Proceedings of the Second Workshop on Linguistic and Neurocognitive Resources
In the proceedings of the first LiNCR (pronounced ‘linker’) workshop in 2018, we stated that the aim of
the workshop was to provide a venue to share and explore a new generation of language resources which
link and aggregate cognitive, behavioural, neuroimaging and linguistic data. Our vision was to provide
a forum for research that leads to the development of methods for the integration of neuro-cognitive
data on language function with linguistic facts, the interpretation of experimental data when linked to
rich linguistic information, and demonstrations of how new insights can be drawn from this powerful
approach in domains such as language learning and neuro-cognitive deficits. We envisioned that there
will be many future LiNCR workshops, just as the current 2nd workshop that we are presenting now.
What we did not foresee, however, was that we won’t be able to meet face-to-face and strengthen our
links during this time of social distancing.
Nevertheless, the eight papers for presentation in this workshop will continue to showcase the innovative
nature and potential for impact of this interdisciplinary and data-driven framework for understanding
language and cognition. Three significant datasets are presented: the Little Prince corpus for neurocognitive
studies in 26 languages, sensorimotor norms for Russian, and a dataset for complex emotion
learning. Three papers focus on leveraging neuro-cognitive measurement for language technology, or
vice versa. Finally, two papers deal with practical issues, such as fonts for dyslexia readers and language
models for cloze task answer generation. The eclectic nature of these paper underlines both the vast
frontiers to be explored yet as well as the versatility of linked linguistic and neuro-cognitive resources.
Most of all, we look forward to the third LiNCR to update our new findings, to overcome the temporary
physical distances, and possibly even to show how linked linguistic and neuro-cognitive databases can
shed light on issues related to epidemiology and public health.