Abstract
Music Recognition System has becoming popular these days. They are based on either audio or symbolic method, which compares the user's query with the existing music database. The investigation has shown that the audio-based method system is good for storing sound waves. However, the limitation is to illustrate the content of the music. The symbolic-based method system doing well in representing the content of the music, including recognize similar patterns, but limitation in creating the music, e.g., Electronic Music. We also carried some detailed tests based on the previous Neural Network systems, with Music Definition Language (MDL) and Music Manipulation Language (MML). Furthermore, we have tested our previous classification system with new melody query, to see how it can handle with external music pieces, which beyond the self-testing from a self-organising-map. The conclusion is that our system can classify variation type, including key variations, expansion and reduction, which is better than those existing Music Information Retrieval (MIR) systems.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call