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RefCo and its Checker: Improving Language Documentation Corpora's Reusability Through a Semi-Automatic Review Process

Domain:

natural language processing

Record type:

paperdataset
Creator:
LanAzn
Editor:
LeiCen
Publisher:
CCSD
Host:avatar
International audience The QUEST (QUality ESTablished) project aims at ensuring the reusability of audiovisual datasets (Wamprechtshammer et al., 2022) by devising quality criteria and curating processes. RefCo (Reference Corpora) is an initiative within QUEST in collaboration with DoReCo (Documentation Reference Corpus, Paschen et al. (2020)) focusing on language documentation projects. Previously, Aznar and Seifart (2020) introduced a set of quality criteria dedicated to documenting fieldwork corpora. Based on these criteria, we establish a semi-automatic review process for existing and work-in-progress corpora, in particular for language documentation. The goal is to improve the quality of a corpus by increasing its reusability. A central part of this process is a template for machine-readable corpus documentation and automatic data verification based on this documentation. In addition to the documentation and automatic verification, the process involves a human review and potentially results in a RefCo certification of the corpus. For each of these steps, we provide guidelines and manuals. We describe the evaluation process in detail, highlight the current limits for automatic evaluation and how the manual review is organized accordingly.

Visit

hal.science

Tags

language documentationannotated corporaoral languagelanguage resourcesquality checkingreusabilityQUEST[SHS.LANGUE]Humanities and Social Sciences/Linguistics[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing

Licenses

info:eu-repo/semantics/OpenAccess

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Background and Purpose: