Normalizing Early English Letters to Present-day English Spelling
What it is about
Early English personal letters, from the 15th to the 19th century, are full of non-standard spellings. The paper normalises them to present-day spelling with five methods: VARD2-style rewrite rules, contextual edit distance, statistical and neural machine translation (with and without period information), and a weighted vote. Each method alone gets a minority of the words right; the best single method is the neural model. The generic test set reaches 67% when any one method is correct. The vote weighted by each method's accuracy gives 45% on the generic set, 56% on the 15th-century set and 22% on the 18th-century set, while a Markov chain over the candidates gives 36%, 40% and 24%. The authors conclude that the period, which they used as a variable, is not a good enough grouping for spelling variation, and that the methods make complementary errors.
Ideas
- I1. 2. Spelling, print conventions and tokens: write the rewrite rules as an ordered table in a deterministic normaliser, and combine them with a dictionary lookup in
en/src/emode.rs. Weight each rule by its accuracy on dev data, as the paper's weighted vote does. Measure exact match on held-out letters, run twice. - I2. Report the "at least one method correct" figure as an upper bound before any change, stratified by period. It shows how much a better selector could gain.
- I3. Negative control: shuffle the period labels in the period-aware table and check that the score falls. The paper's period-aware SMT did not help, so the control is worth running.
For Mova
The chapters are 2. Spelling, print conventions and tokens and 13. Concrete improvements for Mova's parser and lexicon. The code is en/src/emode.rs (the closed table of Early Modern forms) and en/src/morph.rs. Measure: exact-match and lemma accuracy on a held-out letter sample, with the vote weighted and unweighted.
Cite
@inproceedings{hamalainen2018normalizing,
title = {{Normalizing Early English Letters to Present-day English Spelling}},
author = {Hämäläinen, Mika and Säily, Tanja and Rueter, Jack and Tiedemann, Jörg and Mäkelä, Eetu},
booktitle = {Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature},
year = {2018},
url = {https://aclanthology.org/W18-4510/}
}References
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