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Neural Morphology Dataset and Models for Multiple Languages, from the Large to the Endangered ...
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Processing M.A. Castrén's Materials: Multilingual Typed and Handwritten Manuscripts ...
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Never guess what I heard... Rumor Detection in Finnish News: a Dataset and a Baseline ...
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Finnish Dialect Identification: The Effect of Audio and Text ...
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Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity
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In: 11th International Conference on Computational Creativity (ICCC’20) ; https://hal.archives-ouvertes.fr/hal-02977153 ; 11th International Conference on Computational Creativity (ICCC’20), Sep 2020, Coimbra, Portugal ; http://computationalcreativity.net/iccc20/ (2020)
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Murre - Normalize non-standard Finnish and dialectalize standard Finnish ...
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Normalization of Different Swedish Dialects Spoken in Finland ...
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Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity ...
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Ve'rdd. Narrowing the Gap between Paper Dictionaries, Low-Resource NLP and Community Involvement ...
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Morphology data for 22 languages ...
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Abstract:
Most people will want to download only the train_data.zip file. This contains folders named after language ISO codes. Under each language, you will find separate folders for the lemmatization, analysis and generation tasks. Each one of these folders has source and target files for train, val and test. There is also a pred.txt file that has the predictions of the baseline system. If you need more control over how these datasets are created, keep on reading. To create the dataset from scratch, run the data_formatter.py. The morphological data is stored in the fst.zip, if you want to download that and skip some parts of making the data from scratch, extract it to the same folder as the data_formatter.py. Cite: Hämäläinen, M., Partanen, N., Rueter, J., & Alnajjar, K. (2021). Neural Morphology Dataset and Models for Multiple Languages, from the Large to the Endangered. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021) ...
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URL: https://dx.doi.org/10.5281/zenodo.3928628 https://zenodo.org/record/3928628
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Neural models for morphological generation, analysis and lemmatization in 22 languages ...
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