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2016, Benjamins Translation Library
Computational linguistics is a science combined with not only computer science and linguistics, but also mathematics, cognitive science ,and so on. With the application of computer technology into language process ,it emerged and developed gradually into an independent system. Study on linguistics influence on the development of computational linguistics and translation platform construction from the perspective of computational linguistics, promotes deep understanding ,the further research explore and effective practice on translation. There seems a certain plausible division of labor between linguistics analysis methods and language process in computational linguistics, which are combined to form a hybrid system. The approach to design the hybrid system is explored from the application of translation platform construction from the perspective of computational linguistics. The paper aims to provide some new perspectives to the translation and the teaching of foreign languages, firstly, analyzes the basic theory of the hybrid model translation platform based on computational linguistics, and then designs the translation platform in detail from the system design idea, overall structure design, and function module design three aspects.
Rupkatha Journal on Interdisciplinary Studies in Humanities, 2021
How often students use IT resources is a key factor in the acquisition of skills associated to the new technologies. Strategies aimed at increasing student autonomy need to be developed and should offer resources that encourage them to make use of computing tools in class hours. The analysis of the modern linguistic technologies, concerning intellectual language processing necessary for the creation and function of the highly effective technologies of knowledge operation was considered in the paper under consideration. Computerization of the information sphere has triggered extensive search for solving the problem of the use of natural language mechanisms in automated systems of various types. One of them was creating Controlled languages based on a set of features which made machine translation more refined. Triggered by the economic demand, they are not artificial languages like Esperanto, but natural simplified languages, in terms of vocabulary, grammatical and syntactic structur...
Humanities Circle, Vol. 5. No.2. Pp.43-61 , 2017
In this paper, we attempt to discuss the linguistic activities necessary to be carried out on bilingual translation corpus (BTC) to develop the linguistic resources and tools required in machine translation (MT). Although attempts are made in last few decades for developing BTC and models for MT, attention is hardly paid to some basic linguistic tasks indispensable for achieving success in the area. Even though we know that generation of BTC is an essential part of MT, we have not tried to understand how these BTC are going to be used in the work. To overcome this deficiency we intend to focus on some of the basic linguistic activities on BTC relating to analysis of BTC, extraction of translational equivalents, developing bilingual dictionaries, generation of terminology databank, selection of appropriate lexical items from the target language, dissolving lexical ambiguities, and generating a network of grammatical mapping with reference to lexical mapping, pragmatic information, and sentential information. In our view, an MT system will be more robust if it is powered with linguistic resources developed from linguistic tasks carried out on BTC. The activities we propose here are not only suitable for MT from English to Bangla, but also for any two language pair. These are also applicable for most of the Indian languages engaged in developing BTC between English and the Indian languages. The linguistic resources generated from analysis of BTC can also be used in language teaching, electronic dictionary compilation, machine learning, grammar development, and language cognition.
2015
Human beings exhibit a striking quality of communicating with each other. Communication by means of a system of communication based upon words and the combination of words into sentences, referred as linguistic communication. None of non-human species have such a system of communication in place that's comparable to human language. What makes languages of human varied and different, are features of duality and arbitrary. In annuals of Anthropology, language is considered as a primary tool for studying the culture of a civilization, what we speak influences what we think, what we feel and what we believe. Culture is transmitted through language. Humans learn their culture through language. Its inquisitive nature of human and passion to travel across the world, warrants different cultures interact with each other, the means to achieve this is through human language, often interacting cultures communicate through different languages. As such, it's essential that humans translate and interpret languages of different cultures for understand their rituals, business and allied activities. With advancements in technology, computer systems have facilitated the translations of languages and achieved results in minimal amount of time, though these systems do not produce exact translated verse but enough and relevant information that could be used by the information professionals to understand the nature of information contained in the document, tools like Babelfish and Google Translator are examples of such systems. Numerous techniques have been developed to automate the translation process and these are termed under Machine Translation, which can be defined as a task of automatically converting one natural language into another, preserving the meaning of the input text, and producing fluent text in the output language. These automated translation systems use state of art technology with wide-ranging dictionaries and a collection of linguistic rules that translate one language into another without relying on human translators. The motivation of this research is to have a comparative study of machine translation techniques used for multilingual translation vis-à-vis efficiency, ease of use, space-time complexity and creation of experimental framework for comparing machine translation techniques using open-source translation tools.
