Project - DELOSIS: Τhe sensorimotor basis of causality and aspect and their expression with the verbs of pushing, pulling, crashing and hitting of Modern Greek
PROJECTS

DELOSIS: Τhe sensorimotor basis of causality and aspect and their expression with the verbs of pushing, pulling, crashing and hitting of Modern Greek

Start date: 20-06-2018
End date: 20-08-2019
Funded by: OP Human Resources Development, Education and Lifelong Learning, ESPA 2014-2020, Call EBD34
Project leader: Stella Markantonatou
 

DELOSIS will try to ground the abstract linguistic concepts “aktionsart” and “causality” on tangible sensorimotor features. Α subset of the Modern Greek verbs that denote pushing, pulling, crashing and beating events are used as a case study. The aim is to redefine the concepts on the basis of objective measurements. This is an interdisciplinary study that serves the theoretical and cognitive study of Modern Greek because it provides a deeper understanding of linguistic symbols. It also serves the study of the interaction between humans and computers as it couples sensorimotor with symbolic linguistic representations. This is a state-of-the-art study because it tries to connect human cognition with sensorimotor experience, which only recently has become measurable through computational devices. In this research, sensorimotor data will be collected with mocaps, haptic data will be collected with special sensors able to detect force and skin conductance response and vision data will be collected from videos available on the web. This research relies on two pillars: sensorimotor and linguistic data. The latter will be received from annotated corpora extracted from ΕΘΕΓ. The relation between sensorimotor and linguistic data will be studied with clustering and machine learning algorithms. This interdisciplinary study aims at:

  • the identification of sensorimotor parameters that can be related with abstract linguistic notions such as Actionsaart and causality.
  • the description of human cognitive functions with the help of the machine learning technology.
 
 

Research areas