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Recently, we have proposed a novel fast adaptation method for the hybrid DNN-HMM models in speech recognition  . This method relies on learning an adaptation NN that is capable of transforming input speech features for a certain speaker into a more speaker independent space given a suitable speaker code. Speaker codes are learned for each speaker during adaptation. The whole multi-speaker training dataset is used to learn the adaptation NN weights. Our previous work has shown that thisdoi:10.21437/interspeech.2013-336 fatcat:tw6y4pdgkvaefmxskrr7rypwvy