构建首个专用于非人类语音转换的设计化声音数据集
Designed Vocalizations Dataset: Sound-Designed Human and Animal Voices for Non-human Voice Conversion
- 采集真人与动物声音，通过专业音效处理生成怪物吼叫等设计语音
- 提供标准化测试集，支持跨音色与音效风格的泛化能力评估
- 适合游戏、影视等需要创意语音生成的研究者与开发者
基于AI的语音转换技术已广泛应用于电影、有声书和游戏等领域。然而，现有研究和公开基准大多聚焦于自然人类语音，对怪物吼叫、机械音等设计化声音仍关注不足，部分原因在于缺乏公开可用资源。为此，我们推出了「设计化声音数据集」，通过收集多样化的原始声源（包括人声与动物叫声），并应用专业音效处理生成对应的效果变体。我们还构建了标准化测试集，明确划分可见/不可见音色组与音效风格，以在受控条件下评估泛化性能。最后，报告基线评测结果，支持可复现的评估与未来研究。数据集及演示样本已公开：https://ncai-official.github.io/speech/publications/designed-vocalizations-dataset/
原文摘要 · Abstract (English)
Advances in AI-based voice conversion have enabled a wide range of media applications, including films, audiobooks, and games. However, most research and public benchmarks still focus on natural human speech, leaving designed vocalizations, such as monster growls and robotic voices, underexplored, partly due to the lack of publicly available resources. To address this gap, we introduce the Designed Vocalizations Dataset, constructed by curating diverse raw vocal sources, including speech and animal vocalizations, and applying professional vocal effects processing to produce corresponding effect modified variants. We further provide a standardized test set with explicit seen/unseen splits over source timbre groups and preset styles to assess generalization under controlled conditions. Finally, we report baseline benchmark results to support reproducible evaluation and future research. The dataset and demo samples are available at https://ncai-official.github.io/speech/publications/designed-vocalizations-dataset/.
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