Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
10
datasets available to search
ShareScore release 0.9.0
Dataset results
10 results for “Swiss German”
Virtually Real short film "LUX" by Wendy Pillonel, versions with real and virtual backgrounds, 7min18sec, swiss-german, ProRes 1998 × 1080
<p>Two short feature films were recorded with a virtual background by using a green screen in a film studio and previously scanned 3D spaces in a virtual production environment and conventionally (in the corresponding real spaces) to compare the aesthetics and perception of these films. One scene of each film is shown in two variants (real vs. virtual background) to make a comparison.</p> <p>These 2 QuickTime files represents both the "real" and "virtual" version of the short Film "Lux" by Wendy Pillonel. The real version was shot on location using real backgrounds, the virtual version was shot in the studio in front of a green-screen using virtual backgrounds that were added in post production. </p> <p>Running time: 7min18sec. This is the highest quality version available. </p> <p>Virtually Real is a research project by the Zurich University of the Arts, Institute for the Performing Arts and Film and the University of Bern, Institute of Psychology.</p>
Examining the representation of landscape and its emotional value in German-Swiss fiction around 1900
<p>This repository provides access to the main datasets used in Grisot, G & Herrmann, J. B. (2023) <em>Examining the representation of landscape and its emotional value in German-Swiss fiction around 1900.</em> The data set includes the following item:</p> <p>(1) <em>all_entities_new.Rdata</em>: comprehensive list of labelled spatial entities;</p> <p>(2) <em>corpus_summary_table.xlsx</em>: a summary of the corpus content;</p> <p>(3) <em>corpus_clean_partitioned.zip</em>: the entire corpus after removing stopwords;</p> <p>(4) <em>sentiment_lexicons.RData</em>: the sentiment lexicons for German used in our analyses;</p> <p>(5) tables with details of various analyses (<em>proportions_spatial_entities.xlsx, proportions_spatial_entities_by_country.xlsx, Spatial_entities_in_Corpus_by_category.xlsx</em>);</p> <p>(6) <em>Sentiment_lexicons_info.xlsx</em>: information about the content of the sentment lexicons.</p> <p>The study for which this data were collected explored the representation and affective encoding of fictional space in a corpus of 125 Swiss literary prose texts of the 19th and early 20th Century written in German, offering thus a contribution to both spatial and affective literary studies. Motivated by questions about the iconic dichotomy between urban and rural in literary works – and in Swiss literature in particular – we used computational methods to examine the types of space encoded in German-Swiss literature as well as the affective encoding associated with these space types. Taking into account the complexity of cultural perceptions and representations of space across history, we explore questions about affective encoding of rural, urban, and natural fictional spaces, as well as about their role in the construction of ‘Swiss’ national literature.</p>
Swiss German Novel Collection (ELTeC-gsw)
<pre># ELTeC-CH This is the Swiss novel collection for the ELTeC, the European Literary Text Collection, produced by the COST Action "Distant Reading for European Literary History" (CA16204, https://distant-reading.net). ## Release notes General information about ELTeC releases is available at https://github.com/COST-ELTeC/ELTeC. The ELTeC-gsw collection will contain 100 novels encoded at level 1. The corpus composition criteria are fulfilled. ## Contributors * Collection editor(s): Giulia Grisot, Berenike Herrmann * Sources: Textgrid Repository, Deutsches Textarchiv, KOLIMO, Project-gutenberg.de, e-rara.ch ## Licence All texts included in this collection are in the public domain. The textual markup is provided with a Creative Commons Attribution International 4.0 licence (CC 0, https://creativecommons.org/publicdomain/zero/1.0/).</pre>
German-Swiss survey on the use of (digital) language resources
<p>This survey on the use of (digital) language resources in German-speaking Switzerland complements the Europe-wide survey conducted by the European Network of e-Lexicography (ENeL) and was carried out in close cooperation with the Leibniz Institute for the German Language (IDS) in Mannheim. The aim was to obtain information on the use of language resources from the user's perspective.</p>
Swiss Austrian German Testicular Cancer Cohort Study - SAG TCCS
ClinicalTrials.gov study NCT02229916. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Validation of a Swiss German Language Test for Children
ClinicalTrials.gov study NCT06567613. IPD Sharing: NO. Countries: 1. Publications: 0.
STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions
<p>We present STT4SG-350 (Speech-to-Text for Swiss German), a corpus of Swiss German speech, annotated with Standard German text at the sentence level. The data is collected using a web app in which the speakers are shown Standard German sentences, which they translate to Swiss German and record. We make the corpus publicly available. It contains 343 hours of speech from all dialect regions and is the largest public speech corpus for Swiss German to date. Application areas include automatic speech recognition (ASR), text-to-speech, dialect identification, and speaker recognition. Dialect information, age group, and gender of the 316 speakers are provided. Genders are equally represented and the corpus includes speakers of all ages. Roughly the same amount of speech is provided per dialect region, which makes the corpus ideally suited for experiments with speech technology for different dialects. We provide training, validation, and test splits of the data. The test set consists of the same spoken sentences for each dialect region and allows a fair evaluation of the quality of speech technologies in different dialects. We train an ASR model on the training set and achieve an average BLEU score of 74.7 on the test set. The model beats the best published BLEU scores on 2 other Swiss German ASR test sets, demonstrating the quality of the corpus.</p>
Annotation Scheme for Continuous Data in Swiss German Sign Language
<p>Annotation scheme described in the paper "Advancing Annotation for Continuous Data in Swiss German Sign Language" to annotate sentences in Swiss German Sign Language. The annotations are in both German and English.</p>
SMILE Swiss German Sign Language Dataset
<p><strong>Description</strong></p> <p>The SMILE Swiss German Sign Language Dataset consists of videos, joint coordinates and annotations of 100 isolated signs of a Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS) vocabulary production test. All items were produced multiple times by 16 adult L1 signers and 22 adult L2 learners of DSGS. Associated linguistic transcriptions and annotations are available for second path data of 10 adult L1 signers and 18 adult L2 learners of DSGS.</p> <p>The dataset has been created in the context of developing an assessment system for lexical signs of DSGS in the SNSF project SMILE.</p> <p>More precisely, for each participant, the following files are available:</p> <ul> <li>Kinect color video (.mp4); 1920x1080 Pixels @ 30 FPS;</li> <li>Kinect Pose Information (.csv); 25 Joints; 3D Joint Coordinates and Angles;</li> <li>OpenPose output (.json); 2D Joint Coordinates and Confidences;</li> <li>iLex annotation files (.xml); linguistic annotations.</li> </ul> <p> </p> <p><strong>Reference</strong></p> <p>If you use this database, please cite the following publication:</p> <p><em>Sarah Ebling, Necati Cihan Camgöz, Penny Boyes Braem, Katja Tissi, Sandra Sidler-Miserez, Stephanie Stoll, Simon Hadfield, Tobias Haug, Richard Bowden, Sandrine Tornay, Marzieh Razavi, and Mathew Magimai-Doss. SMILE Swiss German Sign Language Dataset. In Proceedings of the 11th Language Resources and Evaluation Conference (LREC 2018), pages 4221–4229, 2018.</em></p>
German-Swiss survey on the use of (digital) language resources
<p>In this document the raw data of an online survey (n=255) on the use of (digital) language resources in German-speaking Switzerland is made available to the public.The corresponding codes are described in more detail in the codebook also published on Zenodo (cf. 10.5281/zenodo.4314348). In addition, the website of the project "Digital Language Resources - Empirical Analyses and Perspectives" (cf. https://www.ds.uzh.ch/de/projekte/digitale-sprachressourcen) offers a detailed presentation of the results elaborated on the basis of this data. The study complements the Europe-wide survey conducted by the European Network of e-Lexicography (ENeL) and was carried out in close cooperation with the Leibniz-Institute for the German Language (IDS) in Mannheim. </p> <p> </p> <p>T</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.