Improvement of a Sign Language Learning Reinforcement Tool Through Phonological Proximity

The study of sign languages (SL) has generated great interest in the fields of linguistics, computing and teaching. Teaching and learning SL are complex tasks, since they are rarely taught by people who are fluent both in SL and the native language of the students. These lessons taught by deaf people are irreplaceable, but it is appropriate for the student to have support mechanisms in the process. This paper presents a SL learning reinforcement tool that uses phonological proximity to improve the obtained results. The methodology used consisted of mapping the phonological parameters of each sign in the lexicon to numerical values and then constructing a matrix where each sign is compared with the others by means of a classic measure of similarity. As far as the authors know, this is the first time that this type of proposal is made for Costa Rican SL (LESCO, for its Spanish acronym), incorporating phonological proximity in a reinforcement tool. The operation of a graphical software tool is explained, showing grouped concepts and reproducing the signs, interfacing with the computerized avatar of the already operational International Platform for Sign Language Edition (PIELS, for its Spanish acronym), expanding its current functionality by learning signs with similar handshapes. For these purposes, homonyms, paronyms, and polysemy are explored, to the extent that these concepts apply to SL. The incorporation of phonological proximity to the tool is explored, in order to reinforce LESCO learning, offering the possibility of using the same approach in any other SL.