The following publications are possibly variants of this publication:
- Normalization of historical texts with neural network modelsMarcel Bollmann. PhD thesis, Ruhr University Bochum, Germany, 2018. [doi]
- A Large-Scale Comparison of Historical Text Normalization SystemsMarcel Bollmann. naacl 2019: 3885-3898 [doi]
- Learning attention for historical text normalization by learning to pronounceMarcel Bollmann, Joachim Bingel, Anders Søgaard. acl 2017: 332-344 [doi]
- Few-Shot and Zero-Shot Learning for Historical Text NormalizationMarcel Bollmann, Natalia Korchagina, Anders Søgaard. acl-deeplo 2019: 104-114 [doi]
- Multi-task learning for historical text normalization: Size mattersMarcel Bollmann, Anders Søgaard, Joachim Bingel. acl-deeplo 2018: 19-24 [doi]
- Applying Rule-Based Normalization to Different Types of Historical Texts - An EvaluationMarcel Bollmann, Florian Petran, Stefanie Dipper. ltconf 2014: 166-177 [doi]