activity
20232026
most citedLAraBench: Benchmarking Arabic AI with Large Language Models

14 citations · 20 across the 10 of their papers we have counts for

collaborators

10 papers

cs.SD2026

DeepFense: A Unified, Modular, and Extensible Framework for Robust Deepfake Audio Detection

Yassine El Kheir, Arnab Das, Yixuan Xiao +6

Speech deepfake detection is a well-established research field with different models, datasets, and training strategies. However, the lack of standardized implementations and evalu…

cs.SD2026

IQRA 2026: Interspeech Challenge on Automatic Pronunciation Assessment for Modern Standard Arabic (MSA)

Yassine El Kheir, Amit Meghanani, Mostafa Shahin +5

We present the findings of the second edition of the IQRA Interspeech Challenge, a challenge on automatic Mispronunciation Detection and Diagnosis (MDD) for Modern Standard Arabic…

cs.SD2025

Towards a Unified Benchmark for Arabic Pronunciation Assessment: Quranic Recitation as Case Study

Yassine El Kheir, Omnia Ibrahim, Amit Meghanani +12

We present a unified benchmark for mispronunciation detection in Modern Standard Arabic (MSA) using Qur'anic recitation as a case study. Our approach lays the groundwork for advanc…

cs.CL2025

MorphBPE: A Morpho-Aware Tokenizer Bridging Linguistic Complexity for Efficient LLM Training Across Morphologies

Ehsaneddin Asgari, Yassine El Kheir, Mohammad Ali Sadraei Javaheri

Tokenization is fundamental to Natural Language Processing (NLP), directly impacting model efficiency and linguistic fidelity. While Byte Pair Encoding (BPE) is widely used in Larg…

cs.CL2025★ 5 cited

Fanar: An Arabic-Centric Multimodal Generative AI Platform

Fanar Team, Ummar Abbas, Mohammad Shahmeer Ahmad +39

We present Fanar, a platform for Arabic-centric multimodal generative AI systems, that supports language, speech and image generation tasks. At the heart of Fanar are Fanar Star an…

cs.CL2023

L1-aware Multilingual Mispronunciation Detection Framework

Yassine El Kheir, Shammur Absar Chowdhury, Ahmed Ali

The phonological discrepancies between a speaker's native (L1) and the non-native language (L2) serves as a major factor for mispronunciation. This paper introduces a novel multili…

cs.CL2023★ 1 cited

The complementary roles of non-verbal cues for Robust Pronunciation Assessment

Yassine El Kheir, Shammur Absar Chowdhury, Ahmed Ali

Research on pronunciation assessment systems focuses on utilizing phonetic and phonological aspects of non-native (L2) speech, often neglecting the rich layer of information hidden…

eess.AS2023

MyVoice: Arabic Speech Resource Collaboration Platform

Yousseif Elshahawy, Yassine El Kheir, Shammur Absar Chowdhury +1

We introduce MyVoice, a crowdsourcing platform designed to collect Arabic speech to enhance dialectal speech technologies. This platform offers an opportunity to design large diale…

cs.SD2023

Multi-View Multi-Task Representation Learning for Mispronunciation Detection

Yassine El Kheir, Shammur Absar Chowdhury, Ahmed Ali

The disparity in phonology between learner's native (L1) and target (L2) language poses a significant challenge for mispronunciation detection and diagnosis (MDD) systems. This cha…

cs.CL2023★ 14 cited

LAraBench: Benchmarking Arabic AI with Large Language Models

Ahmed Abdelali, Hamdy Mubarak, Shammur Absar Chowdhury +13

Recent advancements in Large Language Models (LLMs) have significantly influenced the landscape of language and speech research. Despite this progress, these models lack specific b…