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Dictionary-based Machine Translation
Machine translation can use a method based on dictionary entries, which means that the words will be translated as a dictionary does – word by word, usually without much correlation of meaning between them. Dictionary lookups may be done with or without morphological analysis or lemmatisation. While this approach to machine translation is probably the least sophisticated, dictionary-based machine translation is ideally suitable for the translation of long lists of phrases on the subsentential (i.e., not a full sentence) level, e.g. inventories or simple catalogs of products and services. It can also be used to expedite manual translation, if the person carrying it out is fluent in both languages and therefore capable of correcting syntax and grammar. LMT LMT, introduced around 1990, is a Prolog-based machine-translation system that works on specially made bilingual dictionaries, such as the Collins English-German (CEG), which have been rewritten in an indexed form which is eas ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Translation Arrow
Translation is the communication of the meaning of a source-language text by means of an equivalent target-language text. The English language draws a terminological distinction (which does not exist in every language) between ''translating'' (a written text) and ''interpreting'' (oral or signed communication between users of different languages); under this distinction, translation can begin only after the appearance of writing within a language community. A translator always risks inadvertently introducing source-language words, grammar, or syntax into the target-language rendering. On the other hand, such "spill-overs" have sometimes imported useful source-language calques and loanwords that have enriched target languages. Translators, including early translators of sacred texts, have helped shape the very languages into which they have translated. Because of the laboriousness of the translation process, since the 1940s efforts have been made, with varying degrees o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multilingual Information Retrieval
Cross-language information retrieval (CLIR) is a subfield of information retrieval dealing with retrieving information written in a language different from the language of the user's query. The term "cross-language information retrieval" has many synonyms, of which the following are perhaps the most frequent: cross-lingual information retrieval, translingual information retrieval, multilingual information retrieval. The term "multilingual information retrieval" refers more generally both to technology for retrieval of multilingual collections and to technology which has been moved to handle material in one language to another. The term Multilingual Information Retrieval (MLIR) involves the study of systems that accept queries for information in various languages and return objects (text, and other media) of various languages, translated into the user's language. Cross-language information retrieval refers more specifically to the use case where users formulate their information nee ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Machine Translation
Statistical machine translation (SMT) is a machine translation paradigm where translations are generated on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora. The statistical approach contrasts with the rule-based approaches to machine translation as well as with example-based machine translation, and has more recently been superseded by neural machine translation in many applications (see this article's final section). The first ideas of statistical machine translation were introduced by Warren Weaver in 1949, including the ideas of applying Claude Shannon's information theory. Statistical machine translation was re-introduced in the late 1980s and early 1990s by researchers at IBM's Thomas J. Watson Research Center and has contributed to the significant resurgence in interest in machine translation in recent years. Before the introduction of neural machine translation, it was by far the most widely studied machine translati ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rule-based Machine Translation
Rule-based machine translation (RBMT; "Classical Approach" of MT) is machine translation systems based on linguistic information about source and target languages basically retrieved from (unilingual, bilingual or multilingual) dictionaries and grammars covering the main semantic, morphological, and syntactic regularities of each language respectively. Having input sentences (in some source language), an RBMT system generates them to output sentences (in some target language) on the basis of morphological, syntactic, and Semantic analysis (computational), semantic analysis of both the source and the target languages involved in a concrete translation task. History The first RBMT systems were developed in the early 1970s. The most important steps of this evolution were the emergence of the following RBMT systems: * Systran (http://www.systran.de/) * Japanese MT systems (http://aamt.info/english/mtsys.htm, http://www.wtec.org/loyola/ar93_94/mt.htm) Today, other common RBMT syste ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Machine Translation
Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model. Properties They require only a fraction of the memory needed by traditional statistical machine translation (SMT) models. Furthermore, unlike conventional translation systems, all parts of the neural translation model are trained jointly (end-to-end) to maximize the translation performance. History Deep learning applications appeared first in speech recognition in the 1990s. The first scientific paper on using neural networks in machine translation appeared in 2014. This year Bahdanau et al.Bahdanau D, Cho K, Bengio Y. Neural machine translation by jointly learning to align and translate. In: Proceedings of the 3rd International Conference on Learning Representations; 2015 May 7–9; San Diego, USA; 2015. and Sutskever et al.Sutskever I, Vinyals O, Le QV. Sequ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Language Industry
