Supervised and Nonlinear Alignment of Two Embedding Spaces for Dictionary Induction in Low Resourced Languages (D19-1)
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| Challenge: | Existing methods for mapping monolingual word embeddings into another are based on anchor points and unsupervised methods are more adversarial. |
| Approach: | They propose a noise-tolerant piecewise linear technique to learn a non-linear mapping between two monolingual word embedding vector spaces. |
| Outcome: | The proposed method outperforms the state-of-the-art in lower resourced settings with an average of 3.7% improvement of precision @10 across 14 mostly low resourced languages. |
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