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@inProceedings{bamutura-etal-2020-towards-296511,
title = {Towards Computational Resource Grammars for Runyankore and Rukiga},
abstract = {In this paper, we present computational resource grammars of Runyankore and Rukiga (R&R) languages. Runyankore and Rukiga are two under-resourced Bantu Languages spoken by about 6 million people indigenous to South Western Uganda, East Africa. We used Grammatical Framework (GF), a multilingual grammar formalism and a special-purpose functional programming language to formalise the descriptive grammar of these languages. To the best of our knowledge, these computational resource grammars are the first attempt to the creation of language resources for R&R. In Future Work, we plan to use these grammars to bootstrap the generation of other linguistic resources such as multilingual corpora that make use of data-driven approaches to natural language processing feasible. In the meantime, they can be used to build Computer-Assisted Language Learning (CALL) applications for these languages among others.},
booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
author = {Bamutura, David and Ljunglöf, Peter and Nabende, Peter},
year = {2020},
publisher = {European Language Resources Association},
}
@incollection{berdicevskis-2020-kogda-296607,
title = {Kogda morfologija bessil'na},
booktitle = {VAProsy jazykoznanija: megasbornik nanostatej},
author = {Berdicevskis, Aleksandrs},
year = {2020},
publisher = {Buki-Vedi},
address = {Moskva},
ISBN = {978-5-4465-2882-0},
pages = {56--60},
}
@inProceedings{berdicevskis-2020-older-290636,
title = {Older English Words Are More Polysemous},
booktitle = {The Evolution of Language: Proceedings of the 13th International Conference (EvoLang13). Pp. 14-21},
author = {Berdicevskis, Aleksandrs},
year = {2020},
publisher = {The Evolution of Language Conferences },
address = {Nijmegen },
}
@inProceedings{berdicevskis-eckhoff-2020-diachronic-293349,
title = {A Diachronic Treebank of Russian Spanning More Than a Thousand Years},
booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), May 11-16, 2020, Marseille, France / ed. Nicoletta Calzolari (Conference chair). },
author = {Berdicevskis, Aleksandrs and Eckhoff, Hanne},
year = {2020},
publisher = {European Language Resources Association},
address = {Paris},
ISBN = {979-10-95546-34-4},
}
@incollection{berdicevskis-semenuks-2020-different-296274,
title = {Different trajectories of morphological overspecification and irregularity under imperfect language learning},
booktitle = {The Complexities of Morphology},
editor = {Peter Arkadiev and Francesco Gardani},
author = {Berdicevskis, Aleksandrs and Semenuks, Arturs},
year = {2020},
publisher = {Oxford University Press},
address = {Oxford},
ISBN = {9780198861287},
pages = {283--305},
}
@inProceedings{dannells-etal-2020-evaluation-296165,
title = {Evaluation of a Two-OCR Engine Method: First Results on Digitized Swedish Newspapers Spanning over nearly 200 Years},
abstract = {In this paper we present a two-OCR engine method that was developed at Kungliga biblioteket (KB), the National Library of Sweden, for improving the correctness of the OCR for mass digitization of Swedish newspapers. We report the first quantitative evaluation results on a material spanning over nearly 200 years. In this first evaluation phase we experimented with word lists for different time periods. Although there was no significant overall improvement of the OCR results, the evaluation shows that some combinations of word lists are successful for certain periods and should therefore be explored further. },
booktitle = { CLARIN Annual Conference 2020, (Virtual Event), 5-7 October, 2020. Book of Abstracts},
author = {Dannélls, Dana and Björk, Lars and Dirdal, Ove and Johansson, Torsten },
year = {2020},
}
@inProceedings{dannells-simon-2020-supervised-289944,
title = {Supervised OCR Post-Correction of Historical Swedish Texts: What Role Does the OCR System Play?},
abstract = {Current approaches for post-correction of OCR errors offer solutions that are tailored to a specific OCR system. This can be problematic if the post-correction method was trained on a specific OCR
system but have to be applied on the result of another system. Whereas OCR post-correction of historical text has received much attention lately, the question of what role does the OCR system play for the post-correction method has not been addressed. In this study we explore a dataset of
400 documents of historical Swedish text which has been OCR processed by three state-of-the-art OCR systems: Abbyy Finereader, Tesseract and Ocropus. We examine the OCR results of each system and present a supervised machine learning post-correction method that tries to approach
the challenges exhibited by each system. We study the performance of our method by using three evaluation tools: PrimA, Språkbanken evaluation tool and Frontiers Toolkit. Based on the evaluation analysis we discuss the impact each of the OCR systems has on the results of the post-
correction method. We report on quantitative and qualitative results showing varying degrees of OCR post-processing complexity that are important to consider when developing an OCR post-correction method.},
