Papers with rules-based segmenter
Morphology-Aware Meta-Embeddings for Tamil (2021.naacl-srw)
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| Challenge: | In this work, we focus on producing morphologically enhanced word embeddings for Tamil, a highly agglutinative South Indian language with rich morphology that remains low-resource with regards to NLP tasks. |
| Approach: | They present a first-ever word analogy dataset for Tamil using a rules-based segmenter and meta-embedding techniques. |
| Outcome: | The proposed embeddings outperform baselines on the word analogy task by 16% and appear to mitigate a trade-off between semantic and morphological accuracy. |