2021
Thesis deals with the translation module development which automates corpus-based translation. The translation module is a part of an adaptable corpus tool and is implemented as a separate microservice. This translation module provides for the linguist and translator the ability to translate texts with conveying their style. The translation module is domain-specific oriented which allows to convey text style better than public cloud translation services. In this research religious and historical texts were analyzed. Neural machine translation method was justified and used. Sequence to sequence Transformer model as a neural network model was chosen. All stages of text processing by the Transformer model which based on the Multi-Head Attention mechanism were analyzed. Software libraries and toolkits for the Sequence to sequence Transformer model were analyzed and chosen. Based on chosen software libraries implemented own Transformer model implementation. Developed model comprises text...
2016
Today the world is experiencing advanced technology on a full scale. Man is thus compelled to make use of this technology to develop machine translation as one of the means of transferring the cultural and scientific achievements of the various fields and disciplines from other languages to Arabic and vice versa. It is quite mandatory to pave the way for an efficient ground of cooperation among Arab researches, who should aim at obtaining advanced technology in the field of translation, especially during this booming period. Likewise, conveying world-wide scientific achievements in Arabic plays an essential role in establishing the slight but still ongoing endeavors that aim at the Arabization of various scientific terminologies. The present article attempts to elucidate the concept of machine translation, its objectives, its categories and types, its value in the current age, its position among other modern sciences and fields of research, and the attempts made by the authorities i...
Translation technologies constitute an important new field of interdisciplinary study lying midway between computer science and translation. Its development in the professional world will largely depend on its academic progress and the effective introduction of translation technologies in the translators training curriculum. In this paper different approaches to the subject are examined so as to provide us with a basis on which to conduct an internal analysis of the field of Translation technologies and to structure its content. Following criteria based on professional practice and on the idiosyncrasy of the computer tools and resources that play a part in translation activity, we present our definition of Translation technologies and the field classified in five blocks.
The translation of natural languages by machine, first dreamt of in the seventeenth century, has become a reality in the late twentieth. Computer programs are producing translations -not perfect translations, for that is an ideal to which no human translator can aspire; nor translations of literary texts, for the subtleties and nuances of poetry are beyond computational analysis; but translations of technical manuals, scientific documents, commercial prospectuses, administrative memoranda, medical reports. Machine translation is not primarily an area of abstract intellectual inquiry but the application of computer and language sciences to the development of systems answering practical needs.
2003
The multilingual machine translation system described in the first part of this paper demonstrates that the translation memory (TM) can be used in a creative way for making the translation process more automatic (in a way which in fact does not depend on the languages used). The MT system is based upon exploitation of syntactic similarities between more or less related natural languages. It currently covers the translation from Czech to Slovak, Polish and Lithuanian. The second part of the paper also shows that one of the most popular TM based commercial systems, TRADOS, can be used not only for the translation itself, but also for a relatively fast and natural method of evaluation of the translation quality of MT systems.
The interlingua approach to machine translation (MT) is characterized by the following two stages: 1) translation of the source text into an intermediate representation, an artificial language (interlingua) which is designed to capture the various types of meaning of the source text and 2) translation from the interlingua into the target text. Over the years a number of MT projects tried to develop interlinguabased systems. In these projects the amount of linguistic and encyclopaedic knowledge used to produce intermediate representations was quite limited. However, even at that level difficulties connected with encoding knowledge seemed overwhelming. The TRANSLATOR project at Colgate University benefits from recent developments in knowledge representation techniques. The text of its interlingua text reflects syntactic, lexical, contextual, discourse (including speech situation) and pragmatic meaning of the input This paper discusses the lexicon and grammar of the interlingua used in TRANSLATOR, and touches upon the structure of the bilingual (source language to interlingua) dictionaries. The actual compilation of the interlingua dictionary and additional knowledge bases is an empirical process during which modifications to the original formulations are expected to occur. At all times in the design process the authors were guided by the desire to make decisions that are 'literate' from the point of view of linguistic theory and the experience of knowledge representation in artificial intelligence.
