Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
User interfaceIn the industrial design field of human–computer interaction, a user interface (UI) is the space where interactions between humans and machines occur. The goal of this interaction is to allow effective operation and control of the machine from the human end, while the machine simultaneously feeds back information that aids the operators' decision-making process. Examples of this broad concept of user interfaces include the interactive aspects of computer operating systems, hand tools, heavy machinery operator controls and process controls.
Uses of English verb formsThis article describes the uses of various verb forms in modern standard English language. This includes: Finite verb forms such as go, goes and went Nonfinite forms such as (to) go, going and gone Combinations of such forms with auxiliary verbs, such as was going and would have gone The uses considered include expression of tense (time reference), aspect, mood, modality and voice, in various configurations. For details of how inflected forms of verbs are produced in English, see English verbs.
Interlingual machine translationInterlingual machine translation is one of the classic approaches to machine translation. In this approach, the source language, i.e. the text to be translated is transformed into an interlingua, i.e., an abstract language-independent representation. The target language is then generated from the interlingua. Within the rule-based machine translation paradigm, the interlingual approach is an alternative to the direct approach and the transfer approach. In the direct approach, words are translated directly without passing through an additional representation.
MultilingualismMultilingualism is the use of more than one language, either by an individual speaker or by a group of speakers. It is believed that multilingual speakers outnumber monolingual speakers in the world's population. More than half of all Europeans claim to speak at least one language other than their mother tongue; but many read and write in one language. Multilingualism is advantageous for people wanting to participate in trade, globalization and cultural openness.
Auxiliary verbAn auxiliary verb (abbreviated ) is a verb that adds functional or grammatical meaning to the clause in which it occurs, so as to express tense, aspect, modality, voice, emphasis, etc. Auxiliary verbs usually accompany an infinitive verb or a participle, which respectively provide the main semantic content of the clause. An example is the verb have in the sentence I have finished my lunch. Here, the auxiliary have helps to express the perfect aspect along with the participle, finished.
Syntactic movementSyntactic movement is the means by which some theories of syntax address discontinuities. Movement was first postulated by structuralist linguists who expressed it in terms of discontinuous constituents or displacement. Some constituents appear to have been displaced from the position in which they receive important features of interpretation. The concept of movement is controversial and is associated with so-called transformational or derivational theories of syntax (such as transformational grammar, government and binding theory, minimalist program).
Function wordIn linguistics, function words (also called functors) are words that have little lexical meaning or have ambiguous meaning and express grammatical relationships among other words within a sentence, or specify the attitude or mood of the speaker. They signal the structural relationships that words have to one another and are the glue that holds sentences together. Thus they form important elements in the structures of sentences.
Evaluation of machine translationVarious methods for the evaluation for machine translation have been employed. This article focuses on the evaluation of the output of machine translation, rather than on performance or usability evaluation. Round-trip translation A typical way for lay people to assess machine translation quality is to translate from a source language to a target language and back to the source language with the same engine. Though intuitively this may seem like a good method of evaluation, it has been shown that round-trip translation is a "poor predictor of quality".
Semantic role labelingIn natural language processing, semantic role labeling (also called shallow semantic parsing or slot-filling) is the process that assigns labels to words or phrases in a sentence that indicates their semantic role in the sentence, such as that of an agent, goal, or result. It serves to find the meaning of the sentence. To do this, it detects the arguments associated with the predicate or verb of a sentence and how they are classified into their specific roles. A common example is the sentence "Mary sold the book to John.
