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Example-based 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] |
Machine Translation
Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation and large language models. History Origins The origins of machine translation can be traced back to the work of Al-Kindi, a ninth-century Arabic cryptographer who developed techniques for systemic language translation, including cryptanalysis, frequency analysis, and probability and statistics, which are used in modern machine translation. The idea of machine translation later appeared in the 17th century. In 1629, René Descartes proposed a universal language, with equivalent ideas in different tongues sharing one symbol. The idea of using digital computers for translation of natural languages was proposed as early as 1947 by England's A. D. Booth and Warr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adverb
An adverb is a word or an expression that generally modifies a verb, an adjective, another adverb, a determiner, a clause, a preposition, or a sentence. Adverbs typically express manner, place, time, frequency, degree, or level of certainty by answering questions such as ''how'', ''in what way'', ''when'', ''where'', ''to what extent''. This is called the adverbial function and may be performed by an individual adverb, by an adverbial phrase, or by an adverbial clause. Adverbs are traditionally regarded as one of the parts of speech. Modern linguists note that the term ''adverb'' has come to be used as a kind of "catch-all" category, used to classify words with various types of syntactic behavior, not necessarily having much in common except that they do not fit into any of the other available categories (noun, adjective, preposition, etc.). Functions The English word ''adverb'' derives (through French) from Latin ''adverbium'', from ''ad-'' ('to'), ''verbum'' ('word', 'ver ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Machine Translation
Statistical machine translation (SMT) is a machine translation approach 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, that superseded the previous rule-based approach that required explicit description of each and every linguistic rule, which was costly, and which often did not generalize to other languages. 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. Before the introduction of neural machine translation, it was by far the most widely studied machine translation method. Basis The idea b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence. It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics. Major tasks in natural language processing are speech recognition, text classification, natural-language understanding, natural language understanding, and natural language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, though at the time that was not articulated as a problem separate from artificial intelligence. The proposed test includes a task that involves the automated interpretation and generation of natural language ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Translation Memory
A translation memory (TM) is a database that stores "segments", which can be sentences, paragraphs or sentence-like units (headings, titles or elements in a list) that have previously been translated, in order to aid human translators. The translation memory stores the source text and its corresponding translation in language pairs called "translation units". Individual words are handled by terminology bases and are not within the domain of TM. Software programs that use translation memories are sometimes known as translation memory managers (TMM) or translation memory systems (TM systems, not to be confused with a translation management system (TMS), which is another type of software focused on managing the process of translation). Translation memories are typically used in conjunction with a dedicated computer-assisted translation (CAT) tool, word processing program, terminology management systems, multilingual dictionary, or even raw machine translation output. Research ind ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Programming By Example
In computer science, programming by example (PbE), also termed programming by demonstration or more generally as demonstrational programming, is an end-user development technique for machine learning, teaching a computer new behavior by demonstrating actions on concrete examples. The system records user actions and infers a generalized Computer program, program that can be used on new examples. PbE is intended to be easier to do than traditional computer programming, which generally requires learning and using a programming language. Many PbE systems have been developed as research prototypes, but few have found widespread real-world application. More recently, PbE has proved to be a useful paradigm for creating scientific work-flows. PbE is used in two independent clients for the BioMOBY protocolSeahawkanGbrowse moby Also the programming by demonstration (PbD) term has been mostly adopted by robotics researchers for teaching new behaviors to the robot through a physical demonstra ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hindustani Language
