, all of factored models outperforms the unfactored model.

TRANSLATION AS MENTAL INTERPRETATION ACTIVITY IN LINGUISTICS AND LITERATURE

2019 ◽  
Vol 18 (28) ◽  
pp. 43-53
Author(s):  
Svitlana Gruschko
Keyword(s):  
Literary Criticism ◽  
Literary Work ◽  
Cross Cultural ◽  
Literary Translation ◽  
Literary Texts ◽  
Cultural Dimension ◽  
Cultural Communication ◽  
Original Text ◽  
Cross Cultural Communication ◽  
Cross Language

In the article the phenomenon of translation is regarded as mental interpretation activity not only in linguistics, but also in literary criticism. The literary work and its translation are most vivid guides to mental and cultural life of people, an example of intercultural communication. An adequate perception of non-native culture depends on communicators’ general fund of knowledge. The essential part of such fund of knowledge is native language, and translation, being a mediator, is a means of cross-language and cross-cultural communication. Mastering another language through literature, a person is mastering new world and its culture. The process of literary texts’ translation requires language creativity of the translator, who becomes so-called “co-author” of the work. Translation activity is a result of the interpreter’s creativity and a sort of language activity: language units are being selected according to language units of the original text. This kind of approach actualizes linguistic researching of real translation facts: balance between language and speech units of the translated work (i.e. translationinterpretation, author’s made-up words, or revised language peculiarities of the characters). The process of literary translation by itself should be considered within the dimension of a dialogue between cultures. Such a dialogue takes place in the frame of different national stereotypes of thinking and communicational behavior, which influences mutual understanding between the communicators with the help of literary work being a mediator. So, modern linguistics actualizes the research of language activities during the process of literary work’s creating. This problem has to be studied furthermore, it can be considered as one of the central ones to be under consideration while dealing with cultural dimension of the translation process, including the process of solving the problems of cross-cultural communication.

English-Dogri Translation System using MOSES

2016 ◽  
Vol 1 (1) ◽  
pp. 45-49
Author(s):  
Avinash Singh ◽  
Asmeet Kour ◽  
Shubhnandan S. Jamwal
Keyword(s):  
Natural Language Processing ◽  
Machine Translation ◽  
Language Processing ◽  
Statistical Machine Translation ◽  
Translation System ◽  
Parallel Corpus ◽  
English System ◽  
Machine Translation System ◽  
Translation Machine ◽  
Language Pair

The objective behind this paper is to analyze the English-Dogri parallel corpus translation. Machine translation is the translation from one language into another language. Machine translation is the biggest application of the Natural Language Processing (NLP). Moses is statistical machine translation system allow to train translation models for any language pair. We have developed translation system using Statistical based approach which helps in translating English to Dogri and vice versa. The parallel corpus consists of 98,973 sentences. The system gives accuracy of 80% in translating English to Dogri and the system gives accuracy of 87% in translating Dogri to English system.

Concise CNN model for face expression recognition

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi
Keyword(s):  
Network Architecture ◽  
Expression Recognition ◽  
Human Machine Interaction ◽  
Face Expression ◽  
Computational Overhead ◽  
Average Accuracy ◽  
Proposed Model ◽  
Face Expression Recognition ◽  
Expression Classification ◽  
Machine Interaction

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

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