Emovectors：评估爵士即兴演奏中的情感内容以进行创造力评估
Emovectors: assessing emotional content in jazz improvisations for creativity evaluation
AI总结：
本文提出了一种基于嵌入的方法，用于量化爵士即兴演奏中的情感内容，以评估创造力。
摘要：
音乐即兴演奏是研究的迷人课题，本质上是创造过程的现场展示。在爵士乐中，音乐家常常在预定义的和弦进行（lead sheets）上即兴演奏。我们如何评估爵士即兴演奏的创造力？我们能否用自动化指标来捕捉这种创造力，以适应当前基于LLM的生成系统？情感投入的展示与即兴演奏中的创造力密切相关。分析音乐音频，我们能否检测情感投入？本研究假设如果即兴演奏中包含更多情感丰富的内容，它更可能被识别为具有创造力。提出了一种基于嵌入的方法，用于捕捉即兴演奏中的情感内容，使用基于心理依据的音乐特征分类，这些特征与情感相关。生成的'emovectors'被用来测试上述假设，跨多个即兴演奏进行比较。以这种方式量化情感内容可以为新的创造力评估指标做出贡献，这些指标可以大规模应用。
英文摘要：
Music improvisation is fascinating to study, being essentially a live demonstration of a creative process. In jazz, musicians often improvise across predefined chord progressions (leadsheets). How do we assess the creativity of jazz improvisations? And can we capture this in automated metrics for creativity for current LLM-based generative systems? Demonstration of emotional involvement is closely linked with creativity in improvisation. Analysing musical audio, can we detect emotional involvement? This study hypothesises that if an improvisation contains more evidence of emotion-laden content, it is more likely to be recognised as creative. An embeddings-based method is proposed for capturing the emotional content in musical improvisations, using a psychologically-grounded classification of musical characteristics associated with emotions. Resulting 'emovectors' are analysed to test the above hypothesis, comparing across multiple improvisations. Capturing emotional content in this quantifiable way can contribute towards new metrics for creativity evaluation that can be applied at scale.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
