Computational linguistics differs from traditional linguistics in its methods and applications. While traditional linguistics focuses on analyzing language from a ...
Computational linguistics differs from traditional linguistics in its methods and applications. While traditional linguistics focuses on analyzing language from a theoretical or descriptive perspective—such as syntax, phonology, and semantics—computational linguistics applies computational methods to model and process language data.
The key difference lies in the tools and goals: traditional linguists often work with manual analysis and theory-building, whereas computational linguists use algorithms, corpora, and machine learning to develop systems like speech recognition, machine translation, or chatbots.
Despite these differences, the two fields strongly support each other. Computational linguistics relies on linguistic theories to design accurate models, while traditional linguistics benefits from computational tools that can handle large-scale data analysis and test hypotheses more efficiently. Together, they contribute to a deeper understanding of language and its practical applications in technology.