Disentangling Speaker and Language Effects in Cross-Lingual Speaker Verification for Iberian Languages
Score
54Why selected
Novel methodology with clear experimental results, but limited to five Iberian languages, requiring further validation for generalization.
AI commentary
「This study provides a more precise attribution of language dependence in cross-lingual speaker verification, aiding the design of more robust cross-lingual speaker recognition systems.」
Quick overview
Cross-lingual speaker verification (SV) systems typically degrade when enrollment and test utterances are in different languages, but standard protocols confound language mismatch with inter-speaker variability. This work introduces a bilingual same-speaker evaluation set for five Iberian languages, enabling analysis under constant speaker identity. Using a HuBERT-based SV system and the Cross-Lingual Transfer Matrix (CLTM), results show speaker variability accounts for part of the degradation, but language mismatch remains the primary driver. These findings provide a more precise characterization of language dependence in cross-lingual SV.
- Introduces a bilingual same-speaker evaluation set for five Iberian languages, isolating speaker from language effects.
- Employs a HuBERT-based SV system and the CLTM to quantify pairwise cross-lingual transfer.
- Finds language mismatch is the primary driver of cross-lingual performance loss, with speaker variability explaining only part of the degradation.
Full text
Electrical Engineering and Systems Science > Audio and Speech Processing
arXiv:2607.01161v1 (eess) [Submitted on 1 Jul 2026]Title:Disentangling Speaker and Language Effects in Cross-Lingual Speaker Verification for Iberian Languages
Authors:Pol Buitrago, Javier Hernando View a PDF of the paper titled Disentangling Speaker and Language Effects in Cross-Lingual Speaker Verification for Iberian Languages, by Pol Buitrago and Javier Hernando View PDF HTML (experimental)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.
| Comments: | 5 pages, 8 figures, Submitted to IberSPEECH 2026 |
| Subjects: | Audio and Speech Processing (eess.AS); Computation and Language (cs.CL) |
| Cite as: | arXiv:2607.01161 [eess.AS] |
| (or arXiv:2607.01161v1 [eess.AS] for this version) | |
| https://doi.org/10.48550/arXiv.2607.01161 Focus to learn more arXiv-issued DOI via DataCite |
Submission history
From: Pol Buitrago [view email][v1] Wed, 1 Jul 2026 16:44:19 UTC (1,026 KB)
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