Drum Stroke Computing: Multimodal Signal Processing for Drum Stroke Identification and Performance Metrics
Jordan Hochenbaum, and Ajay Kapur
Proceedings of the International Conference on New Interfaces for Musical Expression
- Year: 2012
- Location: Ann Arbor, Michigan
- Keywords: Multimodality, Drum stroke identification, surrogate sensors, surrogate data training, machine learning, music information retrieval, performance metrics
- DOI: 10.5281/zenodo.1178287 (Link to paper)
- PDF link
Abstract:
In this paper we present a multimodal system for analyzing drum performance. In the first example we perform automatic drum hand recognition utilizing a technique for automatic labeling of training data using direct sensors, and only indirect sensors (e.g. a microphone) for testing. Left/Right drum hand recognition is achieved with an average accuracy of 84.95% for two performers. Secondly we provide a study investigating multimodality dependent performance metrics analysis.
Citation:
Jordan Hochenbaum, and Ajay Kapur. 2012. Drum Stroke Computing: Multimodal Signal Processing for Drum Stroke Identification and Performance Metrics. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.1178287BibTeX Entry:
@inproceedings{Hochenbaum2012, abstract = {In this paper we present a multimodal system for analyzing drum performance. In the first example we perform automatic drum hand recognition utilizing a technique for automatic labeling of training data using direct sensors, and only indirect sensors (e.g. a microphone) for testing. Left/Right drum hand recognition is achieved with an average accuracy of 84.95% for two performers. Secondly we provide a study investigating multimodality dependent performance metrics analysis.}, address = {Ann Arbor, Michigan}, author = {Jordan Hochenbaum and Ajay Kapur}, booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression}, doi = {10.5281/zenodo.1178287}, issn = {2220-4806}, keywords = {Multimodality, Drum stroke identification, surrogate sensors, surrogate data training, machine learning, music information retrieval, performance metrics}, publisher = {University of Michigan}, title = {Drum Stroke Computing: Multimodal Signal Processing for Drum Stroke Identification and Performance Metrics}, url = {http://www.nime.org/proceedings/2012/nime2012_82.pdf}, year = {2012} }