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 dance-assistance, 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.