Papers with historical text normalization
Historical Text Normalization with Delayed Rewards (P19-1)
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| Challenge: | Recent work on a novel approach to historical text normalization has shown that policy gradient fine-tuning improves accuracy across languages. |
| Approach: | They propose to train sequence-to-sequence models with simple token-level log-likelihood with reinforcement learning to optimize for exact matches. |
| Outcome: | The proposed model outperforms phrase-based models in the evaluation metric for historical text normalization across languages. |
Applying the Transformer to Character-level Transduction (2021.eacl-main)
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| Challenge: | morphological inflection generation and historical text normalization tasks are character-level tasks that outperform recurrent models. |
| Approach: | They propose a technique to handle feature-guided character-level transduction that further improves performance. |
| Outcome: | The transformer outperforms recurrent models on morphological inflection and historical text normalization tasks. |
A Large-Scale Comparison of Historical Text Normalization Systems (N19-1)
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| Challenge: | a large study of historical text normalization is done on eight languages . there is no consensus on the state-of-the-art approach to normalization . |
| Approach: | They present a large study of historical text normalization done on eight languages . they evaluate four different systems based on supervised learning on datasets from eight different languages based in the literature . |
| Outcome: | The proposed methods are based on supervised learning and are available online. |