Word segmentation for Akkadian cuneiform

  • We present experiments on word segmentation for Akkadian cuneiform, an ancient writing system and a language used for about 3 millennia in the ancient Near East. To our best knowledge, this is the first study of this kind applied to either the Akkadian language or the cuneiform writing system. As a logosyllabic writing system, cuneiform structurally resembles Eastern Asian writing systems, so, we employ word segmentation algorithms originally developed for Chinese and Japanese. We describe results of rule-based algorithms, dictionary-based algorithms, statistical and machine learning approaches. Our results may indicate possible promising steps in cuneiform word segmentation that can create and improve natural language processing in this area.

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Metadaten
Author:Timo Homburg, Christian ChiarcosORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1041261
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/104126
URL:https://aclanthology.org/L16-1642
URL:http://www.lrec-conf.org/proceedings/lrec2016/index.html
ISBN:978-2-9517408-9-1OPAC
Parent Title (English):Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), May 23-28, 2016, Portorož, Slovenia
Publisher:European Language Resources Association
Place of publication:Paris
Editor:Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Type:Conference Proceeding
Language:English
Year of first Publication:2016
Publishing Institution:Universität Augsburg
Release Date:2023/05/16
First Page:4067
Last Page:4074
Institutes:Philologisch-Historische Fakultät
Philologisch-Historische Fakultät / Angewandte Computerlinguistik
Philologisch-Historische Fakultät / Angewandte Computerlinguistik / Lehrstuhl für Angewandte Computerlinguistik (ACoLi)
Dewey Decimal Classification:4 Sprache / 40 Sprache / 400 Sprache
Licence (German):CC-BY-NC 4.0: Creative Commons: Namensnennung - Nicht kommerziell (mit Print on Demand)

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