Automatic Classification between Wind and Bowstring Instrumental Music Using Support Vector Machine

摘要

The automatic musical instrument classification has many applications such as music information retrieval, music reconstruction and audio classification. In this paper, wind instrumental music and bowstring instrumental music are studied based on the database consisting of 2896 clips from 8 different classes of musical instruments (horn, clarinet, oboe, trumpet, cello, viola, violin, and doublebass). With audio features including spectral centroid, spectral spread, low energy frame ratio, Mel-Frequency Cepstral Coefficients, formant frequency interval, and fundamental frequency, classification using Support Vector Machine whose parameters are optimized by Particle Swarm Optimization searching algorithm, gives an accuracy of 92.22%, the accuracy is close to or better than the ones reported on the similar data sets and using other classifiers.