{"ID":5554321,"CreatedAt":"2026-07-02T02:11:27.934456424Z","UpdatedAt":"2026-07-04T16:34:07.883886499Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.01161","arxiv_id":"2607.01161","title":"Disentangling Speaker and Language Effects in Cross-Lingual Speaker Verification for Iberian Languages","abstract":"Cross-lingual speaker verification (SV) systems typically exhibit performance degradation when enrollment and test utterances are spoken in different languages. However, standard evaluation protocols confound language mismatch with inter-speaker variability, as evaluation is generally performed with different speakers across languages. In this work, we introduce a bilingual same-speaker evaluation set for five Iberian languages, enabling analysis of cross-lingual SV under constant speaker identity. We apply this setup to a HuBERT-based SV system previously shown to exhibit strong language dependence, and analyze results using the Cross-Lingual Transfer Matrix (CLTM) to study pairwise cross-lingual transfer. Our results show that speaker-related variability accounts for part of the observed degradation, but language mismatch remains the main driver of cross-lingual performance loss. These findings provide a more precise characterization of language dependence in cross-lingual SV.","short_abstract":"Cross-lingual speaker verification (SV) systems typically exhibit performance degradation when enrollment and test utterances are spoken in different languages. However, standard evaluation protocols confound language mismatch with inter-speaker variability, as evaluation is generally performed with different speakers...","url_abs":"https://arxiv.org/abs/2607.01161","url_pdf":"https://arxiv.org/pdf/2607.01161v1","authors":"[\"Pol Buitrago\",\"Javier Hernando\"]","published":"2026-07-01T16:44:19Z","proceeding":"eess.AS","tasks":"[\"eess.AS\",\"cs.CL\"]","methods":"[\"Large Language Model\"]","has_code":false}