Sirvi Autor "Ahltorp, Magnus" järgi

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The Word Rain visualisation technique applied to digital history: How to visualise, explore and compare texts using semantically structured word Clouds
(University of Tartu Library, 2025-11) Skeppstedt, Maria; Ahltorp, Magnus; Kucher, Kostiantyn; Aangenendt, Gijs; Lindström, Matts; Söderfeldt, Ylva; Bouma, Gerlof; Dannélls, Dana; Kokkinakis, Dimitrios; Volodina, Elena
The Word Rain text visualisation technique aims to retain the simplicity of the classic word cloud, while addressing some of its limitations. In particular, the Word Rain visualisation uses word embeddings to automatically give the visualised words a semantically meaningful position along the horizontal axis. In this handbook chapter, we showcase how this novel approach for word positioning makes the Word Rain technique suitable for exploring, analysing and comparing texts. More specifically, we show how the Word Rain Python module can be used to visualise longitudinal changes in periodicals published by the Swedish Diabetes Association, and how the Word Rain web service can be used to create visualisations that compare the patient organisation periodicals to journals published by the Swedish Medical Association.
Tugg: A transcription tool for language documentation
(University of Tartu Library, 2025-11) Ahltorp, Magnus; Berthelsen, Harald; Bouma, Gerlof; Dannélls, Dana; Kokkinakis, Dimitrios; Volodina, Elena
Modern language documentation is less about field linguists treating the speakers of a language as rather passive informants, and more about actively involving them in the work as language consultants. This includes handling tools like recording equipment and being able to transcribe language data on their own. Catering to non-expert users of transcription software presents new challenges for a category of tools that traditionally was the exclusive domain of expert users. We will describe a new transcription tool that aims to be directly usable without any special knowledge of the tool, and only requiring modest amounts of previous computer knowledge for the end user. The tool is geared towards producing fully Leipzig glossing rules compliant transcriptions with a minimum of effort. This chapter will describe the tool, how to set up the server part of the tool, and practical instructions on how to use it, including suggested workflows. The chapter ends with a brief description of a practical use case and future directions.