Gender identification for Egyptian Arabic dialect in twitter using deep learning models
نویسندگان
چکیده
منابع مشابه
Spoken Arabic Dialect Identification Using Phonotactic Modeling
The Arabic language is a collection of multiple variants, among which Modern Standard Arabic (MSA) has a special status as the formal written standard language of the media, culture and education across the Arab world. The other variants are informal spoken dialects that are the media of communication for daily life. Arabic dialects differ substantially from MSA and each other in terms of phono...
متن کاملArabic Dialect Identification
The written form of the Arabic language, Modern Standard Arabic (MSA), differs in a nontrivial manner from the various spoken regional dialects of Arabic – the true “native languages” of Arabic speakers. Those dialects, in turn, differ quite a bit from each other. However, due to MSA’s prevalence in written form, almost all Arabic datasets have predominantly MSA content. In this article, we des...
متن کاملDomain and Dialect Adaptation for Machine Translation into Egyptian Arabic
In this paper, we present a statistical machine translation system for English to Dialectal Arabic (DA), using Modern Standard Arabic (MSA) as a pivot. We create a core system to translate from English to MSA using a large bilingual parallel corpus. Then, we design two separate pathways for translation from MSA into DA: a two-step domain and dialect adaptation system and a one-step simultaneous...
متن کاملCollecting Arabic Dialect Variations using Games With A Purpose: A Case Study Targeting the Egyptian Dialect
Arabs throughout the Arab world speak different dialects of Arabic in their daily conversations. We envision collecting a data set that maps different Arabic variations and dialects to Modern Standard Arabic (MSA). These mappings can be then used to facilitate the communication among Arabs from different regions. In this work, we developed a Game With A Purpose (GWAP) to collect mappings betwee...
متن کاملVerifiably Effective Arabic Dialect Identification
Several recent papers on Arabic dialect identification have hinted that using a word unigram model is sufficient and effective for the task. However, most previous work was done on a standard fairly homogeneous dataset of dialectal user comments. In this paper, we show that training on the standard dataset does not generalize, because a unigram model may be tuned to topics in the comments and d...
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ژورنال
عنوان ژورنال: Egyptian Informatics Journal
سال: 2020
ISSN: 1110-8665
DOI: 10.1016/j.eij.2020.04.001