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Found 32 papers, 13 papers with code
Processing M.A. Castrén’s Materials: Multilingual Historical Typed and Handwritten Manuscripts
The study forms a technical report of various tasks that have been performed on the materials collected and published by Finnish ethnographer and linguist, Matthias Alexander Castrén (1813–1852).
Using Graph-Based Methods to Augment Online Dictionaries of Endangered Languages
Many endangered Uralic languages have multilingual machine readable dictionaries saved in an XML format.
Morphosyntactic Disambiguation in an Endangered Language Setting
Endangered Uralic languages present a high variety of inflectional forms in their morphology.
Linguistic change and historical periodization of Old Literary Finnish
In this study, we have normalized and lemmatized an Old Literary Finnish corpus using a lemmatization model trained on texts from Agricola.
Sentiment Analysis Using Aligned Word Embeddings for Uralic Languages
Furthermore, we align these word embeddings and present a novel neural network model that is trained on English data to conduct sentiment analysis and then applied on endangered language data through the aligned word embeddings.
Processing M.A. Castrén's Materials: Multilingual Typed and Handwritten Manuscripts
The study forms a technical report of various tasks that have been performed on the materials collected and published by Finnish ethnographer and linguist, Matthias Alexander Castr\'en (1813-1852).
Detecting Depression in Thai Blog Posts: a Dataset and a Baseline
We present the first openly available corpus for detecting depression in Thai.
Finnish Dialect Identification: The Effect of Audio and Text
Finnish is a language with multiple dialects that not only differ from each other in terms of accent (pronunciation) but also in terms of morphological forms and lexical choice.
Never guess what I heard... Rumor Detection in Finnish News: a Dataset and a Baseline
However, a model fine-tuned on Multilingual BERT reaches the best factual label accuracy of 97. 2%.
Apurinã Universal Dependencies Treebank
The construction of the treebank has also served as an opportunity to develop finite-state description of the language and facilitate the transfer of open-source infrastructure possibilities to an endangered language of the Amazon.
Neural Morphology Dataset and Models for Multiple Languages, from the Large to the Endangered
We train neural models for morphological analysis, generation and lemmatization for morphologically rich languages.
Ve'rdd. Narrowing the Gap between Paper Dictionaries, Low-Resource NLP and Community Involvement
We present an open-source online dictionary editing system, Ve'rdd, that offers a chance to re-evaluate and edit grassroots dictionaries that have been exposed to multiple amateur editors.
Open-Source Morphology for Endangered Mordvinic Languages
This document describes shared development of finite-state description of two closely related but endangered minority languages, Erzya and Moksha.
Automated Prediction of Medieval Arabic Diacritics
This study uses a character level neural machine translation approach trained on a long short-term memory-based bi-directional recurrent neural network architecture for diacritization of Medieval Arabic.
Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity
The models are tested with over 20 different dialects.
FST Morphology for the Endangered Skolt Sami Language
We present advances in the development of a FST-based morphological analyzer and generator for Skolt Sami.
An Open Online Dictionary for Endangered Uralic Languages
This makes it possible to integrate the system with the existing open-source Giellatekno infrastructure that provides and utilizes XML formatted dictionaries for use in a variety of NLP tasks.
Revisiting NMT for Normalization of Early English Letters
This paper studies the use of NMT (neural machine translation) as a normalization method for an early English letter corpus.
Normalizing Early English Letters to Present-day English Spelling
This paper presents multiple methods for normalizing the most deviant and infrequent historical spellings in a corpus consisting of personal correspondence from the 15th to the 19th century.
