Foundations and tasks in Natural Language Processing

Definition and scope of natural language processing

Natural Language Processing (NLP) is the field of computer science focused on processing natural language information by computers. It is closely connected to artificial intelligence and also overlaps with areas such as information retrieval, knowledge representation, computational linguistics, and linguistics more broadly. In practice, NLP systems aim to convert between human language and machine-interpretable representations, enabling computers to work with text and speech. The scope of NLP includes several major processing tasks, such as speech recognition, text classification, natural language understanding, and natural language generation. NLP research and applications span multiple levels of language analysis—from basic processing like tokenization and morphological analysis to higher-level interpretation such as lexical and relational semantics, discourse understanding, and more complex applications that build on these subtasks. Overall, NLP covers both the methods used to analyze language and the end-to-end systems that perform language-related tasks for real-world use.

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Major NLP processing tasks overview

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