booktitle = {Proceedings of the Digital Humanities in the Nordic Countries, 5th Conference, Riga, Latvia, October 21-23, 2020},
editor = {Sanita Reinsone and Inguna Skadiņa and Anda Baklāne and Jānis Daugavietis},
author = {Dannélls, Dana and Simon, Persson},
year = {2020},
publisher = {CEUR-WS},
}
@inProceedings{frossard-etal-2020-dataset-293923,
title = {Dataset for Temporal Analysis of English-French Cognates},
abstract = {Languages change over time and, thanks to the abundance of digital corpora, their evolutionary analysis using computational techniques has recently gained much research attention. In this paper, we focus on creating a dataset to support investigating the similarity in evolution between different languages. We look in particular into the similarities and differences between the use of corresponding words across time in English and French, two languages from different linguistic families yet with shared syntax and close contact. For this we select a set of cognates in both languages and study their frequency changes and correlations over time. We propose a new dataset for computational approaches of synchronized diachronic investigation of language pairs, and subsequently show novel findings stemming from the cognate-focused diachronic comparison of the two chosen languages. To the best of our knowledge, the present study is the first in the literature to use computational approaches and large data to make a cross-language diachronic analysis.},
booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
author = {Frossard, Esteban and Coustaty, Mickael and Doucet, Antoine and Jatowt, Adam and Hengchen, Simon},
year = {2020},
publisher = {European Language Resources Association},
address = {Marseille, France},
ISBN = {979-10-95546-34-4},
}
@inProceedings{johansson-adesam-2020-training-293365,
title = {Training a Swedish Constituency Parser on Six Incompatible Treebanks},
abstract = {We investigate a transition-based parser that usesEukalyptus, a function-tagged constituent treebank for Swedish which includesdiscontinuous constituents. In addition, we show that the accuracy of this parser can be improved by using a multitask learning architecture that makes it possible to train the parser on additional treebanks that use other annotation models.},
booktitle = {Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020)},
author = {Johansson, Richard and Adesam, Yvonne},
year = {2020},
publisher = {European Language Resources Association (ELRA)},
}
@inProceedings{kokkinakis-lundholmfors-2020-digital-295582,
title = {Digital Neuropsychological Tests and Biomarkers: Resources for NLP and AI Exploration in the Neuropsychological Domain},
abstract = {Non-invasive, time and cost-effective, easy-to-measure techniques for the early diagnosis or monitoring the progression of brain and mental disorders are at the forefront of recent research in this field. Natural Language Processing and Artificial Intelligence can play an important role in supporting and enhancing data driven approaches to improve the accuracy of prediction and classification. However, large datasets of e.g. recorded speech in the domain of cognitive health are limited. To improve the performance of existing models we need to train them on larger datasets, which could raise the accuracy of clinical diagnosis, and contribute to the detection of early signs at scale. In this paper, we outline our ongoing work to collect such data from a large population in order to support and conduct future research for modelling speech and language features in a cross-disciplinary manner. The final goal is to explore and combine linguistic with multimodal biomarkers from the same population and compare hybrid models that could increase the predictive accuracy of the algorithms that operate on them.},
booktitle = {CLARIN Annual Conference 2020 in Virtual Form},
author = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina},
year = {2020},
}
@article{kokkinakis-lundholmfors-2020-manga-294522,
title = {Hur många djur du kommer på kan avslöja hur din hjärna mår},
journal = {Språkbruk},
author = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina},
year = {2020},
volume = {2},
pages = {48--51},
}
@inProceedings{lange-ljunglof-2020-learning-291243,
title = {Learning Domain-specific Grammars from a Small Number of Examples},
abstract = {In this paper we investigate the problem of grammar inference from a different perspective. The common approach is to try to infer a grammar directly from example sentences, which either requires a large training set or suffers from bad accuracy. We instead view it as a problem of grammar restriction or sub-grammar extraction. We start from a large-scale resource grammar and a small number of examples, and find a sub-grammar that still covers all the examples. To do this we formulate the problem as a constraint satisfaction problem, and use an existing constraint solver to find the optimal grammar. We have made experiments with English, Finnish, German, Swedish and Spanish, which show that 10–20 examples are often sufficient to learn an interesting domain grammar. Possible applications include computer-assisted language learning, domain-specific dialogue systems, computer games, Q/A-systems, and others.},
