Identification of Indigenous Knowledge Concepts through Semantic Networks, Spelling Tools and Word Embeddings

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 943–947 Marseille, 11–16 May 2020 c⃝ European Language Resources Association (ELRA), licensed under CC-BY-NC 943 Identification of Indigenous Knowledge Concepts through Semantic Networks, Spelling Tools and Word Embeddings Renato Rocha Souza1, Amelie Dorn1, Barbara Piringer1, Eveline Wandl-Vogt1 Austrian Centre for Digital Humanities and Cultural Heritage, Austrian Academy of Sciences1 Sonnenfelsgasse 19, Vienna, Austria1 {renato.souza, amelie.dorn, barbara.piringer, eveline.wandl-vogt}@oeaw.ac.at Abstract In order to access indigenous, regional knowledge contained in language corpora, semantic tools and network methods are most typically employed. In this paper we present an approach for the identification of dialectal variations of words, or words that do not pertain to High German, on the example of non-standard language legacy collection questionnaires of the Bavarian Dialects in Austria (DBÖ). Based on selected cultural categories relevant to the wider project context, common words from each of these cultural categories and their lemmas using GermaLemma were identified. Through word embedding models the semantic vicinity of each word was explored, followed by the use of German Wordnet (Germanet) and the Hunspell tool. Whilst none of these tools have a comprehensive coverage of standard German words, they serve as an indication of dialects in specific semantic hierarchies. Methods and tools applied in this study may serve as an example for other similar projects dealing with non-standard or endangered language collections, aiming to access, analyze and ultimately preserve native regional language heritage. Keywords: Digital Humanities; regional languages; lesser-resourced languages; knowledge discovery 1. Introduction In this paper we present a technique we have developed for identifying dialectal words in a non-standard language legacy dataset (DBÖ [Datenbank der bairischen Mundarten in Österreich/Database of Bavarian Dialects in Austria]). This collection was analyzed in the context of the DH project exploreAT! (Wandl-Vogt et al, 2015). The project exploreAT! – exploring Austria’s culture through the language glass evolved as a cross-disciplinary project at ACDH-OeAW since 2015. It brings together expertise from different disciplines and collaboration partners in the fields of cultural lexicography and open innovation (ACDH-OeAW, Austria), semantic technologies (ADAPT Centre, DCU, Ireland) and human-machine interaction via visualization (VisUSAL, Universidad de Salamanca, Spain) (Abgaz et al., 2018; Benito et al., 2016; 2018; Dorn et al, 2018). The project has given rise to, and enabled, the establishment of the Open Innovation Research Infrastructure (OI-RI) and exploration space at the Austrian Centre for Digital Humanities (ACDH-OeAW) at the Austrian Academy of Sciences The project more generally aims at making the implicit, but to-date still partially unlocked cultural knowledge contained within a non-standard language legacy dataset accessible, connectable and reusable for different disciplines and actor groups. Even though heterogeneous data offers a wide spectrum of different kinds of uncertainties to be addressed, we here more specifically focus on the analysis of uncertainties in linguistic, spatial and temporal aspects of our legacy language collection. The DBÖ collection is a valuable linguistic resource, containing regional, vernacular words that were spoken by the native community in an area of the former Austro- Hungarian empire. …

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