no code implementations • NIDCP (LREC) 2022 • Verena Lyding, Lionel Nicolas, Alexander König
We first list the types of NLP resources most used within its community and second propose a set of blueprints for mapping these resources to well-established language learning exercises as found in standard language learning textbooks.
no code implementations • LREC 2020 • Lionel Nicolas, Verena Lyding, Claudia Borg, Corina Forascu, Kar{\"e}n Fort, Katerina Zdravkova, Iztok Kosem, Jaka {\v{C}}ibej, {\v{S}}pela Arhar Holdt, Alice Millour, Alex K{\"o}nig, er, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Anisia Katinskaia, Anabela Barreiro, Lavinia Aparaschivei, Yaakov HaCohen-Kerner
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.
no code implementations • LREC 2020 • Christos Rodosthenous, Verena Lyding, Federico Sangati, Alex K{\"o}nig, er, Umair ul Hassan, Lionel Nicolas, Jolita Horbacauskiene, Anisia Katinskaia, Lavinia Aparaschivei
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.
no code implementations • LREC 2020 • Verena Lyding, Alex K{\"o}nig, er, Monica Pretti
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.
no code implementations • RANLP 2019 • Verena Lyding, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Lionel Nicolas, Alex K{\"o}nig, er, Jolita Horbacauskiene, Anisia Katinskaia
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.
no code implementations • LREC 2016 • Verena Lyding, Karin Sch{\"o}ne
In this paper, we report on the design and development of an online search platform for the MERLIN corpus of learner texts in Czech, German and Italian.
no code implementations • LREC 2014 • Verena Lyding, Lionel Nicolas, Egon Stemle
In this article, we present interHist, a compact visualization for the interactive exploration of results to complex corpus queries.