

The first was built from school level language instruction material and contains 203 signed sentences and 710 signs. We have constructed two parallel Arabic text-to-ArSL corpora for our system. The time and effort involved in building such a parallel corpus of text and visual signs from scratch mean that we will inevitably be working with quite small corpora. Further, the corpus must facilitate output in visual form, which is clearly far more difficult than producing textual output. First,the lack of a standard writing system requires the building of a parallel text-to-sign language corpus from scratch, as well as computational tools to prepare this parallel corpus. In addition to the familiar technical problems of text-to-text machine translation,building a system for sign language translation requires overcoming some additional challenges. Its icon will also be added to your device home screen.This dissertation presents the first corpus-based system for translation from Arabic text into Arabic Sign Language (ArSL) for the deaf and hearing impaired, for whom it can facilitate access to conventional media and allow communication with hearing people. Once installation is finished you can tap on the OPEN button to start it.Tap on it to start the actual installation of the iOS app. After Al Manhal is downloaded, you'll see an INSTALL button to the right.


The latest version released by its developer is 6.0.1. The company that develops Al Manhal is TechKnowledge General Trading LLC. Al Manhal is a free app for iOS published in the Reference Tools list of apps, part of Education.
