This study introduces a novel approach to generate dance motions using onomatopoeia as input, with the aim of enhancing creativity and diversity in dance generation. Unlike text and music, onomatopoeia conveys rhythm and meaning through abstract word expressions without constraints on expression and without need for specialized knowledge. We adapt the AI Choreographer framework and employ the Sakamoto system, a feature extraction method for onomatopoeia focusing on phonemes and syllables. Additionally, we present a new dataset of 40 onomatopoeia-dance motion pairs collected through a user survey. Our results demonstrate that the proposed method enables more intuitive dance generation and can create dance motions using sound-symbolic words from a variety of languages, including those without onomatopoeia. This highlights the potential for diverse dance creation across different languages and cultures, accessible to a wider audience. Qualitative samples from our model can be found at: https://sites.google.com/view/onomatopoeia-dance/home/.

翻译：本研究提出了一种使用拟声词作为输入生成舞蹈动作的新方法，旨在增强舞蹈生成的创造性和多样性。与文本和音乐不同，拟声词通过抽象词语表达传递节奏和意义，不受表达限制且无需专业知识。我们改编了AI编舞框架，并采用了Sakamoto系统——一种聚焦于音素和音节的拟声词特征提取方法。此外，我们通过用户调查构建了一个包含40对拟声词-舞蹈动作配对的新数据集。实验结果表明，所提出的方法能够实现更直观的舞蹈生成，并可利用各种语言（包括无拟声词的语言）中的声象征词创作舞蹈动作。这凸显了跨语言、跨文化生成多样化舞蹈的潜力，使更多用户能够参与创作。本模型的定性样本可参见：https://sites.google.com/view/onomatopoeia-dance/home/。