machine translation IEEE PAPERS-2020
Machine Translation is software that automatically renders text from one language into another. A key benefit of RBMT over other MT approaches is that it can produce better quality for language pairs with very different word orders
Can You Translate that into Man Commercial Machine Translation Systems Include Stylistic Biases
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The main goal of machine translation has been to convey the correct content. Stylistic considerations have been at best secondary. We show that as a consequence, the output of three commercial machine translation systems (Bing, DeepL, Google) makeWe present a novel approach to automatic Sign Language Production using recent developments in Neural Machine Translation (NMT), Generative Adversarial Networks, and motion generation. Our system is capable of producing sign videos from spoken language Abstract Machine translation system (MTS) constitutes of functionally heterogeneous modules for processing source language to a given target language. Deploying such an application on a stand-alone system requires much time, knowledge and complications. It In computer-aided translation tasks, reducing the time of reviewing and post-editing on translations is meaningful for human translators. However, existing studies mainly aim to improve overall translation quality, which only reduces post-editing time. In this work, we
KNOWLEDGE GRAPHS EFFECTIVENESS IN NEURAL MACHINE TRANSLATION IMPROVEMENT
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Maintaining semantic relations between words during the translation process yields more accurate target-language output from Neural Machine Translation (NMT). Although difficult to achieve from training data alone, it is possible to leverage Knowledge Graphs (KGs) to
ISTICs Neural Machine Translation System for IWSLT 2020
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This paper introduces technical details of machine translation system of Institute of Scientific and Technical Information of China (ISTIC) for the 17th International Conference on Spoken Language Translation (IWSLT 2020). ISTIC participated in both translation tasks of the Open
MTrill project: Machine Translation impact on language learning
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1 Background Over the last decades, massive research investments have been made in the development of machine translation (MT) systems (Gupta and Dhawan). This has brought about a paradigm shift in the performance of these language tools, leading to an Neither assigning similar priority to all phrases nor pruning out the incorrect phrases from the phrase table can improve the accuracy of machine translation . In this paper, we present a novel method for weight re-adjustment of phrase table in a statistical machine translation
Substructure-based Neural Machine Translation for Retrosynthetic Prediction
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With the rapid improvement of machine translation approaches, neural machine translation has started to play an important role in retrosynthesis planning, which finds reasonable synthetic pathways for a target molecule. Previous studies showed that utilizing the
Improving Context-Aware Neural Machine Translation Using Self-Attentive Sentence Embedding.
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Abstract Fully Attentional Networks (FAN) like Transformer (Vaswani et al. 2017) has shown superior results in Neural Machine Translation (NMT) tasks and has become a solid baseline for translation tasks. More recent studies also have reported experimental results
TILDES NEURAL MACHINE TRANSLATION TECHNOLOGY
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Although ideas of machine translation date back to as early as the 17th century , the first working prototype of a digital machine translation system was possible only after the introduction of digital computers. In 195 a team of researchers from IBM and Georgetown
Morphological Segmentation of Polysynthetic Languages for Neural Machine Translation : The Case of Inuktitut
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Segmentation of words into sub-word units is a crucial preprocessing step of modern machine translation systems, which allows the translation of unseen and rare words. It is still largely unknown how existing methods perform on a category of languages with a much
Attention based Neural Machine Translation of Indian Languages
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Abstract Machine translation is converting source text in one language to text in another language automatically. In recent years, Neural Machine Translation has emerged as a way of addressing this task and is proved to be more effective than rule-based and statistical
Alignment-Based Neural Networks for Machine Translation
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After more than a decade of phrase-based systems dominating the scene of machine translation neural machine translation has emerged as the new machine translation paradigm. Not only does state-of-the-art neural machine translation demonstrate superior
Students Perceptions of the Use of Online Machine Translation in L2 Writing
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This study investigated students views on the use of online machine translation (MT) in L2 writing by collecting survey responses from 171 Korean learners of English upon completion of actual writing tasks in the classroom and comparing these responses for different
On the Development and Limitation of Machine Translation
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We are in an age of information in which all kinds of scientific and technological products are increasingly updated. In recent years, machine translation has also set off an upsurge in the translation industry, and its advantages are gaining more and more recognition of the public
Simultaneous translation and paraphrase for language education
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This is motivated by the need to create and maintain large, high-quality sets of acceptable translations for exercises in a language-learning application, and synthe- sizes work spanning machine translation MT evaluation, automatic paraphrasing, and lan- guage education
Machine translation advantages and disadvantages
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In modern society, knowledge of a foreign language is necessary not only if we go on a trip abroad, but in everyday life. So, for example, it is difficult to imagine a humanist, in particular a philologist, without dictionaries. In this case, a very profitable option is an online dictionary
Teaching Arabic Machine Translation to EFL Student Translators: A Case Study of Omani Translation Undergraduates
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The present paper describes a machine translation (MT) course taught to undergraduate students in the Department of English Language and Literature at Dhofar University in Oman. The course is one of the major requirements for BA in Translation . Fifteen EFL
Terminology-Constrained Neural Machine Translation at SAP
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This paper examines approaches to bias a neural machine translation model to adhere to terminology constraints in an industrial setup. In particular, we investigate variations of the approach by Dinu et al.(2019), which uses inline annotation of the target terms in the source
English to Bangla Machine Translation Using Recurrent Neural Network
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The applications of recurrent neural networks in machine translation are increasing in natural language processing. Besides other languages, Bangla language contains a large amount of vocabulary. Improvement of English to Bangla machine translation would be a
The Integrated Evaluation Method of Machine Translation Quality Based on Z-numbers.
