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Deep Neural Network (DNN) acoustic models are commonly used in today's state-of-the-art speech recognition systems. As neural networks are a data driven method, the amount of available training data directly impacts the performance. In the past, several studies have shown that multilingual training of DNNs leads to improvements, especially in resource constrained tasks in which only limited training data in the target language is available. Previous studies have shown speaker adaptation to bedoi:10.21437/interspeech.2016-1143 dblp:conf/interspeech/MullerSW16 fatcat:xxkoeylmtbazbeymilzrsjuhdu