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- W2953673324 abstract "This paper studies the use of NMT (neural machine translation) as a normalization method for an early English letter corpus. The corpus has previously been normalized so that only less frequent deviant forms are left out without normalization. This paper discusses different methods for improving the normalization of these deviant forms by using different approaches. Adding features to the training data is found to be unhelpful, but using a lexicographical resource to filter the top candidates produced by the NMT model together with lemmatization improves results." @default.
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- W2953673324 date "2019-01-01" @default.
- W2953673324 modified "2023-09-23" @default.
- W2953673324 title "Revisiting NMT for Normalization of Early English Letters" @default.
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- W2953673324 doi "https://doi.org/10.18653/v1/w19-2509" @default.
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