跨文化音乐情感研究揭示情绪描述存在差异，需避免翻译偏差。
Are Expressions for Music Emotions the Same Across Cultures?
- 用开放标签法收集各国真实音乐情感词，构建本土化情绪词表。
- 高唤醒高正价情绪在跨文化中一致，其他情绪差异明显。
- 机器翻译常误译音乐特有情感，应采用本地化采集方法。
音乐引发深刻情感，但情感词汇的跨文化普适性仍存争议。现有研究常受限于西方音乐与语言的偏见，依赖人工筛选词表。为此，我们在巴西、美国和韩国开展九项在线实验，共招募672名参与者。首先，从三国流行音乐中选取均衡样本；其次，通过开放式标签流程收集情感词，构建文化专属词表；最后，基于这些自下而上的词表，参与者对每首歌的情感进行评分。该方法使我们能映射文化内与跨文化的感情相似性。结果显示，高唤醒、高正价情感在跨文化中具一致性，而其他情感则差异较大。值得注意的是，机器翻译往往无法准确传达音乐特定含义。研究强调，在情感研究中需采用领域敏感、开放式、自下而上的采集方式，以减少文化偏见。
原文摘要 · Abstract (English)
Music evokes profound emotions, yet the universality of emotional descriptors across languages remains debated. A key challenge in cross-cultural research on music emotion is biased stimulus selection and manual curation of taxonomies, predominantly relying on Western music and languages. To address this, we propose a balanced experimental design with nine online experiments in Brazil, the US, and South Korea, involving N=672 participants. First, we sample a balanced set of popular music from these countries. Using an open-ended tagging pipeline, we then gather emotion terms to create culture-specific taxonomies. Finally, using these bottom-up taxonomies, participants rate emotions of each song. This allows us to map emotional similarities within and across cultures. Results show consistency in high arousal, high valence emotions but greater variability in others. Notably, machine translations were often inadequate to capture music-specific meanings. These findings together highlight the need for a domain-sensitive, open-ended, bottom-up emotion elicitation approach to reduce cultural biases in emotion research.
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