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The OpenKWS14 keyword search evaluation is one of the most challenging and influential evaluations in the field of speech recognition. Its goal is to build a high-performance keyword search system for a minority language with limited training data in a short period of time. We present the system of the Department of Electronic Engineering, Tsinghua University (THUEE team) for the OpenKWS14 keyword...
The Context-Dependent Deep-Neural-Network HMM, or CD-DNN-HMM, is a powerful acoustic modeling technique. Its training process typically involves unsupervised pre-training and supervised fine-tuning. In the paper, we demonstrate that the performance of DNNs can be improved by utilizing a large amount of unlabeled data in the training procedure. In our method, CD-DNN-HMM trained using 309 hours of unlabeled...
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