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The evaluation of machine translations is of great significance to machine translation research. The evaluations are based on the judgments of the evaluators, and it is necessary for us to ensure that the judgments are reliable. Since the Z-number has the potential to
Optimizing segmentation granularity for neural machine translation
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In neural machine translation (NMT), it has become standard to translate using subword units to allow for an open vocabulary and improve accuracy on infrequent words. Byte-pair encoding (BPE) and its variants are the predominant approach to generating these
Knowledge Graphs Enhanced Neural Machine Translation
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Abstract Knowledge graphs (KGs) store much structured information on various entities, many of which are not covered by the parallel sentence pairs of neural machine translation (NMT). To improve the translation quality of these entities, in this paper we propose a novel Language translation is the task in which machine is facing lagging behind the cognitive powers of human beings. Statistical Machine Translation is solving the problem of machine translation but it requires huge data sets and performs well on similar gram structured
FROM MACHINE TRANSLATION TO FORMAL GRAM IN BULGARIA
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The paper discusses the connection between the emergence of the fields of formal gram and machine translation in Bulgarian linguistics in 1960 1965. In the context of intercultural transfer, the core ideas of machine translation are outlined as motivating the first generative
Multilingual Machine Translation
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Page 1. Multilingual Machine Translation OndŠej Bojar April NPFL087 Statistical Machine Translation Charles University Faculty of Mathematics and Physics Institute of Formal and Applied Linguistics unless otherwise stated Page 2. Outline Motivation for using more than 2 languages.Sreedeepa H. S Assistant Professor Computer Science Engineering College Of Engineering Kallooppara Thriuvalla Divya Madhu Assistant Professor Computer Science Engineering Vidya Academy of Science Technology Technical Campus Kilimanoor Abstract Sanskrit
Problems of narrow-branch vocabulary interpretation ?y means of machine translation programs
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Page 1. 42 PROBLEMS OF NARROW-BRANCH VOCABULARY INTERPRETATION BY MEANS OF MACHINE TRANSLATION PROGRAMS Plotnikova NV National University of Pharmacy, Kharkiv Narrow-branch vocabulary, namely terminology, is one of the determining factors for the language
Lexical-Constraint-Aware Neural Machine Translation via Data Augmentation
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Leveraging lexical constraint is extremely significant in domain-specific machine translation and interactive machine translation . Previous studies mainly focus on extending beam search algorithm or augmenting the training corpus by replacing source phrases with the
BULGARIAN-ENGLISH GRAMMATICAL PARALLELS IN RELATION TO MACHINE TRANSLATION
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Digital processing of linguistic data has become increasingly popular in recent years and is being used more widely not only in the field of linguistics but also in a number of related fields. One of the reasons for the growing popularity of digital processing is that it allows
A TRANSFER GRAM FOR ENGLISH-TAMIL MACHINE TRANSLATION
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In this chapter a computationally viable syntactic structure of English has been worked out with the intention of matching it with the similar structure of Tamil in order to prepare a transfer gram for machine translation . English is a configurational language in which the
Statistical Machine Translation between Myan and Myeik
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This paper contributes the first evaluation of the quality of machine translation between Myan and Myeik (also known as Beik). We also developed a Myanmar-Myeik parallel corpus (around 10K sentences) based on the Myan language of ASEAN MT corpus. In
Machine Translation And Its Impact In Our Modern Society
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Machine translation is now rather popular and is gradually breaking the world language barrier. Translation accuracy and efficiency are getting closer to human ability. In addition to translating letters and sentences, machines for translating speech have also been
Statistical Machine Translation of Myan Dialects
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The goal of this work is to contribute the first evaluation of the quality of machine translation between Standard Myan and Other Myan Dialectal Languages. Myan Dialects present many challenges for machine translation which is the lack of data resources. To
Patent Translation
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In this chapter, we first present the history of machine translation ; the contribution of evaluation workshops to machine translation research, and previous evaluation workshops; and the challenge of patent translation at the time of the first patent translation task at NTCIR
Ad hoc compounds in English to Finnish machine translation
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Abstract Language is in a continuous development process, which poses a challenge to machine translation . People also tend to have their only styles of writing, which is often difficult to translate. A special problem is the so called ad hoc compounding, where the writer
BUILDING MACHINE TRANSLATION SYSTEMS FOR MINOR LANGUAGES: CHALLENGES AND EFFECTS.
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Building machine translation systems for disadvantaged languages, which I will call minor languages, poses a number of challenges whilst also opening the door to new opportunities. After defining a few basic concepts, such as minor language and machine translation the
Perceptions of Machine Translation and Computer-Aided Translation by Professionals and the General Public. A Survey Study
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This article examines perceptions of MT and CAT among translation professionals and the general public by surveying 124 articles published in the professional journals of ITI Bulletin and MultiLingual and in the Chinese media between and 2019. Through framing
Statistical Machine Translation between Myan (Burmese) and Kayah
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(SMT) between Myan (Burmese) and Kayah (Kayah Li) languages. We also developed a Myanmar-Kayah parallel corpus ( 590 sentences) based on the Myan language of ASEAN MT corpus. The experiments were carried out using three different statistical
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