Sawalha, M, Brierley, C and Atwell, E (2012) Predicting phrase breaks in classical and modern standard Arabic text. In: Chair, NCC, Choukri, K, Declerck, T, an, MUUD, Maegaard, B, Mariani, J, Odijk, J and Piperidis, S, (eds.) Proceedings of the EighthInternational Conference on Language Resources and Evaluation (LREC’12). Eighth International Conference on Language Resources and Evaluation (LREC’12), 21-27 May 2012, Istanbul, Turkey. European Language Resources Association (ELRA) , 3868 - 3872. ISBN 978-2-9517408-7-7
Abstract
We train and test two probabilistic taggers for Arabic phrase break prediction on a purpose-built, “gold standard”, boundary-annotated and PoS-tagged Qur‟an corpus of 77430 words and 8230 sentences. In a related LREC paper (Brierley et al., 2012), we cover dataset build. Here we report on comparative experiments with off-the-shelf N-gram and HMM taggers and coarse-grained feature sets for syntax and prosody, where the task is to predict boundary locations in an unseen test set stripped of boundary annotations by classifying words as breaks or non-breaks. The preponderance of non-breaks in the training data sets a challenging baseline success rate: 85.56%. However, we achieve significant gains in accuracy with the trigram tagger, and significant gains in performance recognition of minority class instances with both taggers via Balanced Classification Rate. This is initial work on a long-term research project to produce annotation schemes, language resources, algorithms, and applications for Classical and Modern Standard Arabic.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Keywords: | Phrase break prediction; N-gram and HMM taggers; boundary-annotated and PoS-tagged Qur‟an Corpus |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Dec 2014 16:45 |
Last Modified: | 19 Dec 2022 13:29 |
Published Version: | http://www.lrec-conf.org/proceedings/lrec2012/pdf/... |
Status: | Published |
Publisher: | European Language Resources Association (ELRA) |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:81700 |