Naturallanguage

Natural language refers to the set of human languages used for everyday communication, including spoken, signed, and written forms. It contrasts with formal or artificial languages such as programming or mathematical notations. The study of natural language spans multiple disciplines, including linguistics, cognitive science, and computer science, and seeks to describe how language is structured, learned, and used.

Natural language is composed of levels such as phonology, morphology, syntax, semantics, and pragmatics. Phonology deals with sound patterns, morphology with word formation, syntax with grammatical structure, semantics with meaning, and pragmatics with context and use. Language is highly systematic yet highly variable, often featuring ambiguity, polysemy, and context-dependent interpretation.

Historically, linguistics laid the groundwork for understanding language structure, while the field of computational linguistics and later natural language processing (NLP) developed methods for machines to process language. Milestones include grammars, machine translation, speech recognition, and corpus-based analysis, leading to modern neural methods trained on large text datasets.

Applications of natural language technology include voice assistants, machine translation, information extraction, sentiment analysis, text summarization, question answering, and chatbots. These systems rely on representations of language, such as tokens, embeddings, parse trees, or semantic graphs, and on learning algorithms ranging from rule-based systems to statistical models and deep neural networks.

Challenges remain, including ambiguity, multilinguality, cultural and linguistic variation, data bias, and the need for high-quality annotations. Data sparsity for low-resource languages and the quality of training data can affect performance and fairness. Research explores unsupervised and semi-supervised learning, transfer learning, multilingual models, and evaluation frameworks that capture real-world usefulness, safety, and interpretability in language technologies.

See also linguistics, computational linguistics, natural language processing.