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In this paper, we present a novel adaptation method for intent classification using Boosting in a spoken language understanding system. The goal is adapting an existing model to a new target application, which is similar but may have different intents or intent distributions. Adaptation can also be employed for a single application where the intent distribution varies by time. We assume the target application has a small amount of labeled data. We also propose employing active learning todoi:10.1109/icassp.2005.1415045 dblp:conf/icassp/Tur05 fatcat:heatup3udjbttfmzspq7stiwhi