Intent recognition is the natural-language-processing task of inferring a user’s underlying goal or desired action from an utterance, query, or interaction. It maps free-form input to a discrete set of intents and extracts associated parameters, forming the comprehension layer of conversational systems. Accurate intent recognition is what lets chatbots and voice assistants route requests to the correct skill or response.
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- Classical pipelines pair intent classifiers with slot-filling for entity extraction; modern systems use transformer encoders or large language models that jointly interpret intent and context. Disambiguation and out-of-scope detection are key to robust dialogue management.