Papers with feed-forward neural network based classifier
Morphological disambiguation from stemming data (2020.coling-main)
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| Challenge: | morphologically rich languages require ambiguous analysis to be effective . morphology tools are limited for morphlogical analysis, disambiguation, and annotation . |
| Approach: | They propose to learn to morphologically disambiguate Kinyarwanda verbal forms from a crowd-sourced stemming dataset using feature engineering and a feed-forward neural network based classifier. |
| Outcome: | The proposed method achieves about 89% non-contextualized disambiguation accuracy from a crowd-sourced dataset. |