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1 | # Evaluating cross-lingual textual similarity on dictionary alignment | 1 | # Evaluating cross-lingual textual similarity on dictionary alignment |
2 | 2 | ||
3 | This repository contains the scripts to prepare the resources for the study as well as open source implementations of the methods. | 3 | This repository contains the scripts to prepare the resources for the study as well as open source implementations of the methods. Word Mover's Distance and Sinkhorn implementations are extended from [Cross-lingual retrieval with Wasserstein distance](https://github.com/balikasg/WassersteinRetrieval). |
4 | 4 | ||
5 | ## Requirements | 5 | ## Requirements |
6 | - Python 3 | 6 | - Python 3 |
@@ -56,8 +56,8 @@ Linewise aligned definition files are in `wordnets/ready`. | |||
56 | 56 | ||
57 | ## Acquiring The Embeddings | 57 | ## Acquiring The Embeddings |
58 | 58 | ||
59 | We use [VecMap](https://github.com/artetxem/vecmap) on [fastText](https://fasttext.cc/) embeddings. | 59 | We use [VecMap](https://github.com/artetxem/vecmap) on [fastText](https://fasttext.cc/) embeddings. You can skip this step if you are providing your own polylingual embeddings. |
60 | You can skip this step if you are providing your own polylingual embeddings. | 60 | |
61 | Otherwise; | 61 | Otherwise; |
62 | 62 | ||
63 | * initialize and update the VecMap submodule; | 63 | * initialize and update the VecMap submodule; |