booktitle = {12th International Conference on Agents and Artificial Intelligence - Volume 1: NLPinAI},
author = {Lange, Herbert and Ljunglöf, Peter},
year = {2020},
publisher = {SciTePress},
ISBN = {978-989-758-395-7},
}
@misc{mcgillivray-etal-2020-challenges-295208,
title = {The challenges and prospects of the intersection of humanities and data science: A White Paper from The Alan Turing Institute},
abstract = {Since their beginnings, the digital humanities have engaged in an energetic debate about their scope, defining features, and relationship to the wider humanities, and have established themselves as a community of practice (Schreibman et al., 2004; Terras, 2010; Terras, 2013; Terras et al., 2013; Gold and Klein, 2016; The Digital Humanities Manifesto 2.0). The computational focus has characterised the field from its initial explorations (Hockey, 2004; Vanhoutte, 2013; Nyhan and Flinn, 2016) and the shift from the label ‘Humanities Computing’ to ‘Digital Humanities’ was a catalyst for change. In the history of the field, recurring cycles and productive tensions have arisen from the interfolding of computational methodologies and approaches with hermeneutic and critical modes of analysis (see McCarty, 2005; Rockwell and Sinclair, 2016; Jones, 2016). This document postulates that we are currently witnessing another one of these junctures, one that is calling for a critical involvement with data science.
In many ways, we are seeing earlier methods blending into, or being extended by data science.
Digitisation workflows are being augmented with automatic information extraction, data analysis, automated transcription of handwritten documents, and visualisation of transcribed content. Techniques developed for history, literary studies, and linguistics are being scaled towards larger datasets and more complex problems raising the bar of interpretability and questioning the validity of data collection and analysis methods. On the other hand, the field of data science has recently started to engage with non-STEM (Science, Technology, Engineering, and Mathematics) disciplines, by offering new data-driven modelling frameworks for addressing
long-standing research questions (Kitchin, 2014; Lazer et al., 2009) and proposing so-called ‘human-centred approaches’ to data science, focussed on the interpretability of machine learning models and a more active role for human input in algorithms (See Chen et al., 2016).
Moreover, in the current historical context we are witnessing an increased awareness of the questions of diversity and inclusion in research and academia, and we are seeing the creation of a strong movement aimed at addressing such issues globally. We believe that this paper can play a role in reinforcing a positive message in this respect.},
author = {McGillivray, Barbara and Alex, Beatrice and Ames, Sarah and Armstrong, Guyda and Beavan, David and Ciula, Arianna and Colavizza, Giovanni and Cummings, James and De Roure, David and Farquhar, Adam and Hengchen, Simon and Lang, Anouk and Loxley, James and Goudarouli, Eirini and Nanni, Federico and Nini, Andrea and Nyhan, Julianne and Osborne, Nicola and Poibeau, Thierry and Ridge, Mia and Ranade, Sonia and Smithies, James and Terras, Melissa and Vlachidis, Andreas and Willcox, Pip},
year = {2020},
}
@article{roberts-etal-2020-chield-292421,
title = {CHIELD: the causal hypotheses in evolutionary linguistics database},
journal = {Journal of Language Evolution},
author = {Roberts, Sean and Killin, Anton and Deb, Angarika and Sheard, Catherine and Greenhill, Simon and Sinnemäki, Kaius and Segovia-Martin, José and Nölle, Jonas and Berdicevskis, Aleksandrs and Humphreys-Balkwill, Archie and Little, Hannah and Opie, Cristopher and Jacques, Guillaume and Bromham, Lindell and Tinits, Peeter and Ross, Robert and Lee, Sean and Gasser, Emily and Calladine, Jasmine and Spike, Matthew and Mann, Stephen and Shcherbakova, Olena and Singer, Ruth and Zhang, Shuya and Benítez-Burraco, Antonio and Kliesch, Christian and Thomas-Colquhoun, Ewan and Skirgård, Hedvig and Tamariz, Monica and Passmore, Sam and Pellard, Thomas and Jordan, Fiona},
year = {2020},
volume = {5},
number = {2},
pages = {101–120},
}
@inProceedings{rouces-etal-2020-creating-290695,
title = {Creating an Annotated Corpus for Aspect-Based Sentiment Analysis in Swedish},
abstract = {Aspect-Based Sentiment Analysis constitutes a more fine-grained alternative to traditional sentiment analysis at sentence level. In addition to a sentiment value denoting how positive or negative a particular opinion or sentiment expression is, it identifies additional aspects or 'slots' that characterize the opinion. Some typical aspects are target and source, i.e. who holds the opinion and about which entity or aspect is the opinion. We present a large Swedish corpus annotated for Aspect-Based Sentiment Analysis. Each sentiment expression is annotated as a tuple that contains the following fields: one among 5 possible sentiment values, the target, the source, and whether the sentiment expressed is ironic. In addition, the linguistic element that conveys the sentiment is identified too. Sentiment for a particular topic is also annotated at title, paragraph and document level.