The language industry is the sector of activity dedicated to facilitating multilingual communication, both oral and written. According to the European Commission's Directorate-General of Translation, the language industry comprises the activities of translation, interpreting, subtitling and dubbing, software and website globalisation, language technology tools development, international conference organisation, language teaching and linguistic consultancy. According to the Canadian Language Industry Association, this sector comprises translation (with interpreting, subtitling and localisation), language training and language technologies. The European Language Industry Association limits the sector to translation, localisation, internationalisation and globalisation. An older, perhaps outdated view confines the language industry to computerised language processing and places it within the information technology industry. An emerging view expands this sector to include edi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Example-based Machine Translation
Example-based machine translation (EBMT) is a method of machine translation often characterized by its use of a bilingual corpus with parallel texts as its main knowledge base at run-time. It is essentially a translation by analogy and can be viewed as an implementation of a case-based reasoning approach to machine learning. Translation by analogy At the foundation of example-based machine translation is the idea of translation by analogy. When applied to the process of human translation, the idea that translation takes place by analogy is a rejection of the idea that people translate sentences by doing deep linguistic analysis. Instead, it is founded on the belief that people translate by first decomposing a sentence into certain phrases, then by translating these phrases, and finally by properly composing these fragments into one long sentence. Phrasal translations are translated by analogy to previous translations. The principle of translation by analogy is encoded to example-b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Language Detection
In natural language processing, language identification or language guessing is the problem of determining which natural language given content is in. Computational approaches to this problem view it as a special case of text categorization, solved with various statistical methods. Overview There are several statistical approaches to language identification using different techniques to classify the data. One technique is to compare the compressibility of the text to the compressibility of texts in a set of known languages. This approach is known as mutual information based distance measure. The same technique can also be used to empirically construct family trees of languages which closely correspond to the trees constructed using historical methods. Mutual information based distance measure is essentially equivalent to more conventional model-based methods and is not generally considered to be either novel or better than simpler techniques. Another technique, as descr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parallel Corpora
A parallel text is a text placed alongside its translation or translations. Parallel text alignment is the identification of the corresponding sentences in both halves of the parallel text. The Loeb Classical Library and the Clay Sanskrit Library are two examples of dual-language series of texts. Reference Bibles may contain the original languages and a translation, or several translations by themselves, for ease of comparison and study; Origen's Hexapla (Greek for "sixfold") placed six versions of the Old Testament side by side. A famous example is the Rosetta Stone, whose discovery allowed the Ancient Egyptian language to begin being deciphered. Large collections of parallel texts are called parallel corpora (see text corpus). Alignments of parallel corpora at sentence level are prerequisite for many areas of linguistic research. During translation, sentences can be split, merged, deleted, inserted or reordered by the translator. This makes alignment a non-trivial task. P ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Translation
Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another. On a basic level, MT performs mechanical substitution of words in one language for words in another, but that alone rarely produces a good translation because recognition of whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalent words in another language, and many words have more than one meaning. Solving this problem with corpus statistical and neural techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and the isolation of anomalies. Current machine translation software often allows for customizat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Linguistics
Computational linguistics is an Interdisciplinarity, interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others. Sub-fields and related areas Traditionally, computational linguistics emerged as an area of artificial intelligence performed by computer scientists who had specialized in the application of computers to the processing of a natural language. With the formation of the Association for Computational Linguistics (ACL) and the establishment of independent conference series, the field consolidated during the 1970s and 1980s. The Association for Computational Linguistics defines computational linguistics as: The term "comp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lexical Semantics
Lexical semantics (also known as lexicosemantics), as a subfield of linguistic semantics, is the study of word meanings.Pustejovsky, J. (2005) Lexical Semantics: Overview' in Encyclopedia of Language and Linguistics, second edition, Volumes 1-14Taylor, J. (2017) Lexical Semantics'. In B. Dancygier (Ed.), The Cambridge Handbook of Cognitive Linguistics (Cambridge Handbooks in Language and Linguistics, pp. 246-261). Cambridge: Cambridge University Press. It includes the study of how words structure their meaning, how they act in grammar and compositionality, and the relationships between the distinct senses and uses of a word. The units of analysis in lexical semantics are lexical units which include not only words but also sub-words or sub-units such as affixes and even compound words and phrases. Lexical units include the catalogue of words in a language, the lexicon. Lexical semantics looks at how the meaning of the lexical units correlates with the structure of the language or s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
