Alexander König


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An Experiment on Implicitly Crowdsourcing Expert Knowledge about Romanian Synonyms from Language Learners
Lionel Nicolas | Lavinia Nicoleta Aparaschivei | Verena Lyding | Christos Rodosthenous | Federico Sangati | Alexander König | Corina Forascu
Proceedings of the 10th Workshop on NLP for Computer Assisted Language Learning


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CLARIN: Distributed Language Resources and Technology in a European Infrastructure
Maria Eskevich | Franciska de Jong | Alexander König | Darja Fišer | Dieter Van Uytvanck | Tero Aalto | Lars Borin | Olga Gerassimenko | Jan Hajic | Henk van den Heuvel | Neeme Kahusk | Krista Liin | Martin Matthiesen | Stelios Piperidis | Kadri Vider
Proceedings of the 1st International Workshop on Language Technology Platforms

CLARIN is a European Research Infrastructure providing access to digital language resources and tools from across Europe and beyond to researchers in the humanities and social sciences. This paper focuses on CLARIN as a platform for the sharing of language resources. It zooms in on the service offer for the aggregation of language repositories and the value proposition for a number of communities that benefit from the enhanced visibility of their data and services as a result of integration in CLARIN. The enhanced findability of language resources is serving the social sciences and humanities (SSH) community at large and supports research communities that aim to collaborate based on virtual collections for a specific domain. The paper also addresses the wider landscape of service platforms based on language technologies which has the potential of becoming a powerful set of interoperable facilities to a variety of communities of use.

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Creating Expert Knowledge by Relying on Language Learners: a Generic Approach for Mass-Producing Language Resources by Combining Implicit Crowdsourcing and Language Learning
Lionel Nicolas | Verena Lyding | Claudia Borg | Corina Forascu | Karën Fort | Katerina Zdravkova | Iztok Kosem | Jaka Čibej | Špela Arhar Holdt | Alice Millour | Alexander König | Christos Rodosthenous | Federico Sangati | Umair ul Hassan | Anisia Katinskaia | Anabela Barreiro | Lavinia Aparaschivei | Yaakov HaCohen-Kerner
Proceedings of the 12th Language Resources and Evaluation Conference

We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved. We present the approach by explaining its core paradigm that consists in pairing specific types of LRs with specific exercises, by detailing both its strengths and challenges, and by discussing how much these challenges have been addressed at present. Accordingly, we also report on on-going proof-of-concept efforts aiming at developing the first prototypical implementation of the approach in order to correct and extend an LR called ConceptNet based on the input crowdsourced from language learners. We then present an international network called the European Network for Combining Language Learning with Crowdsourcing Techniques (enetCollect) that provides the context to accelerate the implementation of this generic approach. Finally, we exemplify how it can be used in several language learning scenarios to produce a multitude of NLP resources and how it can therefore alleviate the long-standing NLP issue of the lack of LRs.

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Using Crowdsourced Exercises for Vocabulary Training to Expand ConceptNet
Christos Rodosthenous | Verena Lyding | Federico Sangati | Alexander König | Umair ul Hassan | Lionel Nicolas | Jolita Horbacauskiene | Anisia Katinskaia | Lavinia Aparaschivei
Proceedings of the 12th Language Resources and Evaluation Conference

In this work, we report on a crowdsourcing experiment conducted using the V-TREL vocabulary trainer which is accessed via a Telegram chatbot interface to gather knowledge on word relations suitable for expanding ConceptNet. V-TREL is built on top of a generic architecture implementing the implicit crowdsourding paradigm in order to offer vocabulary training exercises generated from the commonsense knowledge-base ConceptNet and – in the background – to collect and evaluate the learners’ answers to extend ConceptNet with new words. In the experiment about 90 university students learning English at C1 level, based on Common European Framework of Reference for Languages (CEFR), trained their vocabulary with V-TREL over a period of 16 calendar days. The experiment allowed to gather more than 12,000 answers from learners on different question types. In this paper we present in detail the experimental setup and the outcome of the experiment, which indicates the potential of our approach for both crowdsourcing data as well as fostering vocabulary skills.

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Digital Language Infrastructures – Documenting Language Actors
Verena Lyding | Alexander König | Monica Pretti
Proceedings of the 12th Language Resources and Evaluation Conference

The major European language infrastructure initiatives like CLARIN (Hinrichs and Krauwer, 2014), DARIAH (Edmond et al., 2017) or Europeana (Europeana Foundation, 2015) have been built by focusing in the first place on institutions of larger scale, like specialized research departments and larger official units like national libraries, etc. However, besides these principal players also a large number of smaller language actors could contribute to and benefit from language infrastructures. Especially since these smaller institutions, like local libraries, archives and publishers, often collect, manage and host language resources of particular value for their geographical and cultural region, it seems highly relevant to find ways of engaging and connecting them to existing European infrastructure initiatives. In this article, we first highlight the need for reaching out to smaller local language actors and discuss challenges related to this ambition. Then we present the first step in how this objective was approached within a local language infrastructure project, namely by means of a structured documentation of the local language actors landscape in South Tyrol. We describe how the documentation efforts were structured and organized, and what tool we have set up to distribute the collected data online, by adapting existing CLARIN solutions.

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Substituto – A Synchronous Educational Language Game for Simultaneous Teaching and Crowdsourcing
Marianne Grace Araneta | Gülşen Eryiğit | Alexander König | Ji-Ung Lee | Ana Luís | Verena Lyding | Lionel Nicolas | Christos Rodosthenous | Federico Sangati
Proceedings of the 9th Workshop on NLP for Computer Assisted Language Learning


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v-trel: Vocabulary Trainer for Tracing Word Relations - An Implicit Crowdsourcing Approach
Verena Lyding | Christos Rodosthenous | Federico Sangati | Umair ul Hassan | Lionel Nicolas | Alexander König | Jolita Horbacauskiene | Anisia Katinskaia
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

In this paper, we present our work on developing a vocabulary trainer that uses exercises generated from language resources such as ConceptNet and crowdsources the responses of the learners to enrich the language resource. We performed an empirical evaluation of our approach with 60 non-native speakers over two days, which shows that new entries to expand Concept-Net can efficiently be gathered through vocabulary exercises on word relations. We also report on the feedback gathered from the users and an expert from language teaching, and discuss the potential of the vocabulary trainer application from the user and language learner perspective. The feedback suggests that v-trel has educational potential, while in its current state some shortcomings could be identified.