Senegalese musician Salliou made his own kashaka, a type of twin ball rattle on a string. Listen to him show how many sounds his ingenious creation can make. Read the rest

"When you tap the tape, it sounds like a electro-magnetic drum." The open Open Reel Ensemble created this cool instrument by stringing several tapes and engaging in tape tapping. Read the rest

Covering Alex Van Halen's drumming on "Hot for Teacher" has become its own YouTube genre, but few have nailed it as well as 13-year-old Mia Morris. Read the rest

Jared Dines demonstrates several weird drum setups that not only sound good, but look pretty cool, too. Read the rest

Every year, intrepid Ph.D. students face off in a high-stakes competition for honor, glory, and the intermingling of science and art. The goal: Dance your Ph.D. thesis. I showed you the finalists last year. This year, Science magazine has posted all 53 entries online, before the finalists are chosen. I'll confess, I've not yet watched them all. So I can't say this is my favorite, but it is well-done and did immediately catch my attention.

"Human-Based Percussion and Self-Similarity Detection in Electroacoustic Music" is, basically, researcher J. Anderson Mills' attempt to teach a computer to hear percussion sounds the way a human does. In the video, Shiny Robot learns how to dance. You can read a full description of how the various parts of this dance tie into Mills' research at the video site:

The dissertation research began with a two-choice, forced-interval experiment in which 29 humans were asked to rate isolated sounds from most to least percussive. The sound characteristic of rise time was found to be the most correlated with percussion of the characteristics tested. The experiment is represented in the dance by the first two interactions between Alain and Shiny, during which Shiny expresses his inability to correctly choose the stronger percussion sound.

... The final stage of the dissertation research was to use the detection algorithm with real-world music to discover self-similarity in the percussion patterns. By using auto-correlation analysis, the detection algorithm can be used to time the repetition and near repetition in music percussion.