Cross Lingual Transfer Learning For Zero-Resource Domain Adaptation

We propose a method for zero-resource domain adaptation of DNN acoustic models, for use in low-resource situations where the only in-language training data available may be poorly matched to the intended target domain. Our method uses a multi-lingual mode
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