ESL127: Emirate Sign Language Dataset(s) and e-Dictionary (Version 2.0) Utilizing Deep Learning Recognition Models

Ahmed Abdelhadi Ahmed, Munkhjargal Gochoo, Mohamad Taghizadeh, Munkh Erdene Otgonbold, Ganzorig Batnasan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As stated by the United Arab Emirates's (UAE) Community Development Authority (CDA), there are around 3,065 individuals with hearing disabilities in the country. These individuals often struggle to communicate with broader society and rely on scarce sign language (SL) interpreters. Moreover, Arabic's dialects diversity compounds the issue by causing dialects in the Arabic Sign Language (ArSL). Hence, the call for a standardized reference for ArSL in the region is a priority. To address these challenges, we've developed an Emirate Sign Language (ESL) electronic dictionary (e-dictionary) with a dataset of 127 signs and 50 sentences, recorded by hearing-impaired individuals in the UAE with various degrees of deafness. Supervised by certified interpreters and validated by ESL's department head at CDA in Dubai, the recordings were made using Azure Kinect DK, resulting in 708 recordings. The dataset is then processed to 10fps. The e-dictionary offers features such as webcam-based sign recognition using YOLOv8 technology, voice-based signing via Arabic Automatic Speech Recognition, text-based signing, and words spelling in ArSL.

Original languageEnglish
Title of host publication2023 15th International Conference on Innovations in Information Technology, IIT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages174-179
Number of pages6
ISBN (Electronic)9798350382396
DOIs
Publication statusPublished - 2023
Event15th International Conference on Innovations in Information Technology, IIT 2023 - Al Ain, United Arab Emirates
Duration: Nov 14 2023Nov 15 2023

Publication series

Name2023 15th International Conference on Innovations in Information Technology, IIT 2023

Conference

Conference15th International Conference on Innovations in Information Technology, IIT 2023
Country/TerritoryUnited Arab Emirates
CityAl Ain
Period11/14/2311/15/23

Keywords

  • Emirate sign language
  • Signs recognition
  • Text-based signing
  • dataset
  • electronic dictionary

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Fingerprint

Dive into the research topics of 'ESL127: Emirate Sign Language Dataset(s) and e-Dictionary (Version 2.0) Utilizing Deep Learning Recognition Models'. Together they form a unique fingerprint.

Cite this