Computational linguistics

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The use of computers to analyze and model human language, including natural language processing and machine translation.

Linguistics: The study of language and its structure, including syntax, semantics, phonology, and morphology.
Computer Science: The study of computation and algorithms, including programming languages, data structures, and databases.
Machine Learning: The study of algorithms that enable computers to learn patterns and make predictions from data.
Natural Language Processing (NLP): The study of computational methods for analyzing and manipulating human language, including text processing, speech recognition, and machine translation.
Artificial Intelligence (AI): The study of machines that can perform tasks that would ordinarily require human intelligence, including cognitive modeling and reasoning.
Evolutionary Biology: The study of the origin and evolution of species, including genetics, natural selection, and adaptation.
Cognitive Science: The study of the brain and its computational processes, including perception, memory, and language.
Statistics: The study of mathematical methods for collecting, analyzing, and interpreting data.
Information Theory: The study of how information is created, transmitted, and processed, including entropy, compression, and error correction.
Corpus Linguistics: The study of language as it is used in real-life contexts by collecting and analyzing large amounts of textual data.
Semiotics: The study of signs and symbols, including how they are used in language and communication.
Psycholinguistics: The study of how people learn, use, and comprehend language, including language acquisition and language processing.
Linguistic Anthropology: The study of how language interacts with culture and society, including language variation and change.
Computational Neuroscience: The study of how the brain processes information and generates behavior, including neural networks and cognitive architectures.
Algorithmic Game Theory: The study of how rational agents interact in a strategic environment, including game theory and mechanism design.
Natural Language Processing (NLP): The study of how computers can be used to process and analyze natural language data, such as text or speech.
Machine Translation: The study of how to translate between languages using computers.
Speech Recognition and Synthesis: The study of how computers can recognize and produce human speech.
Computational Semantics: The study of how meaning can be represented and processed in computational systems.
Computational Pragmatics: The study of how meaning can be derived from context in computational systems.
Corpus Linguistics: The study of how to analyze large collections of linguistic data, such as text corpora.
Computational Morphology: The study of how to analyze the structure of words in computational systems.
Computational Syntax: The study of how to analyze the structure of sentences in computational systems.
Computational Phonology: The study of how to analyze the sound patterns of language in computational systems.
Sentiment Analysis: The study of how to analyze the attitudes and emotions expressed in natural language text.
Text Mining: The study of how to extract useful information from large amounts of natural language text.
Information Extraction: The study of how to identify and extract specific pieces of information from natural language text.
Question Answering: The study of how to automatically provide answers to questions posed in natural language.
Language Generation: The study of how to automatically generate natural language text, such as for chatbots or automated writing systems.
Discourse Analysis: The study of how language is used in longer, coherent pieces of text, such as conversations or written documents.
- "Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions."
- "Computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others."
- "Since the 2020s, computational linguistics has become a near-synonym of either natural language processing or language technology."
- "Deep learning approaches, such as large language models, outperform the specific approaches previously used in the field."
- "Computational linguistics is concerned with the computational modelling of natural language."
- "Linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology, and neuroscience."
- "Computational approaches are studied to find appropriate solutions to linguistic questions."
- "Computational linguistics draws upon linguistics, computer science, and artificial intelligence."
- "Cognitive science, cognitive psychology, and psycholinguistics."
- "Philosophy is one of the disciplines that computational linguistics draws upon."
- "Deep learning approaches, such as large language models, outperform the specific approaches previously used in the field."
- "Since the 2020s, computational linguistics has become a near-synonym of either natural language processing or language technology."
- "Computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology, and neuroscience."
- "Computational linguistics draws upon... neuroscience."
- No direct quote provided.
- "Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language."
- "Deep learning approaches, such as large language models, outperform the specific approaches previously used in the field."
- No direct quote provided.
- "Computational linguistics is concerned with the computational modelling of natural language."
- "Since the 2020s, computational linguistics has become a near-synonym of either natural language processing or language technology, with deep learning approaches, such as large language models, outperforming the specific approaches previously used in the field."