Hindustani is an Indo-Aryan language spoken in North India and Pakistan as the lingua franca of the region. It is also spoken by the Deccani people, Deccani-speaking community in the Deccan plateau. Hindustani is a pluricentric language with two Standard language, standard Register (sociolinguistics), registers, known as Hindi (Sanskritisation (linguistics), Sanskritised register written in the Devanagari script) and Urdu (Persianization, Persianized and Arabization, Arabized register written in the Perso-Arabic script) which serve as official languages of India and Pakistan, respectively. Thus, it is also called Hindi–Urdu. Colloquial registers of the language fall on a spectrum between these standards. In modern times, a third variety of Hindustani with significant English influences has also appeared, which is sometimes called Hinglish or Urdish.Salwathura, A. N.Evolutionary development of ‘hinglish’language within the Indian sub-continent. ''International Journal ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Particle (grammar)
In grammar, the term ''particle'' (abbreviated ) has a traditional meaning, as a part of speech that cannot be inflected, and a modern meaning, as a function word (functor) associated with another word or phrase in order to impart meaning. Although a particle may have an intrinsic meaning and may fit into other grammatical categories, the fundamental idea of the particle is to add context to the sentence, expressing a mood or indicating a specific action. In English, for example, the phrase "oh well" has no purpose in speech other than to convey a mood. The word "up" would be a particle in the phrase "look up" (as in "look up this topic"), implying that one researches something rather than that one literally gazes skywards. Many languages use particles in varying amounts and for varying reasons. In Hindi, they may be used as honorifics, or to indicate emphasis or negation. In some languages, they are clearly defined; for example, in Chinese, there are three types of (; ): ''struct ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Preposition
Adpositions are a part of speech, class of words used to express spatial or temporal relations (''in, under, towards, behind, ago'', etc.) or mark various thematic relations, semantic roles (''of, for''). The most common adpositions are prepositions (which precede their complement) and postpositions (which follow their complement). An adposition typically combines with a noun phrase, this being called its complement (grammar), complement, or sometimes object (grammar), object. English language, English generally has prepositions rather than postpositions – words such as ''in, under'' and ''of'' precede their objects, such as "in England", "under the table", "of Jane" – although there are a few exceptions including ''ago'' and ''notwithstanding'', as in "three days ago" and "financial limitations notwithstanding". Some languages that use a different word order have postpositions instead (like Turkic languages) or have both types (like Finnish language, Finnish). The phrase form ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phrasal Verb
In the traditional grammar of Modern English, a phrasal verb typically constitutes a single semantic unit consisting of a verb followed by a particle (e.g., ''turn down'', ''run into,'' or ''sit up''), sometimes collocated with a preposition (e.g., ''get together with'', ''run out of,'' or ''feed off of''). Phrasal verbs ordinarily cannot be understood based upon the meanings of the individual parts alone but must be considered as a whole: the meaning is non- compositional and thus unpredictable. Phrasal verbs are differentiated from other classifications of multi-word verbs and free combinations by the criteria of idiomaticity, replacement by a single verb, ''wh''-question formation and particle movement. Terminology In 1900, Frederick Schmidt referred to particle verbs in the Middle English writings of Reginald Pecock as "phrasal verbs", though apparently without intending it as a technical term. The term was popularized by Logan Pearsall Smith in ''Words and Idioms'' (1925 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Corpus
In linguistics and natural language processing, a corpus (: corpora) or text corpus is a dataset, consisting of natively digital and older, digitalized, language resources, either annotated or unannotated. Annotated, they have been used in corpus linguistics for statistical statistical hypothesis testing, hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory. Overview A corpus may contain texts in a single language (''monolingual corpus'') or text data in multiple languages (''multilingual corpus''). In order to make the corpora more useful for doing linguistic research, they are often subjected to a process known as annotation. An example of annotating a corpus is part-of-speech tagging, or ''POS-tagging'', in which information about each word's part of speech (verb, noun, adjective, etc.) is added to the corpus in the form of ''tags''. Another example is indicating the Lemma (morphology), lemma (base) form of each word ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rule-based Machine Translation
Rule-based machine translation (RBMT) is a classical approach of machine translation systems based on linguistic information about source and target languages. Such information is retrieved from (unilingual, bilingual or multilingual) dictionaries and grammars covering the main semantic, morphological, and syntactic regularities of each language. Having input sentences, an RBMT system generates output sentences on the basis of analysis of both the source and the target languages involved. RBMT has been progressively superseded by more efficient methods, particularly neural machine translation. 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 * Japanese MT systems Today, other common RBMT systems include: * Apertium * GramTrans Types of RBMT There are three different types of rule-based machine translation systems: # Direct Systems ( Dictionary Based M ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
