North Sámi Dialect Identification with Self-supervised Speech Models

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKonferensbidragVetenskapligPeer 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.
Titel på värdpublikationProceedings of the 24th INTERSPEECH Conference
Antal sidor5
FörlagISCA - International Speech Communication Association
Utgivningsdatumaug. 2023
StatusPublicerad - aug. 2023
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangINTERSPEECH - Convention Centre Dublin, Dublin, Irland
Varaktighet: 20 aug. 202324 aug. 2023
Konferensnummer: 24


FörlagISCA - International Speech Communication Association
ISSN (elektroniskt)2958-1796


  • 213 El-, automations- och telekommunikationsteknik, elektronik
  • 113 Data- och informationsvetenskap
  • 6121 Språkvetenskaper

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