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A Proposed Semantic Machine Translation System fortranslating Arabic text to Arabic sign language

Ameera M.Almasoud Hend S. Al-Khalifa
by

Shimaa Ahmed

on 23 March 2012

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Transcript of A Proposed Semantic Machine Translation System fortranslating Arabic text to Arabic sign language

Semantic
Machine Translation
for Arabic sign language By: Shima Ahmed
Undersupervision of: Prof. Hesham El-Mahdy 1. Introduction
2. Writing Sign Language
3. Sign Language Through Years
4. Ontology
5.Proposed System



Agenda World : 17 Million deaf people 88,000 saudians deaf people (till 2011) Result:
Many Applications Target Deaf People
!!! Problem Statement Deaf people are facing many difficulties when communicating with other hearing because there are limited resources of information written in their language. Research works done before, focused only on translating words to signs and did not take care of the semantics of the translated sentence or the translation rules of Arabic text to Arabic sign language. Let's Understand Arabic Sign Language ArSL Manual Features Non-Manual Features Head Eyes Face Hands
Shape Hands
Orientation Hands
Location
ArSL is limited to represent nouns, adjectives and verbs. Sign language is represented visually and it cannot be read as other written languages. Writing Sign Language 1. Introduction
2. Writing Sign Language
3. Sign Language Through Years
4. Ontology
5. Proposed System



Agenda ERROR ! There are few attempts to write sign language Sign Writing
HamNoSys Stokoe Notation 1960 Writing SL using symbols similar in
the form to English alphabet symbols 1989 Based on Stokoe Notation in addition to set of parameters set at the end of the word representation such as: shape, location, orientation, extended finger orientation and movement of both dominant and the nondominant hands in addition to NMF representation. HamNoSys notations example for: “Oh! Look! There!” sentence. Valerie Sutton- 1974 Symbols used in this system are
pictures that are similar to the
real forms. Word 'Girl' using Sign writing Summary of Notations 1. Introduction
2. Writing Sign Language
3. Sign Language Through Years
4. Ontology
5. Proposed System



Agenda 2008 2006 2006 Ahmed & Seong El-Mohndes The system has a database to store Arabic dictionary
words with the corresponding signs and file names of the sign representation video. If the user enters a word that is available in the database then the recorded clip will be shown, if the word is not included then finger spelling is done. Tawassol Arabic system for translating Arabic text to Arabic SL.
The system is used as an educational tool and It
contains a translator, a dictionary of Arabic words
for a set of categories, in addition to a finger spelling
editor. Writing and reading text messages in signs as an alternative to SMS on mobile phones.

The SignWriting notation system was used to convert text to sign message and sign to text message in two-way communication. 1. Introduction
2. Writing Sign Language
3. Sign Language Through Years
4. Ontology
5. Proposed System



Agenda Ontology An abstract model of some phenomenon in the world by having identified the relevant concepts of that phenomenon. A Proposed Semantic Machine Translation System for translating Arabic text to Arabic sign language Ameera M.Almasoud
Hend S. Al-Khalifa Riyadh, Saudi Arabia-2011 Arabian Deaf People Deaf People Muslim
Deaf People TARGET!! Member (cc) photo by theaucitron on Flickr Relations:
Is-a.
Is a kind of.
Is a synonym of. Prayer Domain Into Ontology Proposed System Structure Let's Go Inside Morphological analysis: This process takes Arabic text as an input and sends each sentence to the Morphological Analysis and Disambiguation for Arabic (MADA) tool for Part of Speech (POS) tagging. MADA returns a feature line for each word in the
inputted sentence, feature line consist of a set of <feature>:<value> pairs. Word features such as (Gender, Mood,Case … etc), POS (Nouns, Verbs, Adjectives, Pronouns … etc) and proclitic (the word, question, conjunction, preposition... etc), enclitics associated with (person, gender, number), the rest include the diacritic form (diac), the lexeme/lemma (lex), the
Buckwalter tag (bw) and the gloss (gloss). Grammatical transformation: The grammatical transformation process takes the previous results as input and applies the Arabic Sign Language rules on each word depending on its feature. Semantic translation: This process takes the result of the previous process and search for each word in the Domain Ontology to get the word sign code. If the word does not have a corresponding sign then replace this word by one of its synonyms that have a sign in the SignWriting Database (DB).

Then, replace each sign code by the corresponding sign symbol stored in the SignWriting DB. If the word does not have a corresponding sign in the domain ontology, it will be finger spelled. That's It !!! Drawbacks: The proposed system doesn't target a wide layer of SL people (Arabian Muslims). The evaluation criteria is not efficient, they depend on the experts opinion. Targets a very narrow domain of words (prayer domain). 1. Introduction
2. Writing Sign Language
3. Sign Language Through Years
4. Ontology
5. Proposed System



Agenda
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