Linköping Electronic Conference Proceedings
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Constructing SABeD: A Spoken Academic Belgian Dutch Corpus
Get PDFWe present the Spoken Academic Belgian Dutch (SABeD) corpus and a description of its construction. It was compiled from selected first bachelor academic lectures in higher education institutions in Flanders, as students indicate that the language used in such lectures is one of the hurdles for comprehension and academic success. We first applied speech recognition on these lectures and then applied manual utterance segmentation and manual correction of the automated transcription. A filtered version of the resulting transcriptions was automatically punctuated and linguistically annotated with CLARIN tools and is currently available for search in the Autosearch online corpus query environment. The manual transcriptions and the ELAN files with the final annotation will soon be made available to the research community for download in the CLARIN infrastructure at http://hdl.handle.net/10032/tm-a2-w4
Analyses of information security standards on data crawled from company web sites using SweClarin resources
Get PDFWith the purpose of analysing Swedish companies’ adherence and adoption of the information security standard ISO 27001 and to examine the communicative constitution of preventive innovation in organisations, we have created a corpus of corporate texts from Swedish company websites. The corpus was analysed from multiple interdisciplinary perspectives in close cooperation with management researchers and SweClarin researchers using SweClarin tools and resources as well as standard language technology tools. Some analyses require deep reading, which was performed by management researchers, often guided by results from language analyses. Initial results have been presented at a management studies conference. In this paper, we focus on presenting the research issues, the methods used in the project, the results, and the experience of SweClarin researchers supporting researchers in social sciences. Our contribution is to show how it is possible, through the integration of human insights and digital methods, to increase the credibility and validity of a digitally acquired data set and subsequent research findings. In our view, a combination of human deep reading (management researchers), contextual lexical verification (management studies) and language technology (content and sentiment analysis) can help to sensitise computational text analysis for medium-sized data sets
Can machine learning help reveal the competitive advantage of elite beach volleyball players?
Get PDFAs the world of competitive sports increasingly embraces data-driven techniques, our research explores the potential of machine learning in distinguishing elite from semi-elite beach volleyball players. This study is motivated by the need to understand the subtle yet crucial differences in player movements that contribute to high-level performance in beach volleyball. Utilizing advanced machine learning techniques, we analyzed specific movement patterns of the motion of the torso during spikes, captured through vest-mounted accelerometers. Our approach offers novel insights into the nuanced dynamics of elite play, revealing that certain movement patterns are distinctly characteristic of higher skill levels. One of our key contributions is the ability to classify spiking movements at different skill levels with an accuracy rate as high as 87%. This current research provides a foundation of what separates elite players from their semi-elite counterparts
Research stories on Twitter
Get PDFThis paper aims to study what type of research seems to interest the users of a social network platform and then complement the data with data from an open catalogue for research, exemplifying with Twitter and Open Alex. The basic idea is to get an overview of the stories the platform content tells during three months regarding topics, disciplines, and open access status. The findings suggest that the picture look very different between the approaches to map the topics, especially when looking at the articles most mentioned compared to the ones that are most retweeted. The study mainly highlights the methodological opportunities of combining text analysis and link relationships to explore the content and public interest in academic research
Import and Export of Functional Mockup Units in CasADi
Get PDFThis paper presents the recently added support for import and export of functional mockup units (FMUs) in CasADi, an open-source software framework for numerical optimization. Of particular interest is the efficient calculation of derivatives, especially in the context of sensitivity analysis and dynamic optimization. We show how the import interface allows for both first and second derivatives can be efficiently and accurately calculated and - importantly - validated for correctness. We also outline the FMU export interface, which leverages CasADi mature and efficient support for forward and adjoint derivative calculation and C code generation. Finally, potential future developments of the support are discussed
Design ideas behind Bioprocess Library for Modelica
Get PDFIn this paper I describe key design ideas behind the Bioprocess Library. The library facilitates modelling and simulation of bioprocesses mainly for the pharmaceutical industry. It borrows some structures from MSL Fluid and Media but differs in central design choices and is much simpler. A typical application consists of both configuration of standard components from the library and tailor-made Modelica code defining the application dependent medium and bioprocess reactions. The guiding idea is that configuration of components works well for defining the setup of process equipment for a production line, while more flexibility is needed for modelling bioprocess reactions and therefore equations are used. Another central design idea is that components of equipment are centrally adapted to the medium used. One could say that the library is parameterised with the application media and reaction models. The focus of this paper is structural aspects of the library rather than the content
Potential of ASR for the study of L2 learner corpora
Get PDFThis study is at the crossroads of Natural Language Processing (NLP) and Second Language Acquistion (SLA). We used Word Error Rate (WER) measurements of Whisper's speech recognition on a French L2 learner corpus to get automatic transcripts, and compared them with pre-existing manual transcripts. We then conducted quantitative and qualitative analysis of the issues which are inherent to the specificities of interlanguage for any automatic tool. We will discuss the different issues encountered by Whisper that are specific to learner corpora
GRAMEX: Generating Controlled Grammar Exercises from Various Sources
Get PDFThis paper presents Gramex, an application designed to assist teachers in the creation of learning materials, namely grammar exercises. More precisely Gramex leverages state-of-the-art parsing techniques to morpho-syntactically annotate texts and turn these into grammar exercises while aligning these with official curricula. Allowing teachers to freely select excerpts of texts from which to generate specific grammar exercises aims to increase learners' engagement in educational activities. Gramex currently supports 4 types of exercises (Fill-in-the-Blanks, Mark-the-Words, Single and Mutliple Choice questionnaires) and 3 output formats (JSON objects, printable workbooks, H5P interactive content). Gramex is under active development and has been experimentally used with teachers of L1-learners in elementary and middle French schools
LLM chatbots as a language practice tool: a user study
Get PDFSecond language learners often experience language anxiety when speaking with others in their target language. As the generative capabilities of Large Language Models (LLMs) continue to improve, we investigate the possibility of using an LLM as a conversation practice tool. We conduct a user study with 160 English language learners, where an LLM chatbot is used to simulate real-world conversations. We present our findings on 1) how an interactive session with a chatbot might impact performance in real-world conversations; 2) whether the learning experience differs for learners of different proficiency levels; 4) how changes in difficulty affects the learner's experience; and 3) how online, synchronous conversation provided by an LLM compares with a purely receptive experience. Additionally, we propose a simple yet effective way to detect linguistic complexity on-the-fly: clicking on words to reveal dictionary definitions. We demonstrate that clicks correlate well with linguistic complexity and indicate which words learners find difficult to understand
Characterizing Playing Styles for Ice Hockey Players
No full textAlthough analytics is being used in, e.g., the evaluation of players and scouting, it is still challenging to quantify skills and playing styles of players. Such information is important for roster creation and scouting, where teams want to find players that have a playing style that fits within the team, as well as for game preparation to understand the playing style of opponents. In this paper we use player vectors to characterize a player’s playing style. The player vectors contain representations of skills that are computed from game event data. Further, we use fuzzy clustering on the vectors to generate five types of defender playing styles and five types of forward playing styles. For these types, we show the typical skill levels and players with similar styles