2012
—Effort to access other language document leads to the development of machine translation system which involves lots of heterogeneous features and its implementations. Information professionals are widely used the advantages of machine translation for satisfying their user's needs. Machine Translation methods are different and each has its own benefits and drawback. No translation tools can generate an exact version of source language but gives gist of information which can utilize to find the type of information contained in the source text. Sometimes, it is necessary to perform post-editing by in-house linguistic after generating translation output with translation engine. This work explains various approaches used in machine translation process such as Dictionary based, Rule based, Corpus Based and Hybrid Translation methods. This paper concludes with the assumption that no perfect translation systems exist, even though Hybrid method is better than that of all available methods because it combines the advantages of various translation methods.
The inceptions of new technological aids, i.e. machine translation, that are at disposal of individual translators are becoming increasingly important to consolidate different strands in the domain of translation studies. To study the features of translated texts-including biblical, literary, and political-at the semantic level of processing, Google translation that is already functioning among a wide range of disciplines has been overarching such a sustained commitment to the task of translator in this study. Translation studies are therefore entangled with an array of interdisciplinary approaches to introduce the new areas of machine translation to theorists and specify the emerging algorithmic paths to computational linguists. The issues raised and developments outlined in this analytical study give a full rein to human involvement to provide remedial support to machine translation, particularly Google translation, and generate the impression of installing automated semantic level of processing of a variety of texts in line with the future wealth of ideas. . P. 1.1. The concept of translation Interestingly, the identification of different categories of translation is essential at the early stages to remove the unexpected ambiguities and uncommon pitfalls. In this regard, an eminent structuralist Roman Jakobson in his seminal paper On linguistic aspects of translation has brought up three interrelated categories of translation to the surface. The common type has been typically known as 'intra-lingual' translation, which hinges upon "rewording" or "rephrasing" an expression in the same language. As it is obvious, it primarily functions on the basis of the underlying structures and principles of a language to reframe the given utterance in a polished style at the expense of clarity and elaboration of the content. The "translation proper" which is virtually an offshoot of the second category of translation has been coined as 'inter-lingual' translation. This type of translation basically deals with the interplay between source language and target language. It actually involves an interdisciplinary approach to minimize the distance between the two languages through mutual correspondence between concepts and verbal modes of representation. The transmuted type which has been typically labelled as' inter-semiotic' translation relies on nonverbal channels of communication rather than verbal sign systems.
GAS Publisher, 2024
Modern translation requires translation technologies such as Computer-Aided Translation tools which eases the difficulties encountererd by translators. The goal of CAT tools is to to assist translators in increasing their productivity and improving the quality of their work. This article, highlights the need to have a foundation on which the translator undertakes a study of translation technology and its multiple approaches. Despite the advancement of technology, most translators are not yet familiar with the use of machines that support them to translate hence translators must have the knowledge of translation technology in order to achieve terminology management, consistency and speed in translating huge tasks. The research examined rigorously some fundamentals of Translation Technology by investigating and showing its genesis, definitions, concepts and classifications that support a translator to execute his task. The researcher applies descriptive approach and interpretative theory of translation. The research explored some fundamentals of translation technology that assist the translator in easing the task of the translation process. Finally, the researcher found out that there is an urgent need for translators to use modern technology, more especially translation technology that assist and facilitate the translation process. Some of these technologies include Computer-Assisted Translation tools, Terminology Management System, Translation Memory and Neural Machine Translation (which uses Artificial Intelligence) that is currently the best machine translation.
2011
Rule Based Machine Translation (RBMT) and Statistical Machine translation (SMT) have different approach in performing translation task. RBMT uses linguistic rule between two languages which is built manually by human in general, whereas SMT uses co-occurrence statistic of word in parallel corpora. We combine those different approaches into Indonesian-English Hybrid Machine Translation (HMT) system to get the advantage from both kind of information. Initially, Indonesian text is inputted into RBMT. Then, the output will be edited by SMT to generate the final translation of English text. SMT is capable to do this because on the training process, it uses RBMT's output (English) as source material and real translation (English) as target material. Unavailability of ready to use Indonesian-English RBMT system becomes a challenge to do this research. Our study shows that SMT still outperforms HMT by 8.01% in average.
Linguistik online, 2003
The translation process (and thus the training of future translators) is not only based upon the bilingual competence of the translator but also on his/her capacity to analyze the relations between the source text (ST) and target text (TT) in order to produce a translation ...
