Before revision:  We use the corpusto explore various cross-lingual transfer methods focusing on the zero-shot setting and leveraging MT for language expansion . Results show that our soft-alignment method significantly improves slot F1 over strong baselines on most languages . In addition, our experiments show the strength of using multilingual BERT for both cross-lingual training and zero-shot transfer .
After revision:  We use the corpusto explore various cross-lingual transfer methods focusing on the zero-shot setting and leveraging MT for language expansion . Results show that our soft-alignment method significantly improves slot F1 over strong baselines on most languages , and achieves competitive performance to the more complex, state-of-the-art projection method with only half of the training time. We release our MultiATIS++ corpus to the community to continue future research on cross-lingual NLU .