Normalizing Early English Letters to Present-day English Spelling

Mika Hämäläinen, Tanja Säily, Jack Rueter, Jörg Tiedemann, Eetu Mäkelä


Abstract
This paper presents multiple methods for normalizing the most deviant and infrequent historical spellings in a corpus consisting of personal correspondence from the 15th to the 19th century. The methods include machine translation (neural and statistical), edit distance and rule-based FST. Different normalization methods are compared and evaluated. All of the methods have their own strengths in word normalization. This calls for finding ways of combining the results from these methods to leverage their individual strengths.
Anthology ID:
W18-4510
Volume:
Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico
Venues:
COLING | LaTeCH | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
87–96
Language:
URL:
https://www.aclweb.org/anthology/W18-4510
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-4510.pdf