Wearable assistance for the ballroom-dance hobbyist - Holistic rhythm analysis and dance-style classification

Automated retrieval of high level information from ballroom dance music is challenging, but has many practical applications. These include, for example, a fully automatic ballroom dance D.J., robots capable of performing ballroom dances, or wearable danceassistance, as considered herein. It is necessary, for such a system, to retrieve information about the song's quarter note tempo, meter and beat positions. Further, the system must be able to discriminate between the nine Standard and Latin ballroom dances. In this paper we present a model that combines all these requirements in one holistic approach. The polyphonic input is processed by a simplified psychoacoustic model. Tatum, tempo and meter features are extracted using resonant filters. The filter output is used for beat tracking. The extracted features are used for a ballroom dance- style classification by Support-Vector-Machines. To show the high effectiveness regarding dance-style recognition and beat tracking, test-runs are carried out on a database containing 1.8k titles.