Autocorrect for Estonian texts: final report from project EKTB25
Agnes Luhtaru Martin Vainikko Krista Liin Kais Allkivi-Metsoja Jaagup Kippar Pille Eslon Mark Fishel
The project was funded in 2021-2023 by the National Programme of Estonian
Language Technology. Its main aim was to develop spelling and grammar
correction tools for the Estonian language. The main challenge was the very
small amount of available error correction data needed for such development. To
mitigate this, (1) we annotated more correction data for model training and
testing, (2) we tested transfer-learning, i.e. retraining machine learning
models created for other tasks, so as not to depend solely on correction data,
(3) we compared the developed method and model with alternatives, including
large language models. We also developed automatic evaluation, which can
calculate the accuracy and yield of corrections by error category, so that the
effectiveness of different methods can be compared in detail.
  There has been a breakthrough in large language models during the project:
GPT4, a commercial language model with Estonian-language support, has been
created. We took into account the existence of the model when adjusting plans
and in the report we present a comparison with the ability of GPT4 to improve
the Estonian language text.
  The final results show that the approach we have developed provides better
scores than GPT4 and the result is usable but not entirely reliable yet. The
report also contains ideas on how GPT4 and other major language models can be
implemented in the future, focusing on open-source solutions.
  All results of this project are open-data/open-source, with licenses that
allow them to be used for purposes including commercial ones.