---
title: "解开伊比利亚语言跨语言说话人验证中的说话人与语言效应"
source: "arXiv AI/CL/LG（论文）"
source_tier: "t2"
url: "https://arxiv.org/abs/2607.01161v1"
permalink: "https://feed.astralor.com/items/itm_32d82785f021abd869739dcd"
published: "2026-07-01T16:44:19.000Z"
score: 54
channel: "ai"
tags: ["HuBERT","伊比利亚语言","说话人验证","跨语言"]
---

# 解开伊比利亚语言跨语言说话人验证中的说话人与语言效应

## 速览

跨语言说话人验证系统在 Enrollment 和测试语音语言不同时性能下降。但标准评估协议混淆了语言不匹配与说话人间变异性，因为不同语言的说话人往往不同。本研究引入了一个双语同说话人评估集（涵盖五种伊比利亚语言），在恒定说话人身份下分析跨语言 SV。基于 HuBERT 系统，利用跨语言迁移矩阵（CLTM）分析配对迁移。结果表明，说话人相关变异性部分解释了性能下降，但语言不匹配仍是主要原因。这为跨语言 SV 的语言依赖性提供了更精确的表征。

## 关键点

- 提出双语同说话人评估集，覆盖五种伊比利亚语言，分离说话人与语言因素。
- 使用 HuBERT 模型和 CLTM 矩阵定量分析配对跨语言转移。
- 发现语言不匹配是跨语言性能损失的主要因素，说话人变异性仅解释部分下降。

## 全文

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.

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