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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 time-consuming process and a great part of the automatic approaches have been relying on rules or supervised machine learning. We present a fully automatic unsupervised way of extracting parallel data for training a characterbased sequence-to-sequence NMT (neural machine translation) model to conduct OCR error correction.

Satire has played a role in indirectly expressing critique towards an authority or a person from time immemorial. We present an autonomously creative masterapprentice approach consisting of a genetic algorithm and an NMT model to produce humorous and culturally apt satire out of movie titles automatically. Furthermore, we evaluate the approach in terms of its creativity and its output. We provide a solid definition for creativity to maximize the objectiveness of the evaluation.

This paper studies the use of NMT (neural machine translation) as a normalization method for an early English letter corpus. The corpus has previously been normalized so that only less frequent deviant forms are left out without normalization. This paper discusses different methods for improving the normalization of these deviant forms by using different approaches. Adding features to the training data is found to be unhelpful, but using a lexicographical resource to filter the top candidates produced by the NMT model together with lemmatization improves results.

Open-source analyzer dictionary development is being implemented for Skolt Sami, Ingrian, Moksha-Mordvin, etc. in the Helsinki CSC infrastructure; home of the Finnish Kielipankki 'Language Bank' and Termipankki 'Term Bank'. The proximity of minority-language corpora in need of annotation and the multiple usage of controlled wikimedia-type dictionaries make CSC an attractive site for synchronized transducer dictionary development. The open-source FST development of Uralic and other minority languages at Giellatekno-Divvun in Tromsø demonstrates a vast potential for reusage of FST-s, only augmented by opensource work in OmorFi, Apertium and Universal Dependency . The initial idea is to allow synchronized editing of Giellatekno XML and CSC Wiki structures via github. In addition to allowing for simple lexc LEMMA:STEM CONTINUATION_LEXICON "TRANS-LATION" ; line exports, the parallel dictionaries will provide for documentation of derivation, morpho-syntactic information on valency and government, semantics and etymology.