SiLearn: an intelligent sign vocabulary learning tool

Abstract

Purpose Vocabulary learning is a difficult task for children without hearing ability. Absence of enough learning centers and effective learning tools aggravate the problem. Modern technology can be utilized fruitfully to find solutions to the learning difficulties experienced by the deaf. The purpose of this paper is to present SiLearn – a novel technology based tool for teaching/learning sign vocabulary. Design/methodology/approach The proposed mobile application can act as a visual dictionary for deaf people. SiLearn is equipped with features that can automatically detect both text and physical objects and convert them to their corresponding signs. For testing the effectiveness of the proposed mobile application quantitative analyses were done. Quantitative analysis is based on testing a class of 28 students belonging to St Clare Oral School for the Deaf, Kerala, India. This group consisted of 17 boys and 11 girls. Analysis was also done through questionnaire. Questionnaires were given to teachers, parents of deaf students learning sign language and other sign language learners. Findings Results indicate that as SiLearn is very effective in sign vocabulary development. It can enhance vocabulary learning rate considerably. Originality/value This is the first time that artificial intelligence (AI) based techniques are used for early stage sign language learning. SiLearn can equally be used by children, parents and teachers for learning sign language.

Computer-Assisted Vocabulary Learning for Thai Deaf Students: A Case Study of Sot Suksa School for the Deaf

“…The results raise interesting questions regarding the threshold at which technology intervention for vocabulary learning becomes appropriate for the Deaf. While some studies have pointed to language as being the fundamental building block for reading and vocabulary (Joy et al, 2019;Mayberry et al, 2011;Schirmer et al, 2004), others have pointed to a proportional relationship between skills such as word recognition and vocabulary (Easterbrooks et al, 2015;Lasasso & Crain, 2015;Scarborough, 2001). It would seem, therefore, that the students in this study may be lacking in underpinning language skills.…”

“…Concerning the Deaf, the report affirmed that learning the mother tongue language should precede learning to read or write. Unfortunately, for the Deaf, the mother tongue language is typically sign language (Razalli et al, 2018), which, unless born into a deaf family, is unlikely to be a natural acquisition (Joy et al, 2019;Razalli et al, 2018). Conversely, children born of deaf parents (second generation Deaf) often acquire sign language through natural exposure in the same way the hearing-abled acquire speech (Joy et al, 2019).…”

Artificial Intelligence Technologies for Sign Language

“…Liang et al [117] Windows desktop British Dementia screening Zhou et al [118] iOS Hong Kong Translation Ozarkar et al [119] Android Indian Translation Joy et al [120] Android Indian Learning Paudyal et al [121] Android American Learning Luccio et al [122] Android Multiple Learning Chaikaew et al [123] Android, iOS Thai Learning Ku et al [124] -American Translation Potamianos et al [125] -Greek Learning Lee et al [126] -Korean Translation Schioppo et al [127] -American Learning Bansal et al [128] -American Learning Quandt et al [129] -American Learning…”

“…Furthermore, a deep learning-based approach for isolated sign recognition of GSL was introduced. On the other hand, Joy et al in [ 120 ], proposed a mobile application that could be used as a visual dictionary for children. It consisted of two modules: an object detection module and a word recognition module.…”

A Systematic Review and Meta-Analysis of Vocabulary Interventions for Deaf/Hard of Hearing Children and Adolescents

“…There were 13 studies that took place in the United States of America. The others were conducted in Australia (Paatsch et al, 2006;Salins et al, 2021), Hong Kong (Fung et al, 2005), India (Joy et al, 2019), Iran (Zamani et al, 2016), Italy (Majorano et al, 2017), the Netherlands (van Berkel-van Hoof et al, 2020;Wauters et al, 2001), South Africa (van Staden, 2013, Thailand (Plaewfueang & Suksakulchai, 2020;Wicha, Chakpitak, & Adipattaranan, 2012), and Turkey (Birinci & Sarıçoban, 2021).…”