Features Extraction for Music Notes Recognition using Hidden Markov Models

In recent years Hidden Markov Models (HMMs) have been successfully applied to human speech recognition. The present article proves that this technique is also valid to detect musical characteristics, for example: musical notes. However, any recognition system needs to get a suitable set of parameters, that is, a reduced set of magnitudes that represent the outstanding aspects to classify an entity. This paper shows how a suitable parameterisation and adequate HMMs topology make a robust recognition system of musical notes. At the same time, the way to extract parameters can be used in other recognition technologies applied to music.