Modeling Orthographic Variation in Occitan's Dialects

• URL: http://arxiv.org/abs/2404.19315v1
• Date: Tue, 30 Apr 2024 07:33:51 GMT
• Title: Modeling Orthographic Variation in Occitan's Dialects
• Authors: Zachary William Hopton, Noëmi Aepli,
• Abstract summary: Large multilingual models minimize the need for spelling normalization during pre-processing. Our findings suggest that large multilingual models minimize the need for spelling normalization during pre-processing.
• Score: 3.038642416291856
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Effectively normalizing textual data poses a considerable challenge, especially for low-resource languages lacking standardized writing systems. In this study, we fine-tuned a multilingual model with data from several Occitan dialects and conducted a series of experiments to assess the model's representations of these dialects. For evaluation purposes, we compiled a parallel lexicon encompassing four Occitan dialects. Intrinsic evaluations of the model's embeddings revealed that surface similarity between the dialects strengthened representations. When the model was further fine-tuned for part-of-speech tagging and Universal Dependency parsing, its performance was robust to dialectical variation, even when trained solely on part-of-speech data from a single dialect. Our findings suggest that large multilingual models minimize the need for spelling normalization during pre-processing.

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