Summary of the paper

Title From Speech to Trees: Applying Treebank Annotation to Arabic Broadcast News
Authors Mohamed Maamouri, Ann Bies, Seth Kulick, Wajdi Zaghouani, Dave Graff and Mike Ciul
Abstract The Arabic Treebank (ATB) Project at the Linguistic Data Consortium (LDC) has embarked on a large corpus of Broadcast News (BN) transcriptions, and this has led to a number of new challenges for the data processing and annotation procedures that were originally developed for Arabic newswire text (ATB1, ATB2 and ATB3). The corpus requirements currently posed by the DARPA GALE Program, including English translation of Arabic BN transcripts, word-level alignment of Arabic and English data, and creation of a corresponding English Treebank, place significant new constraints on ATB corpus creation, and require careful coordination among a wide assortment of concurrent activities and participants. Nonetheless, in spite of the new challenges posed by BN data, the ATB’s newly improved pipeline and revised annotation guidelines for newswire have proven to be robust enough that very few changes were necessary to account for the new genre of data. This paper presents the points where some adaptation has been necessary, and the overall pipeline as used in the production of BN ATB data.
Topics Corpus (creation, annotation, etc.), Parsing, Part of speech tagging
Full paper From Speech to Trees: Applying Treebank Annotation to Arabic Broadcast News
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Bibtex @InProceedings{MAAMOURI10.558,
  author = {Mohamed Maamouri and Ann Bies and Seth Kulick and Wajdi Zaghouani and Dave Graff and Mike Ciul},
  title = {From Speech to Trees: Applying Treebank Annotation to Arabic Broadcast News},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
 }
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