# The MGB-2 Challenge: Arabic Multi-Dialect Broadcast Media Recognition

arXiv: https://arxiv.org/abs/1609.05625 · HTML: https://mlsanity.com/paper/1609.05625/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2016.

## Built on by (most cited first, 22 of 22)

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- [HARNESS: Lightweight Distilled Arabic Speech Foundation Models](https://mlsanity.com/paper/2509.14689/) (2025)
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- [ARCADE: A City-Scale Corpus for Fine-Grained Arabic Dialect Tagging](https://mlsanity.com/paper/2601.02209/) (2026)
- [Doing More with Less: Data Augmentation for Sudanese Dialect Automatic Speech Recognition](https://mlsanity.com/paper/2601.06802/) (2026)
- [Bulbul: A Dataset for Dialectal Arabic Speech Recognition](https://mlsanity.com/paper/2608.21950/) (2026)
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- [Zero-Shot Context-Aware ASR for Diverse Arabic Varieties](https://mlsanity.com/paper/2511.18774/) (2025)
- [HARNESS: Lightweight Distilled Arabic Speech Foundation Models](https://mlsanity.com/paper/2604.14186/) (2026)
- [Nuha-Speech: Building General-Purpose Arabic Speech-LLMs](https://mlsanity.com/paper/2609.11892/) (2026)
- [NADI 2026: The Second Multidialectal Arabic Speech Processing Shared Task](https://mlsanity.com/paper/2609.27086/) (2026)
- [CARDAMOM: A Micro-Dialectal Arabic Speech Dataset for ASR](https://mlsanity.com/paper/2609.34481/) (2026)
- [Almieyar: A Culturally Grounded Benchmark for Multi-Dialect Arabic Speech Recognition](https://mlsanity.com/paper/2609.35564/) (2026)
- [Child ASR Adaptation with Adult Retention: An Empirical Study](https://mlsanity.com/paper/2610.08827/) (2026)

## Abstract (arXiv)

This paper describes the Arabic Multi-Genre Broadcast (MGB-2) Challenge for SLT-2016. Unlike last year's English MGB Challenge, which focused on recognition of diverse TV genres, this year, the challenge has an emphasis on handling the diversity in dialect in Arabic speech. Audio data comes from 19 distinct programmes from the Aljazeera Arabic TV channel between March 2005 and December 2015. Programmes are split into three groups: conversations, interviews, and reports. A total of 1,200 hours have been released with lightly supervised transcriptions for the acoustic modelling. For language modelling, we made available over 110M words crawled from Aljazeera Arabic website Aljazeera.net for a 10 year duration 2000-2011. Two lexicons have been provided, one phoneme based and one grapheme based. Finally, two tasks were proposed for this year's challenge: standard speech transcription, and word alignment. This paper describes the task data and evaluation process used in the MGB challenge, and summarises the results obtained.