학술논문

Artist detection in music with Minnowmatch
Document Type
Conference
Source
Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584) Neural networks for signal processing Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop. :559-568 2001
Subject
Computing and Processing
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Multiple signal classification
Music information retrieval
Neural networks
Support vector machines
Support vector machine classification
National electric code
Space technology
Engines
Copyright protection
Audio databases
Language
ISSN
1089-3555
Abstract
In this paper we demonstrate the artist detection component of Minnowmatch, a machine listening and music retrieval engine. Minnowmatch (Mima) automatically determines various meta-data and makes classifications concerning a piece of audio using neural networks and support vector machines. The technologies developed in Minnowmatch may be used to create audio information retrieval systems, copyright protection devices, and recommendation agents. This paper concentrates on the artist or source detection component of Mima, which we show to classify a one-in-n artist space correctly 91% over a small song-set and 70% over a larger song set. We show that scaling problems using only neural networks for classification can be addressed with a pre-classification step of multiple support vector machines.