EAGER: Structural Analysis of Large Amounts of Music Information (SALAMI)

EAGER：大量音乐信息的结构分析（SALAMI）

• 批准号: 1042727
• 负责人: John Downie
• 金额: $ 9.97万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1042727&HistoricalAwards=false
• 关键词: EAGER; Structural; Analysis; Large; Amounts

This research project aims to make large amounts web-based music information accessible to researchers, scholars and students from a range of disciplines pursuing a variety of goals. The approach proposed here involves applying new, untested and exploratory computational approaches to extremely large corpora of digital music in combination with sets of proven algorithms and tools for effectively extracting features from recorded music. These developments together with successful efforts to create and deploy online massive online music corpora have created circumstances in which music analysis can be greatly expedited because of automation in critical areas. This project also intends to expand the corpus of scores available (Open Source) and create new tools for analyzing them.

该研究项目旨在为追求各种目标的研究人员，学者和学生提供大量基于网络的音乐信息。这里提出的方法涉及应用新的，未经测试的和探索性的计算方法，以极大的数字音乐语料库相结合的一套行之有效的算法和工具，有效地从录制的音乐提取功能。这些发展以及创建和部署在线大规模在线音乐语料库的成功努力创造了音乐分析可以大大加快的环境，因为关键领域的自动化。 该项目还打算扩大可用的分数语料库（开源），并创建新的工具来分析它们。