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Statistical machine translation
ACM Computing Surveys, 2008Statistical machine translation (SMT) treats the translation of natural language as a machine learning problem. By examining many samples of human-produced translation, SMT algorithms automatically learn how to translate. SMT has made tremendous strides in less than two decades, and new ideas are constantly introduced.
Adam Lopez
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MACHINE TRANSLATION AND MACHINE‐AIDED TRANSLATION
Journal of Documentation, 1978The recent report for the Commission of the European Communities on current multilingual activities in the field of scientific and technical information and the 1977 conference on the same theme both included substantial sections on operational and experimental machine translation systems, and in its Plan of action the Commission announced its ...
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Evaluation of machine translation
Proceedings of the International Conference & Workshop on Emerging Trends in Technology - ICWET '11, 2011Machine Translation (MT) refers to the use of a machine for performing translation task which converts text or speech from one Natural Language (NL) into another Natural Language. Machine Translation is an important technology for localization, and is particularly relevant in a linguistically diverse country like India.
Manisha Sharma, G. N. Purohit
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Machine Translation For Machines
2021Traditionally, Machine Translation (MT) systems are developed by targeting fluency (i.e. output grammaticality) and adequacy (i.e. semantic equivalence with the source text) criteria that reflect the needs of human end-users. However, recent advancements in Natural Language Processing (NLP) and the introduction of NLP tools in commercial services have ...
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A SOMAgent for machine translation
Expert Systems with Applications, 2010This work describes a method that uses artificial neural networks, specially a self-organising map (SOM), to determine the correct meaning of a word. By using a distributed architecture, we take advantages of the parallelism in the different levels of the natural language processing system, for modeling a community of conceptually autonomous agents ...
Vivian F. López Batista +2 more
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Proceedings of the workshop on Speech and Natural Language - HLT '90, 1990
Machine translation (MT) remains the paradigm task for natural language processing (NLP) since its inception in the 1950s. Unless NLP can succeed with the central task of machine translation, it cannot be considered successful as a field. We maintain that the most profitable approach to MT at the present time is an interlingual and modular one.
Yorick Wilks +4 more
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Machine translation (MT) remains the paradigm task for natural language processing (NLP) since its inception in the 1950s. Unless NLP can succeed with the central task of machine translation, it cannot be considered successful as a field. We maintain that the most profitable approach to MT at the present time is an interlingual and modular one.
Yorick Wilks +4 more
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Journal of Intelligent & Fuzzy Systems, 2017
Machine Translation (MT) requires a large amount of linguistic resources, which leads current MT systems to leaving unknown words untranslated. This can be annoying for end users, as they might not understand at all such untranslated words. However, most language families share a common vocabulary, therefore this knowledge can be leveraged to produce ...
Luis A. Leiva, Vicent Alabau
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Machine Translation (MT) requires a large amount of linguistic resources, which leads current MT systems to leaving unknown words untranslated. This can be annoying for end users, as they might not understand at all such untranslated words. However, most language families share a common vocabulary, therefore this knowledge can be leveraged to produce ...
Luis A. Leiva, Vicent Alabau
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2015
The goal of machine translation (MT) is to translate text from one natural language to another. Linguistic properties of the languages involved, and rich morphology in particular, play an important role in the difficulty of the task. After a brief survey of history of MT and morphologically rich languages (MRLs), the whole ‘MT pipeline’ is introduced,
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The goal of machine translation (MT) is to translate text from one natural language to another. Linguistic properties of the languages involved, and rich morphology in particular, play an important role in the difficulty of the task. After a brief survey of history of MT and morphologically rich languages (MRLs), the whole ‘MT pipeline’ is introduced,
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The outlook for machine translation
Papers presented at the May 3-5, 1960, western joint IRE-AIEE-ACM computer conference on - IRE-AIEE-ACM '60 (Western), 1960The idea of using electronic digital computers for language translation seems to have arisen about 1946; it was first brought to widespread attention in a memorandum by Warren Weaver in 1949. Today there are about a dozen projects in the United States devoted to machine translation, mostly translation from Russian to English.
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2006
Machine translation – the use of computers to translate automatically among human languages – is an alluring prospect, one that for more than 50 years has fascinated researchers, inspired idealists and opportunists, and provoked unease among professional translators. This article gives a broad survey of this diverse and active field.
Isabelle, P., Foster, G.
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Machine translation – the use of computers to translate automatically among human languages – is an alluring prospect, one that for more than 50 years has fascinated researchers, inspired idealists and opportunists, and provoked unease among professional translators. This article gives a broad survey of this diverse and active field.
Isabelle, P., Foster, G.
openaire +2 more sources