Detection of a Specific Musical Instrument Note Playing in Polyphonic Mixtures by Extreme Learning Machine and Particle Swarm Optimization
Keywords:
Extreme learning machine, particle swarm optimization, musical signal processing; musical information retrievalAbstract
In this work, we present a system for detecting a
specific musical instrument note in polyphonic mixtures based on machine learning method. By using extreme learning machine as a classifier, we generate input features from magnitude data of FFT spectrum, which are processed by an adjustable dynamic level processor. We use the particle swarm optimization to tune the parameter values of this level processor to make the system have the optimal detection performance for
the specific instrument signal. Three musical instruments were used in the experiments. These were trumpet, flute and clarinet. We also compare the detection results between using ELM with linear and non-linear output functions for selected features.
Furthermore, we show that our system can be used as a musical instrument source tracking system by creating a trajectory of its fundamental frequency using the information from the outputs of the system and illustrating over the spectrogram
Downloads
Downloads
Published
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
