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With James H. Martin, he wrote the textbook Speech and Language Processing: An Introduction to Natural Language Processing, Speech Recognition, and Computational Linguistics; Roger Schank – introduced the conceptual dependency theory for natural-language understanding. [23] Jean E. Fox Tree – Alan Turing – originator of the Turing Test.
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.
In neuroscience and psychology, the term language center refers collectively to the areas of the brain which serve a particular function for speech processing and production. [1] Language is a core system that gives humans the capacity to solve difficult problems and provides them with a unique type of social interaction . [ 2 ]
Natural Language Processing with Python. O'Reilly Media. ISBN 978-0-596-51649-9. Daniel Jurafsky and James H. Martin (2008). Speech and Language Processing, 2nd edition. Pearson Prentice Hall. ISBN 978-0-13-187321-6. Mohamed Zakaria KURDI (2016). Natural Language Processing and Computational Linguistics: speech, morphology, and syntax, Volume 1 ...
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.
Deep linguistic processing is a natural language processing framework which draws on theoretical and descriptive linguistics. It models language predominantly by way of theoretical syntactic/semantic theory (e.g. CCG , HPSG , LFG , TAG , the Prague School ).
Effective natural language processing systems and text segmentation tools usually operate on text in specific domains and sources. As an example, processing text used in medical records is a very different problem than processing news articles or real estate advertisements.
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.