A model of music perceptual theory based on Markov chains
- Resource Type
- Conference
- Authors
- Wen, Ru; Chen, Kai; Zhang, Yilin; Huang, Wenmin; Tian, Jiyuan; Xu, Kuan; Wu, Jiang
- Source
- 2018 Chinese Control And Decision Conference (CCDC) Chinese Control And Decision Conference (CCDC), 2018. :1099-1105 Jun, 2018
- Subject
- General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Feature extraction
IP networks
Markov processes
Mathematical model
Music
Machine learning
Psychology
Music style analysis
Markov chain
Implication-Realization theory
clustering
machine learning
- Language
- ISSN
- 1948-9447
Music perceptions can be regarded as the expectancies for which the brain processes temporal statistics to predict future rhythms. The different patterns of the expectancy streams represent the different styles of music. In this paper, we present a model for music style recognition based on a music cognitive theory combined with machine learning approach. First, we establish a Markov chain with eight states where each state represents a certain composition mode derived from the Implication-Realization (IR) theory. Then we use a clustering method to detect music styles hidden in compositions. The results are identical to the conclusions in musicology, which confirms the effectiveness of our method.