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The methods of neuro-linguistic programming are the specific techniques used to perform and teach neuro-linguistic programming, [1] [2] which teaches that people are only able to directly perceive a small part of the world using their conscious awareness, and that this view of the world is filtered by experience, beliefs, values, assumptions, and biological sensory systems.
NLP posits that consciousness can be divided into conscious and unconscious components. The part of our internal representations operating outside our direct awareness is referred to as the "unconscious mind". [j] Finally, NLP uses a method of learning called "modeling", designed to replicate expertise in any field.
Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program. Natural language programming is not to be mixed up with ...
Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP) that is concerned with building systems that automatically answer questions that are posed by humans in a natural language. [1]
Google Neural Machine Translation (GNMT) was a neural machine translation (NMT) system developed by Google and introduced in November 2016 that used an artificial neural network to increase fluency and accuracy in Google Translate.
] NLP proponents also found that pacing and leading the various cues tended to build rapport, and allowed people to communicate more effectively. Certain studies suggest that using similar representational systems to another person can help build rapport [ 15 ] whilst other studies have found that merely mimicking or doing so in isolation is ...
It is the dominant approach today [1]: 293 [2]: 1 and can produce translations that rival human translations when translating between high-resource languages under specific conditions. [3] However, there still remain challenges, especially with languages where less high-quality data is available, [ 4 ] [ 5 ] [ 1 ] : 293 and with domain shift ...
BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translation, the better it is" – this is the central idea behind BLEU.
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