Visualizing lects in a sign language corpus: Mining lexical variation data in lects of Swedish Sign Language
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Detalles
In this paper, we discuss the possibilities for mining lexical variation data across (potential) lects in Swedish Sign Language (SSL). The data come from the SSL Corpus (SSLC), a continuously expanding corpus of SSL, its latest release containing 43 307 annotated sign tokens, distributed over 42 signers and 75 time-aligned video and annotation files. After extracting the raw data from the SSLC annotation files, we created a database for investigating lexical distribution/variation across three possible lects, by merging the raw data with an external metadata file, containing information about the age, gender, and regional background of each of the 42 signers in the corpus. We go on to present a first version of an easy-to-use graphical user interface (GUI) that can be used as a tool for investigating lexical variation across different lects, and demonstrate a few interesting finds. This tool makes it easier for researchers and non-researchers alike to have the corpus frequencies for individual signs visualized in an instant, and the tool can easily be updated with future expansions of the SSLC.
En: Eleni Efthimiou, Stavroula-Evita Fotinea, Thomas Hanke, Julie Hochgesang, Jette Kristoffersen & Johanna Mesch (eds.), Proceedings of the 7th Workshop on the Representation and Processing of Sign Languages: Corpus Mining [Language Resources and Evaluation Conference (LREC)], 13–18.