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Investigating Machine Learning Methods for Language and Dialect Identification of Cuneiform Texts
Identification of the languages written using cuneiform symbols is a
difficult task due to the lack of resources and the problem of tokenization.
The Cuneiform Language Identification task in VarDial 2019 addresses the
problem of identifying seven languages and dialects written in cuneiform;
Sumerian and six dialects of Akkadian language: Old Babylonian, Middle
Babylonian Peripheral, Standard Babylonian, Neo-Babylonian, Late Babylonian,
and Neo-Assyrian. This paper describes the approaches taken by SharifCL team to
this problem in VarDial 2019. The best result belongs to an ensemble of Support
Vector Machines and a naive Bayes classifier, both working on character-level
features, with macro-averaged F1-score of 72.10%