Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation

Publication
Transactions of the Association for Computational Linguistics (TACL)

Code

Our model is implemented in XNMT. The employed version including extensions written for this paper can be downloaded here. The relevant XNMT extension is under xnmt/custom/symmetric_translator.py.

Example configuration files