10.5281/zenodo.3473456
https://zenodo.org/records/3473456
oai:zenodo.org:3473456
Hämäläinen, Mika
Mika
Hämäläinen
0000-0001-9315-1278
University of Helsinki
Alnajjar, Khalid
Khalid
Alnajjar
0000-0002-7986-2994
University of Helsinki
FinMeter models
Zenodo
2019
2019-10-04
fin
10.5281/zenodo.3473449
10.5281/zenodo.3473455
1.0.0
Creative Commons Attribution 4.0 International
This contains data files needed for FinMeter.
This data is complementary for FinMeter Python library described in:
Mika Hämäläinen and Khalid Alnajjar (2019). Let's FACE it. Finnish Poetry Generation with Aesthetics and Framing. In the Proceedings of The 12th International Conference on Natural Language Generation.
Sources:
The pretrained vectors for Finnish (es - I know) and English (en) are from E. Grave, P. Bojanowski, P. Gupta, A. Joulin, T. Mikolov, Learning Word Vectors for 157 Languages . Creative Commons Attribution-Share-Alike License 3.0. See https://fasttext.cc/docs/en/crawl-vectors.html
The word2vec model trained on the Finnish Internet ParseBank is from Kanerva, Jenna; Luotolahti, Juhani; Laippala, Veronika; Ginter, Filip: Syntactic N-gram Collection from a Large-Scale Corpus of Internet Finnish. Proceedings of the Sixth International Conference Baltic HLT. 2014. paper. Creative Commons Attribution-ShareAlike 4.0 International License. See http://bionlp.utu.fi/finnish-internet-parsebank.html
The Finnish concreteness data has been automatically translated from Brysbaert, Marc, Amy Beth Warriner, and Victor Kuperman. "Concreteness ratings for 40 thousand generally known English word lemmas." Behavior research methods 46.3 (2014): 904-911. Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. see http://crr.ugent.be/archives/1330