17 citations · 42 across the 6 of their papers we have counts for
7 papers
Transformer-based HTR for Historical Documents
Phillip Benjamin Ströbel, Simon Clematide, Martin Volk +1
We apply the TrOCR framework to real-world, historical manuscripts and show that TrOCR per se is a strong model, ideal for transfer learning. TrOCR has been trained on English only…
Evaluation of HTR models without Ground Truth Material
Phillip Benjamin Ströbel, Simon Clematide, Martin Volk +3
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, va…
Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain
Samuel Läubli, Chantal Amrhein, Patrick Düggelin +3
Neural machine translation (NMT) has set new quality standards in automatic translation, yet its effect on post-editing productivity is still pending thorough investigation. We emp…
Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation
Samuel Läubli, Rico Sennrich, Martin Volk
Recent research suggests that neural machine translation achieves parity with professional human translation on the WMT Chinese--English news translation task. We empirically test…
Evaluating the fully automatic multi-language translation of the Swiss avalanche bulletin
Kurt Winkler, Tobias Kuhn, Martin Volk
The Swiss avalanche bulletin is produced twice a day in four languages. Due to the lack of time available for manual translation, a fully automated translation system is employed,…
Comparing a statistical and a rule-based tagger for German
Martin Volk, Gerold Schneider
In this paper we present the results of comparing a statistical tagger for German based on decision trees and a rule-based Brill-Tagger for German. We used the same training corpus…