根据文本生成情绪匹配的音乐，让旋律随故事情感变化。
Story2MIDI: Emotionally Aligned Music Generation from Text
- 用Transformer模型将文本转为情绪一致的音乐序列
- 在小规模数据上实现多样化的音乐情感表达
- 适合内容创作与情感化音乐生成场景
本文提出Story2MIDI，一种基于Transformer的序列到序列模型，用于从给定文本生成情绪一致的音乐。为训练该模型，我们整合了文本情感分析和音乐情绪分类的现有数据集，构建了Story2MIDI数据集，包含文本片段与引发相同情绪的音乐配对。尽管数据集规模较小且计算资源有限，实验表明模型能有效学习音乐中的情绪特征，并在生成中融入这些特征，产出具有多样化情感响应的音乐样本。通过客观音乐指标和人类听觉评估，验证了模型对目标情绪线索的捕捉能力。
原文摘要 · Abstract (English)
In this paper, we introduce Story2MIDI, a sequence-to-sequence Transformer-based model for generating emotion-aligned music from a given piece of text. To develop this model, we construct the Story2MIDI dataset by merging existing datasets for sentiment analysis from text and emotion classification in music. The resulting dataset contains pairs of text blurbs and music pieces that evoke the same emotions in the reader or listener. Despite the small scale of our dataset and limited computational resources, our results indicate that our model effectively learns emotion-relevant features in music and incorporates them into its generation process, producing samples with diverse emotional responses. We evaluate the generated outputs using objective musical metrics and a human listening study, confirming the model's ability to capture intended emotional cues.
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