activity
20202022
most citedMulti-Dialect Arabic BERT for Country-Level Dialect Identification

46 citations · 47 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SD2022

Arabic Text-To-Speech (TTS) Data Preparation

Hala Al Masri, Muhy Eddin Za'ter

People may be puzzled by the fact that voice over recordings data sets exist in addition to Text-to-Speech (TTS), Synthesis system advancements, albeit this is not the case. The go…

cs.CV20221 cited

Bench-Marking And Improving Arabic Automatic Image Captioning Through The Use Of Multi-Task Learning Paradigm

Muhy Eddin Za'ter, Bashar Talafha

The continuous increase in the use of social media and the visual content on the internet have accelerated the research in computer vision field in general and the image captioning…

cs.CL2021

sarcasm detection and quantification in arabic tweets

Bashar Talafha, Muhy Eddin Za'ter, Samer Suleiman +2

The role of predicting sarcasm in the text is known as automatic sarcasm detection. Given the prevalence and challenges of sarcasm in sentiment-bearing text, this is a critical pha…

cs.CL2020

SPARTA: Speaker Profiling for ARabic TAlk

Wael Farhan, Muhy Eddin Za'ter, Qusai Abu Obaidah +3

This paper proposes a novel approach to an automatic estimation of three speaker traits from Arabic speech: gender, emotion, and dialect. After showing promising results on differe…

cs.CL202046 cited

Multi-Dialect Arabic BERT for Country-Level Dialect Identification

Bashar Talafha, Mohammad Ali, Muhy Eddin Za'ter +5

Arabic dialect identification is a complex problem for a number of inherent properties of the language itself. In this paper, we present the experiments conducted, and the models d…