SGER: A Music Search Engine Based on Aesthetic Similarity

SGER：基于审美相似度的音乐搜索引擎

• 批准号: 0736480
• 负责人: Bill Manaris
• 金额: --
• 依托单位: College of Charleston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0736480&HistoricalAwards=false
• 关键词: SGER; Music; Search; Engine; Based

AbstractIIS - 0736480Manaris, Bill Z.College of CharlestonA Music Search Engine based on Aesthetic SimilarityThis SGER project aims to develop a prototype music search engine based on identifying aesthetic similarities. This engine will utilize power-law metrics to extract statistical proportions of music-theoretic and other attributes of music pieces (e.g., Pitch, Duration, Pitch Distance, Duration Distance, Melodic Intervals, Harmonic Intervals, Melodic Bigrams, etc.).The engine searches for pieces that are aesthetically similar to the input piece using a mean squared error (MSE) approach. Preliminary testing has been done using the Classical Music Archives corpus (14,695 MIDI pieces), combined with 500+ MIDI pieces from other styles (e.g. Jazz, Rock, Country, etc.). Similar metrics have already been validated on aesthetic attributes of textual materials. Text results (author attribution, style identification, and pleasantness prediction) indicated an high level of accuracy. Assessment and validation experiments will be conducted to compare to computational findings indicating aesthetic similarity of retrieved pieces. These experiments will be conducted by Prof. Dwight Krehbiel (subaward, Bethel College), a specialist in cognitive neuroscience and psychology of music, who has extensive experience in measuring emotional and physiological responses to music.

基于美学相似性的音乐搜索引擎本SGER项目旨在开发一个基于识别美学相似性的音乐搜索引擎原型。该引擎将利用幂律度量来提取音乐作品的音乐理论和其他属性的统计比例（例如，音高、持续时间、音高距离、持续时间距离、旋律音程、和声音程、旋律双字母等）。引擎使用均方误差（MSE）方法搜索与输入片段在美学上相似的片段。初步测试已经完成，使用古典音乐档案语料库（14，695首），结合500多首来自其他风格（例如爵士，摇滚，乡村等）的作品。 类似的指标已经在文本材料的美学属性上得到了验证。 文本结果（作者归属，风格识别和愉悦度预测）表明了高水平的准确性。 评估和验证实验将进行比较，计算结果表明检索件的美学相似性。这些实验将由德怀特·克恩比尔教授（伯特利学院副教授）进行，他是认知神经科学和音乐心理学方面的专家，在测量对音乐的情感和生理反应方面拥有丰富的经验。