Rashedur Rahman, Gwénolé Lecorvé, Aline Étienne, Delphine Battistelli, Nicolas Béchet, Jonathan Chevelu
| Challenge: | Existing methods to predict minimal age from which text can be understood for children are unresolved in computational linguistics. |
| Approach: | They propose a method which predicts the minimum age from which a text can be understood by a recurrent neural network. |
| Outcome: | The proposed method outperforms state-of-the-art models at sentence and text levels and achieves mean absolute errors of 1.86 and 2.28. |
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