Logan Beth author Ellis Daniel P. W. author Columbia University. Electrical Engineering Berenzweig Adam author Columbia University. Electrical Engineering Columbia University. Electrical Engineering originator text Articles 2003 manuscript version English We describe and discuss our recent work developing a database, methodology and ground truth for the evaluation of automatic techniques for music similarity. Our database consists of acoustic and textual 'Web-mined' data covering 400 popular artists. Of note is our technique of sharing acoustic features rather than raw audio to avoid copyright problems. Our evaluation methodology allows any data source to be regarded as ground truth and can highlight which measure forms the best collective ground truth. We additionally describe an evaluation methodology that is useful for data collected from people in the form of a survey about music similarity. We have successfully used our database and techniques to evaluate a number of music similarity algorithms. Electrical engineering Artificial intelligence http://hdl.handle.net/10022/AC:P:13787 NNC NNC 2012-07-02 14:57:28 -0400 2012-07-02 15:22:38 -0400 7789 eng