The documents are articles obtained from two Swedish media (Svenska Dagbladet and Aftonbladet) and one online forum (Flashback), totalling around 4000 documents. The corpus is freely available and we plan to use it for training and testing an Aspect-Based Sentiment Analysis system.},
booktitle = {Proceedings of the 5th conference in Digital Humanities in the Nordic Countries, Riga, Latvia, October 21-23, 2020.},
author = {Rouces, Jacobo and Borin, Lars and Tahmasebi, Nina},
year = {2020},
publisher = {CEUR Workshop Proceedings},
}
@inProceedings{schlechtweg-etal-2020-semeval-295463,
title = {SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection},
abstract = {Lexical Semantic Change detection, i.e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and linguistics. Evaluation is currently the most pressing problem in Lexical Semantic Change detection, as no gold standards are available to the community, which hinders progress. We present the results of the first shared task that addresses this gap by providing researchers with an evaluation framework and manually annotated, high-quality datasets for English, German, Latin, and Swedish. 33 teams submitted 186 systems, which were evaluated on two subtasks. },
booktitle = {Proceedings of the Fourteenth Workshop on Semantic Evaluation (SemEval2020), Barcelona, Spain (Online), December 12, 2020.},
author = {Schlechtweg, Dominik and McGillivray, Barbara and Hengchen, Simon and Dubossarsky, Haim and Tahmasebi, Nina},
year = {2020},
publisher = {ACL},
}
@misc{schlechtweg-etal-2020-post-295466,
title = {Post-Evaluation Data for SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection},
abstract = {This data collection contains the post-evaluation data for SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection: (1) the starting kit to download data, and examples for competing in the CodaLab challenge including baselines; (2) the true binary change scores of the targets for Subtask 1, and their true graded change scores for Subtask 2 (test_data_truth/); (3)the scoring program used to score submissions against the true test data in the evaluation and post-evaluation phase (scoring_program/); and (4) the results of the evaluation phase including, for example, analysis plots (plots/) displaying the results:},
author = {Schlechtweg, Dominik and McGillivray, Barbara and Hengchen, Simon and Dubossarsky, Haim and Tahmasebi, Nina},
year = {2020},
publisher = {Zenodo},
}
@misc{tahmasebi-etal-2020-swedish-295465,
title = {Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection},
abstract = {This data collection contains the Swedish test data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection. It consists of a Swedish text corpus pair (corpus1/, corpus2/) and 31 lemmas which have been annotated for their lexical semantic change between the two corpora (targets.txt). We sample from the KubHist2 corpus, digitized by the National Library of Sweden, and available through the Språkbanken corpus infrastructure Korp (Borin et al., 2012). The full corpus is available through a CC BY (attribution) license. Each word for which the lemmatizer in the Korp pipeline has found a lemma is replaced with the lemma. In cases where the lemmatizer cannot find a lemma, we leave the word as is (i.e., unlemmatized, no lower-casing). KubHist contains very frequent OCR errors, especially for the older data.More detail about the properties and quality of the Kubhist corpus can be found in (Adesam et al., 2019).},
author = {Tahmasebi, Nina and Hengchen, Simon and Schlechtweg, Dominik and McGillivray, Barbara and Dubossarsky, Haim},
year = {2020},
}
@article{themistocleous-etal-2020-voice-295469,
title = {Voice quality and speech fluency distinguish individuals with Mild Cognitive Impairment from Healthy Controls},
abstract = {Mild Cognitive Impairment (MCI) is a syndrome characterized by cognitive decline greater than expected for an individual's age and education level. This study aims to determine whether voice quality and speech fluency distinguish patients with MCI from healthy individuals to improve diagnosis of patients with MCI. We analyzed recordings of the Cookie Theft picture description task produced by 26 patients with MCI and 29 healthy controls from Sweden and calculated measures of voice quality and speech fluency. The results show that patients with MCI differ significantly from HC with respect to acoustic aspects of voice quality, namely H1-A3, cepstral peak prominence, center of gravity, and shimmer; and speech fluency, namely articulation rate and averaged speaking time. The method proposed along with the obtainability of connected speech productions can enable quick and easy analysis of speech fluency and voice quality, providing accessible and objective diagnostic markers of patients with MCI.},
