Saar-Voice: A Multi-Speaker Saarbrücken Dialect Speech Corpus

[论文] Saar-Voice: A Multi-Speaker Saarbrücken Dialect Speech Corpus

论文概要

研究领域: cs.CL 作者: Lena S. Oberkircher, Jesujoba O. Alabi, Dietrich Klakow, Jürgen Trouvain 发布时间: 2026-04-13 arXiv: 2604.11803

中文摘要

NLP和语音技术近年取得显著进步，但仍主要关注标准化语言变体。方言尽管具有文化意义和广泛使用，但在语言资源和计算模型中代表性不足，导致性能差异。本文介绍Saar-Voice，一个6小时的萨尔布吕肯德语方言语音语料库。数据集通过数字化书籍和本地材料收集文本，由9名说话人录制子集。该语料库为未来方言感知TTS研究奠定基础，特别是在低资源场景下的零样本和少样本模型适应。

原文摘要

Natural language processing (NLP) and speech technologies have made significant progress in recent years; however, they remain largely focused on standardized language varieties. Dialects, despite their cultural significance and widespread use, are underrepresented in linguistic resources and computational models, resulting in performance disparities.

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