Sistemas de classificação musical com redes neuronais

As a result of recent technological innovations, there has been a tremendous growth in the Electronic Music Distribution industry. In this way, tasks such us automatic music genre classification address new and exciting research challenges. Automatic music genre recognition involves issues like feature extraction and development of classifiers using the obtained features. In this study we aim to classify classical music in subgenres, through three independent classification problems. Therefore, we extract 40 features for each one of the musical segments and we use neural nets as classifiers. Afterwards, due to the quality of the obtained results, a prototype system for automatic music classification of entire songs (not only segments) was built. We use 10 extracts for each song, uniformly distributed throughout the song. Each song is classified according to the most representative genre in all extracts.