The MGB-2 Challenge: Arabic Multi-Device Broadcast Media Recognition

Ahmed Ali, Peter Bell, James Glass, Yacine Messaoui, Hamdy Mubarak, Steve Renals, Yifan Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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 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.
Original languageEnglish
Title of host publication2016 IEEE Workshop on Spoken Language Technology
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)978-1-5090-4903-5
Publication statusPublished - 9 Feb 2017
Event2016 IEEE Workshop on Spoken Language Technology - San Diego, United States
Duration: 13 Dec 201616 Dec 2016


Conference2016 IEEE Workshop on Spoken Language Technology
Abbreviated titleSLT 2016
Country/TerritoryUnited States
CitySan Diego
Internet address


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