Search Results for author: Raphael Schwitter

Found 3 papers, 1 papers with code

Machine Translation of 16Th Century Letters from Latin to German

no code implementations LT4HALA (LREC) 2022 Lukas Fischer, Patricia Scheurer, Raphael Schwitter, Martin Volk

This paper outlines our work in collecting training data for and developing a Latin–German Neural Machine Translation (NMT) system, for translating 16th century letters.

Machine Translation NMT +1

Evaluation of HTR models without Ground Truth Material

1 code implementation LREC 2022 Phillip Benjamin Ströbel, Simon Clematide, Martin Volk, Raphael Schwitter, Tobias Hodel, David Schoch

The evaluation of Handwritten Text Recognition (HTR) models during their development is straightforward: because HTR is a supervised problem, the usual data split into training, validation, and test data sets allows the evaluation of models in terms of accuracy or error rates.

Handwritten Text Recognition Model Selection

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