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Designed Vocalizations Dataset: Sound-Designed Human and Animal Voices for Non-human Voice Conversion

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Do you know Seolhee Lee?You can claim authorship or link another user.Do you know Minsu Kang?You can claim authorship or link another user.Do you know Yangsun Lee?You can claim authorship or link another user.Do you know Woosun Min?You can claim authorship or link another user.Do you know Choonghyeon Lee?You can claim authorship or link another user.Do you know Namhyun Cho?You can claim authorship or link another user.

Abstract

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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Publication notes

Author note
Accepted at InterSpeech 2026