Natural Language Processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human-computer interaction. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural input; Natural language generation, that is,’ ‘computers creating or composing text in a way that simulates or mimics human speech, and Speech recognition, whereupon spoken input can be converted into machine-readable output.

NLP research draws upon methods from computer science, linguistics, and psychology. In the 1950s early work in NLP attempted to address problems with machine translation by looking at ways to automatically generate translations using grammatical rules encoded as software programs. This rule-based approach was extended in later years with statistical models which allowed for more generalizations across languages. These models were able to consider not just grammar but also word order and other factors which are important for deriving meaning from sentences.

With recent advances in neural networks that comprise the discipline of Neural Linguistic Programming also whose acronym is NLP, it has become possible to develop end-to-end models for various tasks such as machine translation directly from text without any need for handcrafted rules or feature engineering. These deep-learning approaches have shown very promising results on various benchmark datasets.

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