The Multimodal Child Language Acquisition

The Multimodal Child Language Acquisition is a network of researchers from the University of Copenhagen and from the Chinese University of Hong Kong and the Hong Kong University. It is founded by the Danish Research Councils with start in March 2019 and end in February 2021. The network will mainly address research related to the use and role of gestures in child language acquisition focusing on bilingual children (English/Chinese, Danish/Chinese, Danish/English), but themes related to enetCollect, such as the analysis of code switching and code mixing in the various language combinations using NLP, and the use of crowdsourcing will also be addressed.

External links to the project
Not available yet.

Contact person in enetCollect for this project:

Costanza Navarretta

Large-Scale Information Extraction and Gamification for Crowdsourced Language Learning

The project aims at contributing to the activities of COST Action CA 16105 – enetCollect – in the areas related to large-scale information extraction from the web and gamification of the preparation and the annotation of multimedia content suitable for various language learning activities. We will explore advanced methods for web-scale crawling and semantic enrichment of the collected material as well as modern human-computer interaction technologies engaging users in the process of acquisition of languages in the form of a game.

External links to the project
Grant page
Project page

Contact person in enetCollect for this project:

Pavel Smrz

From parallel corpora to multilingual exercises – Making use of large text collections and crowdsourcing techniques for innovative autonomous language learning applications

Over the last few decades, there has been a shift in language teaching, from focused grammar and vocabulary learning to more intuitive use of the foreign language through examples. Large collections of translated texts, which are increasingly freely available, provide language learners with a variety of examples of word usage and grammar. The aim of the project is to find out which of these translations are most suitable for this purpose. To do so, we will combine findings from other areas with the judgments of language learners and teachers. We will take advantage of the qualities that a good example should have to automatically find appropriate translations in large collections of text and to generate exercises.

External links to the project
Grant page

Contact person in enetCollect for this project:

Johannes Graën

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