Musical Instrument Recognition Using Their Distinctive Characteristics in Artificial Neural Networks
Sound
2017-05-16 v1 Machine Learning
Abstract
In this study an Artificial Neural Network was trained to classify musical instruments, using audio samples transformed to the frequency domain. Different features of the sound, in both time and frequency domain, were analyzed and compared in relation to how much information that could be derived from that limited data. The study concluded that in comparison with the base experiment, that had an accuracy of 93.5%, using the attack only resulted in 80.2% and the initial 100 Hz in 64.2%.
Keywords
Cite
@article{arxiv.1705.04971,
title = {Musical Instrument Recognition Using Their Distinctive Characteristics in Artificial Neural Networks},
author = {Babak Toghiani-Rizi and Marcus Windmark},
journal= {arXiv preprint arXiv:1705.04971},
year = {2017}
}
Comments
Results based on a study conducted during the course Machine Learning at Uppsala University