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Multi task learning for historical text normalization: Size matters

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Figure

Table 1: Historical datasets used in our experiments
Table 3: Normalization accuracy (in percent) us-ing the full or sparse training sets, both for thesingle-task setup and the best-performing multi-task (MTL) setup.
Figure 1: Percentage change of error of MTL over single-task models; rows are targets, columns auxiliarydata

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