A technique used in Natural Language Processing (NLP) that predicts the next word in a sentence to help systems write and translate text that sounds natural and makes sense.
Language modeling is the process of assigning probabilities to sequences of words in a text. It predicts which words are likely to come next based on the context. This technique helps computers understand and generate natural language by capturing patterns in text.
Language models support various localization tasks by providing context to translations, making machine translation outputs more fluent and accurate. They help check grammar, style, and tone, and can improve the quality of suggestions offered to human translators. They are essential for many natural language processing tasks like autocomplete, spell checking, and translation memory suggestions.
Language modeling stands at the heart of modern language technologies, driving advances in machine translation, voice assistants, and multilingual content. Its ability to predict word sequences and capture context makes it invaluable for both everyday applications and specialized linguistic tasks, supporting developers, linguists, and localization specialists alike.