@inproceedings{gidey-etal-2024-morphological,
    title = "Morphological Synthesizer for {G}e{'}ez Language: Addressing Morphological Complexity and Resource Limitations",
    author = "Gidey, Gebrearegawi Gebremariam  and
      Teklehaymanot, Hailay Kidu  and
      Atsbha, Gebregewergs Mezgebe",
    editor = "Mabuya, Rooweither  and
      Matfunjwa, Muzi  and
      Setaka, Mmasibidi  and
      van Zaanen, Menno",
    booktitle = "Proceedings of the Fifth Workshop on Resources for African Indigenous Languages @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.rail-1.11",
    pages = "94--106",
    abstract = "Ge{'}ez is an ancient Semitic language renowned for its unique alphabet. It serves as the script for numerous lan- guages, including Tigrinya and Amharic, and played a pivotal role in Ethiopia{'}s cultural and religious development during the Aksumite kingdom era. Ge{'}ez remains significant as a liturgical language in Ethiopia and Eritrea, with much of the national identity documentation recorded in Ge{'}ez. These written materials are invaluable primary sources for studying Ethiopian and Eritrean philosophy, creativity, knowledge, and civilization. Ge{'}ez is a complex morphological structure with rich inflectional and derivational morphology, and no usable NLP has been developed and published until now due to the scarcity of annotated linguistic data, corpora, labeled datasets, and lexicons. Therefore, we proposed a rule-based Ge{'}ez morphological synthesis to generate surface words from root words according to the morphological structures of the language. Consequently, we proposed an automatic morphological synthesizer for Ge{'}ez using TLM. We used 1,102 sample verbs, representing all verb morphological structures, to test and evaluate the system. Finally, we get a performance of 97.4{\%}. This result outperforms the baseline model, suggesting that other scholars build a comprehensive system considering morphological variations of the language. Keywords: Ge{'}ez, NLP, morphology, morphological synthesizer, rule-based",
}

Ge{'}ez is an ancient Semitic language renowned for its unique alphabet. It serves as the script for numerous lan- guages, including Tigrinya and Amharic, and played a pivotal role in Ethiopia{'}s cultural and religious development during the Aksumite kingdom era. Ge{'}ez remains significant as a liturgical language in Ethiopia and Eritrea, with much of the national identity documentation recorded in Ge{'}ez. These written materials are invaluable primary sources for studying Ethiopian and Eritrean philosophy, creativity, knowledge, and civilization. Ge{'}ez is a complex morphological structure with rich inflectional and derivational morphology, and no usable NLP has been developed and published until now due to the scarcity of annotated linguistic data, corpora, labeled datasets, and lexicons. Therefore, we proposed a rule-based Ge{'}ez morphological synthesis to generate surface words from root words according to the morphological structures of the language. Consequently, we proposed an automatic morphological synthesizer for Ge{'}ez using TLM. We used 1,102 sample verbs, representing all verb morphological structures, to test and evaluate the system. Finally, we get a performance of 97.4{\%}. This result outperforms the baseline model, suggesting that other scholars build a comprehensive system considering morphological variations of the language. Keywords: Ge{'}ez, NLP, morphology, morphological synthesizer, rule-based
Gidey, Gebrearegawi Gebremariam Teklehaymanot, Hailay Kidu Atsbha, Gebregewergs Mezgebe
Morphological Synthesizer for Ge'ez Language: Addressing Morphological Complexity and Resource Limitations