DGS-Korpus

1 April 2015

DGS Corpus is a long-term project of the Academy of Sciences in Hamburg for the documentation of and research on German Sign Language (DGS). The aim is to collect sign language texts from Deaf people and to present parts of them as a public corpus. During the project term of 15 years, a corpus-based electronic DGS – German dictionary will be developed. The corpus is meant to be representative for the everyday language of Deaf people all over Germany.

The DGS Corpus project is carried out at the Institute for German Sign Language and Communication of the Deaf at Hamburg University. The project is financed by the joint research funding of the German Federal Government and Federal States in the Academies’ Programme, with funding from the Federal Ministry of Education and Research and the Free and Hanseatic City of Hamburg.

German Sign Language

Marc Schulder

Research Associate in Computational Linguistics

My research interests include sign languages, natural language processing, and open science.

Publications

Data Statement for the Public DGS Corpus (v3)

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Latest version:
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Version 2:
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Abstract

This data statement of the Public DGS Corpus provides information relevant to judging the nature of the language content of the corpus. It covers how the corpus was curated, specifies the language varieties it covers, and provides demographic information for participants and annotators. It also describes the technical and sociological conditions under which the language data was recorded as well as its topical characteristics. The data statement provides a general overview, supported by references to a variety of publications that cover individual topics in more detail.

Marc Schulder, Dolly Blanck, Thomas Hanke, Ilona Hofmann, Sung-Eun Hong, Olga Jeziorski, Lutz König, Susanne König, Reiner Konrad, Gabriele Langer, Rie Nishio, Christian Rathmann

Not just 'any' sign! Searching for negative polarity items in German Sign Language (DGS)

Abstract

Negative Polarity Items (NPIs) are expressions such as “any” that cannot occur in positive assertions with simple past (“Mary bought any books”), but become acceptable under the scope of negation (“Mary didn’t buy any books”). While NPIs have been claimed to occur in virtually every language, evidence for their use in signed languages is still very limited. Our study seeks to identify potential NPI candidates in German Sign Language (DGS) by performing a collocation analysis of negation signs in the DGS Corpus dataset.

Cornelia Loos, Marc Schulder

Deutsche Gebärdensprache zugänglich und nutzbar machen: Das Öffentliche DGS-Korpus und das Digitale Wörterbuch der Deutschen Gebärdensprache

This article is only available in German.

Abstract

Das DGS-Korpus-Projekt erstellt ein Referenzkorpus der Deutschen Gebärdensprache (DGS) und macht mit dem Öffentlichen DGS-Korpus und dem korpusbasierten Wörterbuch der DGS diese Sprache in ihrer Vielfalt öffentlich zugänglich. Um den verschiedenen Nutzungsaspekten gerecht zu werden, stehen die Daten des Öffentlichen Korpus in drei verschiedenen Portalen zur Verfügung. Inhalte des Wörterbuchs werden bereits als Vorabeinträge veröffentlicht. Der Artikel gibt einen Überblick über die Inhalte und Funktionen der drei Portale sowie des Wörterbuchs, die untereinander verlinkt sind.

Reiner Konrad, Julian Bleicken, Calvin Khan, Amy Isard, Gabriele Langer, Anke Müller, Marc Schulder

How to be FAIR when you CARE: The DGS Corpus as a Case Study of Open Science Resources for Minority Languages

Article and video presentation on how the DGS Corpus implement ethical open data practices.

Marc Schulder, Thomas Hanke

How to be FAIR when you CARE: The DGS Corpus as a Case Study of Open Science Resources for Minority Languages

HamNoSys in TeX

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Latest version:
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Abstract

The Hamburg Notation System, HamNoSys for short, is a system for the phonetic transcription of signed languages. The TeX package hamnosys makes the HamNoSys font available in TeX documents.

Marc Schulder, Thomas Hanke

Collocations in Sign Language Lexicography: Towards Semantic Abstractions for Word Sense Discrimination

Abstract

In general monolingual lexicography a corpus-based approach to word sense discrimination (WSD) is the current standard. Automatically generated lexical profiles such as Word Sketches provide an overview on typical uses in the form of collocate lists grouped by their part of speech categories and their syntactic dependency relations to the base item. Collocates are sorted by their typicality according to frequency-based rankings. With the advancement of sign language (SL) corpora, SL lexicography can finally be based on actual language use as reflected in corpus data. In order to use such data effectively and gain new insights on sign usage, automatically generated collocation profiles need to be developed under the special conditions and circumstances of the SL data available. One of these conditions is that many of the prerequesites for the automatic syntactic parsing of corpora are not yet available for SL. In this article we describe a collocation summary generated from DGS Corpus data which is used for WSD as well as in entry-writing. The summary works based on the glosses used for lemmatisation. In addition, we explore how other resources can be utilised to add an additional layer of semantic grouping to the collocation analysis. For this experimental approach we use glosses, concepts, and wordnet supersenses.

Gabriele Langer, Marc Schulder

Extending the Public DGS Corpus in Size and Depth

Abstract

In 2018 the DGS-Korpus project published the first full release of the Public DGS Corpus. This event marked a change of focus for the project. While before most attention had been on increasing the size of the corpus, now an increase in its depth became the priority. New data formats were added, corpus annotation conventions were released and OpenPose pose information was published for all transcripts. The community and research portal websites of the corpus also received upgrades, including persistent identifiers, archival copies of previous releases and improvements to their usability on mobile devices. The research portal was enhanced even further, improving its transcript web viewer, adding a KWIC concordance view, introducing cross-references to other linguistic resources of DGS and making its entire interface available in German in addition to English. This article provides an overview of these changes, chronicling the evolution of the Public DGS Corpus from its first release in 2018, through its second release in 2019 until its third release in 2020.

Thomas Hanke, Marc Schulder, Reiner Konrad, Elena Jahn

OpenPose in the Public DGS Corpus (v2)

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Latest version:
Version 2:
Version 1:

Abstract

This project note gives an overview of how pose information was created for the Public DGS Corpus with the use of OpenPose. Pose information is machine-readable data that describes where people are located in an image, providing the coordinates for various points of each body, such as joints, eyes or ears. The data we generate consists of body, face and hand models for informants in every camera perspective of all published transcripts.