journal = {PloS one},
author = {Themistocleous, Charalambos and Eckerström, Marie and Kokkinakis, Dimitrios},
year = {2020},
volume = {15},
number = {7},
pages = {e0236009},
}
@inProceedings{virk-etal-2020-from-295339,
title = {From Linguistic Descriptions to Language Profiles},
abstract = {Language catalogues and typological databases are two important types of resources containing different types of knowledge about the world’s natural languages. The former provide metadata such as number of speakers, location (in prose descriptions and/or GPS coordinates), language code, literacy, etc., while the latter contain information about a set of structural and functional attributes of languages. Given that both types of resources are developed and later maintained manually, there are practical limits as to the number of languages and the number of features that can be surveyed. We introduce the concept of a language profile, which is intended to be a structured representation of various types of knowledge about a natural language extracted semi-automatically from descriptive documents and stored at a central location. It has three major parts: (1) an introductory; (2) an attributive; and (3) a reference part, each containing different types of knowledge about a given natural language. As a case study, we develop and present a language profile of an example language. At this stage, a language profile is an independent entity, but in the future it is envisioned to become part of a network of language profiles connected to each other via various types of relations. Such a representation is expected to be suitable both for humans and machines to read and process for further deeper linguistic analyses and/or comparisons.},
booktitle = {Proceedings of the 7th Workshop on Linked Data in Linguistics (LDL-2020). Language Resources and Evaluation Conference (LREC 2020), Marseille, 11–16 May 2020 / Edited by : Maxim Ionov, John P. McCrae, Christian Chiarcos, Thierry Declerck, Julia Bosque-Gil, and Jorge Gracia},
author = {Virk, Shafqat and Hammarström, Harald and Borin, Lars and Forsberg, Markus and Wichmann, Søren },
year = {2020},
publisher = {European Language Resources Association},
address = {Paris},
ISBN = {979-10-95546-36-8},
}
@inProceedings{virk-etal-2020-dream-295338,
title = {The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages},
booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), Marseille, 11–16 May 2020 / Editors : Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis},
author = {Virk, Shafqat and Hammarström, Harald and Forsberg, Markus and Wichmann, Søren },
year = {2020},
publisher = {European Language Resources Association},
address = {Paris},
ISBN = {979-10-95546-34-4 },
}
@inProceedings{waldispuhl-etal-2020-material-293332,
title = {Material Philology Meets Digital Onomastic Lexicography: The NordiCon Database of Medieval Nordic Personal Names in Continental Sources},
abstract = {We present NordiCon, a database containing medieval Nordic personal names attested in Continental sources. The database combines formally interpreted and richly interlinked onomastic data with digitized versions of the medieval manuscripts from which the data originate and information on the tokens' context. The structure of NordiCon is inspired by other online historical given name dictionaries. It takes up challenges reported on in previous works, such as how to cover material properties of a name token and how to define lemmatization principles, and elaborates on possible solutions. The lemmatization principles for NordiCon are further developed in order to facilitate the connection to other name dictionaries and corpuses, and the integration of the database into Språkbanken Text, an infrastructure containing modern and historical written data.},
booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference, Marseille, 11–16 May 2020 / editors: Nicoletta Calzolari... [et. al.]},
author = {Waldispühl, Michelle and Dannélls, Dana and Borin, Lars},
year = {2020},
publisher = {European Language Resources Association},
address = {Marseille},
ISBN = {979-10-95546-34-4},
}