Experiments in Cuneiform Language Identification
This paper presents methods to discriminate between languages and dialects written in Cuneiform script, one of the first writing systems in the world. We report the results obtained by the PZ team in the Cuneiform Language Identification (CLI) shared task organized within the scope of the VarDial Evaluation Campaign 2019. The task included two languages, Sumerian and Akkadian. The latter is divided into six dialects: Old Babylonian, Middle Babylonian peripheral, Standard Babylonian, Neo Babylonian, Late Babylonian, and Neo Assyrian. We approach the task using a meta-classifier trained on various SVM models and we show the effectiveness of the system for this task. Our submission achieved 0.738 F1 score in discriminating between the seven languages and dialects and it was ranked fourth in the competition among eight teams.
Code (0)
등록된 구현이 없습니다.
Tasks
Language IdentificationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Language and Dialect Identification of Cuneiform Texts
This article introduces a corpus of cuneiform texts from which the dataset for the use of the Cuneiform Language Identification (CLI) 2019 shared task was derived as well as some preliminary language identification exper…
Dialect IdentificationLanguage IdentificationInvestigating 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 p…
BIG-bench Machine LearningDialect IdentificationLanguage IdentificationTwistBytes - Identification of Cuneiform Languages and German Dialects at VarDial 2019
We describe our approaches for the German Dialect Identification (GDI) and the Cuneiform Language Identification (CLI) tasks at the VarDial Evaluation Campaign 2019. The goal was to identify dialects of Swiss German in G…
Dialect IdentificationLanguage IdentificationImproving Cuneiform Language Identification with BERT
We describe the systems developed by the National Research Council Canada for the Cuneiform Language Identification (CLI) shared task at the 2019 VarDial evaluation campaign. We compare a state-of-the-art baseline relyin…
Language IdentificationAutomatic Identification of Cuneiform Fragments Using String Alignment Algorithms
The literature from ancient Mesopotamia is still riddled with textual lacunas. Scores of fragments which could potentially fill those lacunas lie unidentified in museums's cabinets, but their identification has tradition…