Herbert Lange


2022

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RefCo and its Checker: Improving Language Documentation Corpora’s Reusability Through a Semi-Automatic Review Process
Herbert Lange | Jocelyn Aznar
Proceedings of the Thirteenth Language Resources and Evaluation Conference

The QUEST (QUality ESTablished) project aims at ensuring the reusability of audio-visual 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.

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Metadata Formats for Learner Corpora: Case Study and Discussion
Herbert Lange
Proceedings of the 11th Workshop on NLP for Computer Assisted Language Learning

2020

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Proceedings of the 9th Workshop on NLP for Computer Assisted Language Learning
David Alfter | Elena Volodina | Ildikó Pilan | Herbert Lange | Lars Borin
Proceedings of the 9th Workshop on NLP for Computer Assisted Language Learning

2019

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Proceedings of the 8th Workshop on NLP for Computer Assisted Language Learning
David Alfter | Elena Volodina | Lars Borin | Ildikó Pilan | Herbert Lange
Proceedings of the 8th Workshop on NLP for Computer Assisted Language Learning

2018

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MULLE: A grammar-based Latin language learning tool to supplement the classroom setting
Herbert Lange | Peter Ljunglöf
Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications

MULLE is a tool for language learning that focuses on teaching Latin as a foreign language. It is aimed for easy integration into the traditional classroom setting and syllabus, which makes it distinct from other language learning tools that provide standalone learning experience. It uses grammar-based lessons and embraces methods of gamification to improve the learner motivation. The main type of exercise provided by our application is to practice translation, but it is also possible to shift the focus to vocabulary or morphology training.

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Demonstrating the MUSTE Language Learning Environment
Herbert Lange | Peter Ljunglöf
Proceedings of the 7th workshop on NLP for Computer Assisted Language Learning