The primary goal of the workshop series on Natural Language Processing for Computer-Assisted Language Learning (NLP4CALL) is to create a meeting place for researchers working on the integration of Natural Language Processing and Speech Technologies in CALL systems and exploring the theoretical and methodological issues arising in this connection. The latter includes, among others, insights from Second Language Acquisition (SLA) research, on the one hand, and promoting the development of “Computational SLA” through setting up Second Language research infrastructure(s), on the other.
The intersection of Natural Language Processing (or Language Technology / Computational Linguistics) and Speech Technology with Computer-Assisted Language Learning (CALL) brings “understanding” of language to CALL tools, thus making CALL intelligent. This fact has given the name for this area of research – Intelligent CALL, ICALL. As the definition suggests, apart from having excellent knowledge of Natural Language Processing and/or Speech Technology, ICALL researchers need good insights into second language acquisition theories and practices, as well as knowledge of second language pedagogy and didactics. This workshop invites therefore a wide range of ICALL-relevant research, including studies where NLP-enriched tools are used for testing SLA and pedagogical theories, and vice versa, where SLA theories, pedagogical practices or empirical data are modeled in ICALL tools. The NLP4CALL workshop series is aimed at bringing together competencies from these areas for sharing experiences and brainstorming around the future of the field.
We invited submissions:
- that describe research directly aimed at ICALL;
- that demonstrate actual or discuss the potential use of existing Language and Speech Technologies or resources for language learning;
- that describe the ongoing development of resources and tools with potential usage in ICALL, either directly in interactive applications, or indirectly in materials, application or curriculum development, e.g. learning material generation, assessment of learner texts/responses, individualized learning solutions, provision of feedback;
- that discuss challenges and/or research agenda for ICALL;
- that describe empirical studies on language learner data.
A special focus was given to established and upcoming infrastructures aimed at SLA and learner corpus research, covering questions such as data collection, legal issues, reliability of annotation, annotation tool development and search environments for SLA-relevant data. We encouraged paper presentations and software demonstrations describing the above-mentioned themes primarily, but not exclusively, for the Nordic languages.