GALE Phase 3 Arabic Broadcast News Transcripts Part 1

Full Official Name: GALE Phase 3 Arabic Broadcast News Transcripts Part 1
Submission date: Aug. 18, 2016, 4:32 p.m.

*Introduction* GALE Phase 3 Arabic Broadcast News Transcripts Part 1 was developed by the Linguistic Data Consortium (LDC) and contains transcriptions of approximately 132 hours of Arabic broadcast news speech collected in 2007 by the Linguistic Data Consortium (LDC), MediaNet, Tunis, Tunisia and MTC, Rabat, Morocco during Phase 3 of the DARPA GALE (Global Autonomous Language Exploitation) program. Corresponding audio data is released as GALE Phase 3 Arabic Broadcast News Speech Part 1 (LDC2016S07). The broadcast news recordings for transcription feature news broadcasts focusing principally on current events from the following sources: Abu Dhabi TV, a television station based in Abu Dhabi, Al Alam News Channel, based in Iran; Al Arabiya, a news television station based in Dubai; Al Iraqiyah, an Iraqi television station; Aljazeera , a regional broadcaster located in Doha, Qatar; Al Ordiniyah, a national broadcast station in Jordan; Dubai TV, a broadcast station in the United Arab Emirates; Kuwait TV, a national broadcast station in Kuwait; Lebanese Broadcasting Corporation, a Lebanese television station; Nile TV, a broadcast programmer based in Egypt, Saudi TV, a national television station based in Saudi Arabia; and Syria TV, the national television station in Syria. *Data* The transcript files are in plain-text, tab-delimited format (TDF) with UTF-8 encoding, and the transcribed data totals 741,689 tokens. The transcripts were created with the LDC tool, XTrans, which supports manual transcription and annotation of audio recordings. XTrans is available from the following link, https://www.ldc.upenn.edu/language-resources/tools/xtrans. The files in this corpus were transcribed by LDC staff and/or by transcription vendors under contract to LDC. Transcribers followed LDC's quick transcription guidelines (QTR) and quick rich transcription specification (QRTR) both of which are included in the documentation with this release. QTR transcription consists of quick (near-) verbatim, time-aligned transcripts plus speaker identification with minimal additional mark-up. It does not include sentence unit annotation. QRTR annotation adds structural information such as topic boundaries and manual sentence unit annotation to the core components of a quick transcript. Files with QTR as part of the filename were developed using QTR transcription. Files with QRTR in the filename indicate QRTR transcription. *Acknowledgement* This work was supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

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