There is no consensus on the state-of-the-art approach to historical text normalization. Many
techniques have been proposed, including rule-based methods, distance metrics, character …

Research in the digital humanities and computational social sciences requires overcoming
complexity in research data, methodology, and research questions. In this article, we show …

A great deal of historical corpora suffer from errors introduced by the OCR (optical character
recognition) methods used in the digitization process. Correcting these errors manually is a …

Spelling normalisation is a useful step in the study and analysis of historical language texts,
whether it is manual analysis by experts or automatic analysis using downstream natural …

Abstract Machine translation is one of the applications of natural language processing which
has been explored in different languages. Recently researchers started paying attention …

We compare different LSTMs and transformer models in terms of their effectiveness in
normalizing dialectal Finnish into the normative standard Finnish. As dialect is the common …

This paper presents Murreviikko, a dataset of dialectal Finnish tweets which have been
dialectologically annotated and manually normalized to a standard form. The dataset can be …

With the increasing availability of digitized resources of historical documents, interest in
effective natural language processing (NLP) for these documents is on the rise. However …

This paper presents an overview of the LL (O) D and NLP methods, tools and data for
detecting and representing semantic change, with its main application in humanities …

Texts written in Old Literary Finnish represent the first literary work ever written in Finnish
starting from the 16th century. There have been several projects in Finland that have …