natural language processing (NLP)

Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and human language. It encompasses the development of algorithms and systems that enable computers to understand, interpret, and generate human language in a way that is both meaningful and useful.

NLP combines computational linguistics, which is rule-based modeling of human language, with statistical, machine learning, and deep learning models. The goal is to enable computers to process and analyze large amounts of natural language data to perform tasks such as translation, sentiment analysis, and question answering[1][2][4].

NLP is used in various applications that we interact with daily, such as voice-operated GPS systems, digital assistants, speech-to-text software, and customer service chatbots. It also plays a crucial role in enterprise solutions, helping to streamline business operations, increase productivity, and automate complex processes[1].

The tasks involved in NLP include word segmentation, stemming and lemmatization, tokenization, semantic reasoning, and more. These tasks help break down text and speech into components that can be more easily analyzed by computers. NLP technologies can also involve natural language understanding (NLU), which focuses on comprehending the intent behind sentences, and natural language generation (NLG), which is about producing human-like text from data[1][2].

NLP has evolved from hand-coded, rules-based systems to more sophisticated models that use statistical approaches and deep learning to process and make sense of language. These advancements have allowed NLP to handle the nuances and complexities of human language, such as idioms, metaphors, and varying sentence structures[1][2].

In summary, NLP is a critical technology in AI that gives computers the ability to understand, manipulate, and generate human language, enabling them to perform tasks that require the comprehension of language and its contextual nuances[1][2][4].

See also: natural language understanding (NLU), natural language generation (NLG)

Citations:

[1] https://www.ibm.com/topics/natural-language-processing

[2] https://en.wikipedia.org/wiki/Natural_language_processing

[3] https://en.wikipedia.org/wiki/Neuro-linguistic_programming

[4] https://aws.amazon.com/what-is/nlp/

[5] https://anlp.org/knowledge-base/definition-of-nlp

[6] https://www.coursera.org/articles/natural-language-processing

[7] https://www.oracle.com/artificial-intelligence/what-is-natural-language-processing/

[8] https://cloud.google.com/learn/what-is-natural-language-processing