TY  - JOUR
A1  - Eger, Steffen
A1  - Brück, Tim vor der
A1  - Mehler, Alexander
T1  - A comparison of four character-level string-to-string translation models for (OCR) spelling error correction
T2  - The Prague bulletin of mathematical linguistics
N2  - We consider the isolated spelling error correction problem as a specific subproblem of the more general string-to-string translation problem. In this context, we investigate four general string-to-string transformation models that have been suggested in recent years and apply them within the spelling error correction paradigm. In particular, we investigate how a simple ‘k-best decoding plus dictionary lookup’ strategy performs in this context and find that such an approach can significantly outdo baselines such as edit distance, weighted edit distance, and the noisy channel Brill and Moore model to spelling error correction. We also consider elementary combination techniques for our models such as language model weighted majority voting and center string combination. Finally, we consider real-world OCR post-correction for a dataset sampled from medieval Latin texts.
Y1  - 2017
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/43840
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-438408
SN  - 1804-0462
SN  - 0032-6585
N1  - © 2016 Steffen Eger et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0
VL  - 105
IS  - 1
SP  - 77
EP  - 99
PB  - Universita Karlova
CY  - Praha
ER  -