TY - GEN
T1 - SalsaAsst
T2 - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
AU - Dong, Yudi
AU - Liu, Jian
AU - Chen, Yingying
AU - Lee, Woo Y.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/14
Y1 - 2017/11/14
N2 - Dancing is always challenging especially for beginners who may lack sense of rhythm. Salsa, as a popular style of dancing, is even harder to learn due to its unique overlapped rhythmic patterns made by different Latin instruments (e.g., Clave sticks, Conga drums, Timbale drums) together. In order to dance in synchronization with the Salsa beats, the beginners always need prompts (e.g., beat counting voice) to remind them of the beat timing. The traditional way to generate the Salsa music with beat counting voice prompts requires professional dancers or musicians to count Salsa beats manually, which is only possible in dance studios. Additionally, the existing music beat tracking solutions cannot well capture the Salsa beats due to its intricacy of rhythms. In this work, we propose a mobile device enabled beat counting system, SalsaAsst, which can perform rhythm deciphering and fine-grained Salsa beat tracking to assist Salsa dancers with beat counting voice/vibration prompts. The proposed system can be used conveniently in many scenarios, which can not only help Salsa beginners make accelerated learning progress during practice at home but also significantly reduce professional dancers' errors during their live performance. The developed Salsa beat counting algorithm has the capability to track beats accurately in both real-time and offline manners. Our extensive tests using 40 Salsa songs under 8 evaluation metrics demonstrate that SalsaAsst can accurately track the beats of Salsa music and achieve much better performance comparing to existing beat tracking approaches.
AB - Dancing is always challenging especially for beginners who may lack sense of rhythm. Salsa, as a popular style of dancing, is even harder to learn due to its unique overlapped rhythmic patterns made by different Latin instruments (e.g., Clave sticks, Conga drums, Timbale drums) together. In order to dance in synchronization with the Salsa beats, the beginners always need prompts (e.g., beat counting voice) to remind them of the beat timing. The traditional way to generate the Salsa music with beat counting voice prompts requires professional dancers or musicians to count Salsa beats manually, which is only possible in dance studios. Additionally, the existing music beat tracking solutions cannot well capture the Salsa beats due to its intricacy of rhythms. In this work, we propose a mobile device enabled beat counting system, SalsaAsst, which can perform rhythm deciphering and fine-grained Salsa beat tracking to assist Salsa dancers with beat counting voice/vibration prompts. The proposed system can be used conveniently in many scenarios, which can not only help Salsa beginners make accelerated learning progress during practice at home but also significantly reduce professional dancers' errors during their live performance. The developed Salsa beat counting algorithm has the capability to track beats accurately in both real-time and offline manners. Our extensive tests using 40 Salsa songs under 8 evaluation metrics demonstrate that SalsaAsst can accurately track the beats of Salsa music and achieve much better performance comparing to existing beat tracking approaches.
UR - http://www.scopus.com/inward/record.url?scp=85040566697&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040566697&partnerID=8YFLogxK
U2 - 10.1109/MASS.2017.25
DO - 10.1109/MASS.2017.25
M3 - Conference contribution
AN - SCOPUS:85040566697
T3 - Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
SP - 81
EP - 89
BT - Proceedings - 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2017
Y2 - 22 October 2017 through 25 October 2017
ER -