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International Journal of Speech Technology

Erschienen in:

11.06.2015

Comparative evaluation of tools for Arabic corpora search and analysis

verfasst von: Abdullah Alfaifi, Eric Atwell

Erschienen in: International Journal of Speech Technology | Ausgabe 2/2016

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Abstract

As the number of Arabic corpora is constantly increasing, there is an obvious and growing need for concordancing software for corpus search and analysis that supports as many features as possible of the Arabic language, and provides users with a greater number of functions. This paper evaluates six existing corpus search and analysis tools based on eight criteria which seem to be the most essential for searching and analysing Arabic corpora, such as displaying Arabic text in its right-to-left direction, normalising diacritics and Hamza, and providing an Arabic user interface. The results of the evaluation revealed that three tools: Khawas, Sketch Engine, and aConCorde, have met most of the evaluation criteria and achieved the highest benchmark scores. The paper concluded that developers’ conscious consideration of the linguistic features of Arabic when designing these three tools was the most significant factor behind their superiority.

Vorheriger Artikel A new Quranic Corpus rich in morphosyntactical information

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The ALC may be accessed here http://www.arabiclearnercorpus.com.

Khawas can be downloaded from http://www.sourceforge.net/projects/kacst-acptool.

aConCorde can be downloaded from http://www.andy-roberts.net/coding/aconcorde.

AntConc can be downloaded from http://www.antlab.sci.waseda.ac.jp/software.html.

WordSmith Tools can be downloaded from http://www.lexically.net/wordsmith.

The manual can be accessed here http://www.lexically.net/wordsmith/step_by_step_Arabic6/index.html.

Sketch Engine can be accessed from http://www.sketchengine.co.uk.

IntelliText Corpus Queries can be accessed from http://smlc09.leeds.ac.uk/itb/htdocs/Query.html.

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Titel: Comparative evaluation of tools for Arabic corpora search and analysis
verfasst von: Abdullah Alfaifi
Eric Atwell
Publikationsdatum: 11.06.2015
Verlag: Springer US
Erschienen in: International Journal of Speech Technology / Ausgabe 2/2016
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI: https://doi.org/10.1007/s10772-015-9285-5

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