Language Identification for Austronesian Languages

• URL: http://arxiv.org/abs/2206.04327v1
• Date: Thu, 9 Jun 2022 08:08:18 GMT
• Title: Language Identification for Austronesian Languages
• Authors: Jonathan Dunn and Wikke Nijhof
• Abstract summary: This paper provides language identification models for low- and under-resourced languages in the Pacific region. We combine 29 Austronesian languages with 171 non-Austronesian languages to create an evaluation set. Further experiments adapt these language identification models for code-switching detection, achieving high accuracy across all 29 languages.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper provides language identification models for low- and under-resourced languages in the Pacific region with a focus on previously unavailable Austronesian languages. Accurate language identification is an important part of developing language resources. The approach taken in this paper combines 29 Austronesian languages with 171 non-Austronesian languages to create an evaluation set drawn from eight data sources. After evaluating six approaches to language identification, we find that a classifier based on skip-gram embeddings reaches a significantly higher performance than alternate methods. We then systematically increase the number of non-Austronesian languages in the model up to a total of 800 languages to evaluate whether an increased language inventory leads to less precise predictions for the Austronesian languages of interest. This evaluation finds that there is only a minimal impact on accuracy caused by increasing the inventory of non-Austronesian languages. Further experiments adapt these language identification models for code-switching detection, achieving high accuracy across all 29 languages.

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