Our founder is a biologist, statistician, and programmer. His interests in birds, singing (he’s a tenor in the Choral Arts Society of Southeast Wisconsin) and languages (English, Spanish, Arabic, and German), led him to pursue a Ph.D. in the ecology and behavior of song learning in birds.

Just like humans, baby birds learn to sing. They must pass through a “babbling” phase, in which they produce an acoustically diverse range of sounds. Ultimately, birds settle upon “crystallized” sounds and phrases, just as human language learners do. Quantifying this process poses a very difficult challenge for sound-measuring algorithms. This is especially true when the research question is focused on how well individual birds learn. The algorithms must be general enough to capture the variation found in the babbling phase, and precise enough to evaluate variation within and among crystallized songs. Acoustic Landmarks enable both tasks simultaneously.