{"id":96,"date":"2013-12-26T19:57:10","date_gmt":"2013-12-26T19:57:10","guid":{"rendered":"https:\/\/mikewinters.io\/?p=96"},"modified":"2019-10-09T23:49:13","modified_gmt":"2019-10-09T23:49:13","slug":"sonification-of-music-information","status":"publish","type":"post","link":"https:\/\/mikewinters.io\/?p=96","title":{"rendered":"Beethoven at 10,000 Notes per Second"},"content":{"rendered":"\n

As a music technology researcher, I’m aware of the incredible amount of information available about music. The practice of Computational Music Analysis involves analyzing large databases of music to find patterns representing distinct styles, genres and composers. <\/p>\n\n\n\n

At the end of my master’s degree, I worked with developers at the ELVIS Project<\/a> to make a sonification interface<\/a> for rapidly scanning through databases of music by ear. Audio seemed like an intuitive choice to represent this data.<\/p>\n\n\n\n

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It was fun to find out that the difference between composers could be heard, even at 10,000 notes per second. <\/p>\n\n\n\n

Monteverdi’s Madrigals – 10,000 Notes\/Second<\/figcaption><\/figure>\n\n\n\n

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Bach’s Chorales – 10,000 Notes\/Second<\/figcaption><\/figure>\n\n\n\n

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Beethoven’s String Quartets – 10,000 Notes\/Second<\/figcaption><\/figure>\n\n\n\n

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You can find the app, the source code and more examples here<\/a><\/p>\n\n\n\n