Ìnformacìjnì Tehnologì ì Zasobi Navčannâ, 2020
The anthropocosmic vector of modern Pedagogy and Linguistics requires development of such tools for future translators that enable as quick as possible processing of huge amounts of information with production of automatically determined frequencies, on the one hand. On the other hand, it demands minimization of the subjective influence of an individual researcher on the received results, giving a chance for detecting and analysing linguistic phenomena unnoticed earlier. Linguistic corpora are a state-of-the-art technology that can solve the outlined problem perfectly, for it opens a broad variety of practical and theoretical research options, and at the same time it is a didactic tool fulfilling purely didactic, cognitive, informative, formative, and testing / checking functions. Therefore, the use of linguistic corpora technology can be considered from two perspectives-learning to use corpora to translate and learning to translate using corpora. Corpora technology employment can enhance both objectivity and reliability of the results researchers obtain when processing language data, too. The application of corpus approach by translators-to-be gives an opportunity to study any language units in different speech genres in different types of discourse, as well as in various contexts in the corpus, without being hindered by the specificity of the studied linguistic unit. Translation students can search for discrete lexical / grammatical units, based on concordances, showing their functioning in different styles and areas of use. Moreover, parallel corpora provide ready solutions for the choice of translation models in certain conditions. The purpose of this article, stipulated by the relevance of the set problem, as well as the lack of ready parallel corpora in Ukraine, covers development of special methodological procedures and
2016
The Machine Translation has been a branch of Natural Language Processing, which comes under the broad area of Artificial Intelligence. Machine Translation system refers to computer software that translates text or voice from one natural language into another with or without human assistance. Worldwide, large number of machine translation systems have been developed using several approaches including humanassisted, rule-based, statistical, example-based, hybrid and agent based techniques. Among others, Statistical machine translation approach is by far the most widelystudied machine translation method in the field of machine translation. The multi-agent approach is a modern approach to handle complexity of the systems in past five years. This paper reviews existing machine translation approaches and systems including existing English to Sinhala machine translation systems.
Traditionally, all the translation work is done by individual translators separately. If they want to share translation expertise to the others, since all the translation knowledge and vocabulary are stored in their own computers, these can only be used by one-off user. Moreover, as the number of documents to be translated increases a lot nowadays, the translation task becomes impractical without the support of computer aided translation tools. As a result, the use of these tools, and their integration in the translation cycle has been one of the hottest topics in the translation community. Due to the fast development of computer technologies, networking technologies, and the fruitful results obtained from the research of Machine Translation (MT) field, computer aided translation systems are no more than that compared with the simple tools. Sophisticated translation systems may be implemented to use different MT technologies and engines, and they are able to run on different working environments and infrastructures. In this paper, a computer aided translation system based on multiple translation engines, including MT and Translation Memory, with a focus on the languages of Portuguese and Chinese is presented. Moreover, the architecture of the system is based on a Client-Server model and it has a centralized knowledge base for better management. The Portuguese-Chinese Translation (PCT) System is developed by the University of Macau.
Translation techniques are never getting old; translation is a classic method in the process of learning languages. The trigger under personal motto that NOT WORDS, BUT MEANING led to write this paper and we are also fully aware that people understand speeches, but not WORDS. This study investigates the use of translation method, technique, and structure in learning any languages (particularly Mongolian to English vice versa) by focusing on specialized or professional translations. The objectives of this study are: i. to try to introduce systematic approaches how to translate from source language to the targeted one, why the translation is playing in main role in languages, how the meanings are shown by words structurally and grammatically, ii. To give more simple ideas on grammatical structure and lexical families for translating materials tailored to the communication needs of students, being passionate for translations at the universities by combining cultural and language differences based on contrastive and comparative, parallel linguistic researches on translation. For this purpose, as the researcher and author of this academic paper, this is aimed for applying much easier and simpler ways to the students, beginner for sophisticated translations; so that instructors and learners at the universities may understand well on creating own much optimal translations. In general understanding of translations, this is a process of conveying the source meaning to the targeted language with the same ideas as informed. Certainly for translation, we need to have excellent knowledge of grammars, lexical families (word choice), sentence structures, order of context, and so forth, however, mother language is always fundamental influence to translate any speeches or documents. Hence, this academic paper is based on authentic cases and translation barriers of students at universities, targeting on how to have systematic approaches on written translations.
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