- About MET-lab
- Research projects
- K-12 education initiatives
In this body of work, we seek to model musical attributes from music audio signals. These attributes span instrumentation, rhythm, and sonority, as well as elements performer expression.
Genre provides one of the most convenient groupings of music, but it is often regarded as poorly defined and largely subjective. In this work we seek to answer whether musical genres be modeled objectively via a combination of musical attributes and if audio features mimic the behavior of these attributes. This work is done in collaboration with Pandora, and evaluation is performed using Pandora’s Music Genome Project® (MGP).
Musical meter and attributes of the rhythmic feel such as swing, syncopation, and danceability are crucial when defining musical style. In this work, we propose a number of tempo-invariant audio features for modeling meter and rhythmic feel. This work is done in collaboration with Pandora, and evaluation is performed using Pandora’s Music Genome Project® (MGP).
In this work, we present a system that seeks to classify different expressive articulation techniques independent of percussion instrument.
The presented work makes use of a newly recorded dataset that encompasses a vast array of percussion performance expressions on a standard four piece drum kit.