The North S\'{a}mi (NS) language encapsulates four primary dialectal variants that are related but that also have differences in their phonology, morphology, and vocabulary. The unique geopolitical location of NS speakers means that in many cases they are bilingual in S\'{a}mi as well as in the dominant state language: Norwegian, Swedish, or Finnish. This enables us to study the NS variants both with respect to the spoken state language and their acoustic characteristics. In this paper, we investigate an extensive set of acoustic features, including MFCCs and prosodic features, as well as state-of-the-art self-supervised representations, namely, XLS-R, WavLM, and HuBERT, for the automatic detection of the four NS variants. In addition, we examine how the majority state language is reflected in the dialects. Our results show that NS dialects are influenced by the state language and that the four dialects are separable, reaching high classification accuracy, especially with the XLS-R model.

翻译：北萨米语（NS）包含四种主要方言变体，这些变体虽相互关联，但在音系、形态和词汇层面存在差异。北萨米语使用者独特的地缘政治位置，使得他们在多数情况下同时掌握萨米语与所在国主导语言（挪威语、瑞典语或芬兰语）的双语能力。这为我们从口述国家语言特征和声学特性两个维度研究北萨米语变体提供了可能。本文系统研究了包括MFCC、韵律特征在内的广泛声学特征，以及XLS-R、WavLM、HuBERT等先进自监督表征方法，用于四种北萨米语变体的自动识别。此外，我们探讨了主流国家语言如何影响这些方言。实验结果表明：北萨米语方言受国家语言影响显著，四种方言具有可分离性，其中基于XLS-R模型的方法达到了最高分类准确率。