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    <abstract>Orthographical standardization is a milestone in a language‘s documentation and the development of its resources. However, texts written in former orthographies remain relevant to the language‘s history and development and therefore must be converted to the standardized orthography. Ensuring a language has access to the orthographically standardized version of all of its recorded texts is important in the development of resources as it provides additional textual resources for training, supports contribution of authors using former writing systems, and provides information about the development of the language. This paper evaluates the performance of natural language processing methods, specifically Finite State Transducers and Long Short-term Memory networks, for the orthographical conversion of Bàsàá texts from the Protestant missionary orthography to the now-standard AGLC orthography, with the conclusion that LSTMs are somewhat more effective in the absence of explicit lexical information.</abstract>
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%0 Conference Proceedings
%T Comparing methods of orthographic conversion for Bàsàá, a language of Cameroon
%A O’neil, Alexandra
%A Swanson, Daniel
%A Pugh, Robert
%A Tyers, Francis
%A Ngue Um, Emmanuel
%Y Mabuya, Rooweither
%Y Mthobela, Don
%Y Setaka, Mmasibidi
%Y Van Zaanen, Menno
%S Proceedings of the Fourth workshop on Resources for African Indigenous Languages (RAIL 2023)
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F oneil-etal-2023-comparing
%X Orthographical standardization is a milestone in a language‘s documentation and the development of its resources. However, texts written in former orthographies remain relevant to the language‘s history and development and therefore must be converted to the standardized orthography. Ensuring a language has access to the orthographically standardized version of all of its recorded texts is important in the development of resources as it provides additional textual resources for training, supports contribution of authors using former writing systems, and provides information about the development of the language. This paper evaluates the performance of natural language processing methods, specifically Finite State Transducers and Long Short-term Memory networks, for the orthographical conversion of Bàsàá texts from the Protestant missionary orthography to the now-standard AGLC orthography, with the conclusion that LSTMs are somewhat more effective in the absence of explicit lexical information.
%R 10.18653/v1/2023.rail-1.11
%U https://aclanthology.org/2023.rail-1.11/
%U https://doi.org/10.18653/v1/2023.rail-1.11
%P 97-105

Markdown (Informal)

[Comparing methods of orthographic conversion for Bàsàá, a language of Cameroon](https://aclanthology.org/2023.rail-1.11/) (O’neil et al., RAIL 2023)

• Comparing methods of orthographic conversion for Bàsàá, a language of Cameroon (O’neil et al., RAIL 2023)

ACL

• Alexandra O’neil, Daniel Swanson, Robert Pugh, Francis Tyers, and Emmanuel Ngue Um. 2023. Comparing methods of orthographic conversion for Bàsàá, a language of Cameroon. In Proceedings of the Fourth workshop on Resources for African Indigenous Languages (RAIL 2023), pages 97–105, Dubrovnik, Croatia. Association for Computational Linguistics.