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InterBias-SV: Compound Conditions in Speaker Verification — arXiv:2609.36500

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.36500
License (as archived): CC0-1.0
Archived: 2026-10-07T16:25:56.644Z
SHA-256 of the archived text: 748f0523291056b55c4820bd42ae670b4b8c215414042506786aa692a4014701
Stable URL of this page: https://metraipolis.com/documento/dc_093f9569caeb

How to cite

InterBias-SV: Compound Conditions in Speaker Verification — arXiv:2609.36500 — arXiv (en), https://arxiv.org/abs/2609.36500 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_093f9569caeb (Metraipolis archive dc_093f9569caeb, sha256 748f0523291056b55c4820bd42ae670b4b8c215414042506786aa692a4014701)

BibTeX

@misc{dc093f9569caeb,
  title = {InterBias-SV: Compound Conditions in Speaker Verification — arXiv:2609.36500},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.36500},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_093f9569caeb; sha256 748f0523291056b55c4820bd42ae670b4b8c215414042506786aa692a4014701},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.36500. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Speaker verification systems encounter combinations of noise, channel distortion, and changes in speech. Evaluating each condition separately does not establish whether their effects add. InterBias-SV organises this question around a four-term comparison: joint error, two marginal errors, and a common reference. Its results artefact contains 4,068 scored records across 17 experiments, 12 encoder labels, and six speech corpora, totalling 12 million trial evaluations. Three experiment families contain the same-corpus terms needed to compute additive contrasts. For labels assigned to speaker-trained encoders, their mean contrasts are +0.0026, +0.0088, and +0.0024 in equal error rate (EER), with larger variation across settings. These descriptive averages do not establish equivalence to additivity: trial matching, checkpoint identity, and parts of the condition metadata remain unverified. We also examine two interpretation problems. Near-chance EER can make additive predictions difficult to interpret, but chance performance is not a hard EER ceiling, and correlation with the prediction does not identify a saturation mechanism. Ratios of demographic gaps are unstable when their clean reference is near zero; absolute gaps provide a more direct summary. The benchmark provides condition definitions, analysis scripts, and explicit requirements for interpretable compound-condition comparisons, while separating recomputable summaries from claims that require further experimental validation.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-30 in cs.AI).
Categorie arXiv: Sound (cs.SD) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2609.36500 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T15:54:53.848Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-09-30?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).