North Sámi Dialect Identification with Self-supervised Speech Models

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


The North Sámi (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 Sámi 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.
Original languageEnglish
Title of host publicationProceedings of the 24th INTERSPEECH Conference
Number of pages5
Place of PublicationBaixas
PublisherISCA - International Speech Communication Association
Publication dateAug 2023
Publication statusPublished - Aug 2023
MoE publication typeA4 Article in conference proceedings
EventINTERSPEECH - Convention Centre Dublin, Dublin, Ireland
Duration: 20 Aug 202324 Aug 2023
Conference number: 24

Publication series

PublisherISCA - International Speech Communication Association
ISSN (Electronic)2958-1796

Fields of Science

  • 213 Electronic, automation and communications engineering, electronics
  • 113 Computer and information sciences
  • 6121 Languages

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