A natural language, also called an ordinary language, is any spoken or signed language that develops organically within a human community. It emerges without conscious premeditation and is subject to replication across generations, regional expansion or contraction, and gradual internal and structural changes. The vast majority of languages in the world are natural languages, encompassing both standard dialects with high social prestige and nonstandard or vernacular dialects. Even an official language with a regulating academy, such as Standard French overseen by the Académie Française, remains classified as a natural language in fields like Natural language processing, because its prescriptive aspects do not make it regulated enough to be considered a constructed or controlled language. Linguists broadly view writing as a static visual representation of a particular natural language, though in highly literate modern societies, writing itself is also subject to natural processes of change.
Excluded from the definition are artificial and constructed languages, such as those developed for fiction; languages of formal logic, including computer programming languages; and non-human communication systems in nature, such as whale vocalizations or honey bees' waggle dance. Academic consensus holds that key features prevent animal communication systems from being classified as languages at all. Certain human communication systems with no native speakers, sometimes used in cross-cultural contexts, are also not natural languages.
Characteristics and Evolution
Natural languages are distinguished by their organic emergence and continuous evolution. They change through fluctuations in vocabulary and syntax, incrementally improving human communication. This process occurs without central planning, driven by everyday use across diverse communities. For instance, a pidgin, which arises from contact between groups speaking different languages and is not considered a full language, can develop into a stable creole language over a relatively short period. A creole such as Haitian Creole has its own grammar, vocabulary, and literature, and is spoken by over 10 million people worldwide, serving as one of the two official languages of the Republic of Haiti. This synthesis of pre-existing natural languages illustrates how natural languages can standardize organically.
Controlled Natural Languages
Controlled natural languages are subsets of natural languages whose grammars and dictionaries have been restricted to reduce ambiguity and complexity. This may be achieved by decreasing usage of superlative or adverbial forms, or irregular verbs. Typical purposes include aiding understanding by non-native speakers or easing computer processing. An example of a widely used controlled natural language is Simplified Technical English, originally developed for aerospace and avionics industry manuals. These systems retain the core vocabulary and structure of a natural language but impose constraints to serve specific practical needs.
Relationship to Constructed Languages
International auxiliary languages such as Esperanto and Interlingua are constructed, not natural, with the possible exception of true native speakers of such languages. Esperanto was created by Polish ophthalmologist L. L. Zamenhof in the late 19th century, in deliberate contrast to natural languages that evolve organically. As of 1996, there were 350 attested families with one or more native speakers of Esperanto, indicating some degree of naturalization among a small population. Latino sine flexione, another international auxiliary language, is no longer widely spoken. The distinction remains important in linguistics and Natural-language understanding, where natural languages are the primary object of study.
Role in Technology
Natural languages are central to Artificial intelligence and Machine learning research. Natural language processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. Modern approaches often use neural networks and transformer architectures, which power systems like large language models. These models are trained on vast amounts of natural language text, learning patterns of syntax and semantics. Related techniques include Masked Language Modeling and Causal Language Modeling, which help models predict and generate text. The field also addresses challenges in Cross-language information retrieval, where natural language differences complicate search and translation. Despite advances, natural language remains complex due to its ambiguity, cultural context, and constant evolution, posing ongoing challenges for Natural-language understanding systems.
See Also
- History of natural language processing - Development of computational approaches to language
- Natural Questions - A dataset for question answering in natural language
- Vision-language model - Models that combine visual and linguistic understanding
- Generative AI - AI systems that produce natural language content