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In natural language understanding (NLU), a user utterance can be labeled differently depending on the domain or application (e.g., weather vs. calendar). Standard domain adaptation techniques are not directly applicable to take advantage of the existing annotations because they assume that the label set is invariant. We propose a solution based on label embeddings induced from canonical correlation analysis (CCA) that reduces the problem to a standard domain adaptation task and allows use of adoi:10.3115/v1/p15-1046 dblp:conf/acl/KimSSJ15 fatcat:clelwfbudvef7p2pbbrb5lov2a