Open Universal Arabic ASR Leaderboard
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Abstract (arXiv)
In recent years, the enhanced capabilities of ASR models and the emergence of multi-dialect datasets have increasingly pushed Arabic ASR model development toward an all-dialect-in-one direction. This trend highlights the need for benchmarking studies that evaluate model performance on multiple dialects, providing the community with insights into models' generalization capabilities. In this paper, we introduce Open Universal Arabic ASR Leaderboard, a continuous benchmark project for open-source general Arabic ASR models across various multi-dialect datasets. We also provide a comprehensive analysis of the model's robustness, speaker adaptation, inference efficiency, and memory consumption. This work aims to offer the Arabic ASR community a reference for models' general performance and also establish a common evaluation framework for multi-dialectal Arabic ASR models.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 22 of its 31 references that are in the map. First posted on arXiv 18 Dec 2024.
Builds on
22 of 31 references.
References · 22
- 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
- 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,905
- 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,342
- 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,218
- 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,863
- 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,384
- 2022data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Languagecited by 727
- 2020Unsupervised Cross-lingual Representation Learning for Speech Recognitioncited by 501
- 2022FLEURS: Few-shot Learning Evaluation of Universal Representations of Speechcited by 469
- 2023Scaling Speech Technology to 1,000+ Languagescited by 411
- 2021W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Trainingcited by 347
- 2019NeMo: a toolkit for building AI applications using Neural Modulescited by 235
10 more
- 2023SeamlessM4T: Massively Multilingual & Multimodal Machine Translationcited by 125
- 2023Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognitioncited by 124
- 2017Speech Recognition Challenge in the Wild: Arabic MGB-3cited by 60
- 2024Open-Source Conversational AI with SpeechBrain 1.0cited by 56
- 2021Towards One Model to Rule All: Multilingual Strategy for Dialectal Code-Switching Arabic ASRcited by 41
- 2021QASR: QCRI Aljazeera Speech Resource -- A Large Scale Annotated Arabic Speech Corpuscited by 38
- 2023Stateful Conformer with Cache-based Inference for Streaming Automatic Speech Recognitioncited by 25
- 2023N-Shot Benchmarking of Whisper on Diverse Arabic Speech Recognitioncited by 20
- 2024Casablanca: Data and Models for Multidialectal Arabic Speech Recognitioncited by 20
- 2023LAraBench: Benchmarking Arabic AI with Large Language Modelscited by 16
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Citing papers per year: 2025: 4.
4 papers.
- 2025ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systemscited by 4
- 2025Advancing Arabic Speech Recognition Through Large-Scale Weakly Supervised Learningcited by 2
- 2025Flavors of Moonshine: Tiny Specialized ASR Models for Edge Devicescited by 2
- 2025Arabic ASR on the SADA Large-Scale Arabic Speech Corpus with Transformer-Based Modelscited by 0
- 2025Flavors of Moonshine: Tiny Specialized ASR Models for Edge Devices2 Sep 2025
- 2025Arabic ASR on the SADA Large-Scale Arabic Speech Corpus with Transformer-Based Models18 Aug 2025
- 2025ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems16 May 2025
- 2025Advancing Arabic Speech Recognition Through Large-Scale Weakly Supervised Learning16 Apr 2025