Recent research in music-gesture relationship has paid more attention on the sound variations and its corresponding gesture expressiveness. In this study we are interested by gestures performed by orchestral conductors, with a focus on the expressive gestures made by the non dominant hand. We make the assumption that these gestures convey some meaning shared by most of conductors, and that they implicitly correspond to sound effects which can be encoded in musical scores. Following this hypothesis, we defined a collection of gestures for musical direction. These gestures are designed to correspond to well known functional effect on sounds, and they can be modulated to vary this effect by simply modifying one of their structural component (hand movement or hand shape). This paper presents the design of the gesture and sound sets and the protocol that has led to the database construction. The relevant musical excerpts and the related expressive gestures have been first defined by one expert musician. The gestures were then recorded through motion capture by two non experts who performed them along with recorded music. This database will serve as a basis for training gesture recognition system for live sound control and modulation.
@InProceedings{CHEN18.1075, author = {Lei Chen and Sylvie Gibet and Camille Marteau}, title = "{CONDUCT: An Expressive Conducting Gesture Dataset for Sound Control}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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