Musical Instrument Recognition using Mel-Frequency Cepstral Coefficients and Learning Vector Quantization
Irfan Maliki, Sofiyanudin · IOP Conference Series Materials Science and Engineering · 2018
Musical instrument recognition is an essential subtask in many application regarding in music information retrieval. This research aims at extending the previous research saying that the MFCC used to feature extraction and LVQ method used to classification has good accuracy for musical instrument recognition. To test the methods described have been implemented in an android based application. Looking at the presented results, this research then focuses on to implementation that method for recognition musical instrument based on Aerophone, Electrophone, Chordophone, Idiophone, and Membranophone. The test was performed used 750 dataset with 5 sound source classes, the result of the performance test show that methods has 94.80% accuracy. It can be concluded that MFCC and LVQ methods can be implemented to recognize musical instruments.