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Automatic music transcription (extracting musical notes from a polyphonic audio stream) is a very complex task that continues waiting for solutions, due to the harmonic complexity of musical sounds. Traditional approaches try to extract the information directly from the audio stream, but by taking into account that a polyphonic audio stream is no more than a combination of several notes, music transcription can be considered as a search problem where the goal is to find the sequence of the notes that best models our audio signal. By taking advantage of the genetic algorithms to explore a large search space we present a new approach to the music transcription problem. The results obtained show the feasibility of the approach.