Multimodal Musician Recognition

Jordan Hochenbaum, Ajay Kapur, and Matthew Wright

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract:

This research is an initial effort in showing how a multimodal approach can improve systems for gaining insight into a musician's practice and technique. Embedding a variety of sensors inside musical instruments and synchronously recording the sensors' data along with audio, we gather a database of gestural information from multiple performers, then use machine-learning techniques to recognize which musician is performing. Our multimodal approach (using both audio and sensor data) yields promising performer classification results, which we see as a first step in a larger effort to gain insight into musicians' practice and technique.

Citation:

Jordan Hochenbaum, Ajay Kapur, and Matthew Wright. 2010. Multimodal Musician Recognition. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.1177805

BibTeX Entry:

@inproceedings{Hochenbaum2010,
 abstract = {This research is an initial effort in showing how a multimodal approach can improve systems for gaining insight into a musician's practice and technique. Embedding a variety of sensors inside musical instruments and synchronously recording the sensors' data along with audio, we gather a database of gestural information from multiple performers, then use machine-learning techniques to recognize which musician is performing. Our multimodal approach (using both audio and sensor data) yields promising performer classification results, which we see as a first step in a larger effort to gain insight into musicians' practice and technique. },
 address = {Sydney, Australia},
 author = {Hochenbaum, Jordan and Kapur, Ajay and Wright, Matthew},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.1177805},
 issn = {2220-4806},
 keywords = {Performer Recognition, Multimodal, HCI, Machine Learning, Hyperinstrument, eSitar},
 pages = {233--237},
 title = {Multimodal Musician Recognition},
 url = {http://www.nime.org/proceedings/2010/nime2010_233.pdf},
 year = {2010}
}