This paper describes a computationally efficient method for estimating the predominant pitch in audio recordings. This method is intended for building a real-time system that can automatically detect the melody line from complex music signals i.e. music signals containing human voice accompanied with sounds from at least three musical instruments. Available pitch estimation methods are effective primarily when dealing with recordings of human voice that is either unaccompanied or accompanied with one or two musical instruments. These methods perform poorly when applied to pitch estimation in complex music signals due to their reliance on directly estimating the fundamental frequency (F0), a task that is affected by the overlapping presence in frequency of instrumental sounds of guitar, piano, etc. In our method we exploit the higher harmonic structure of the human voice to develop a low-complexity system for estimating predominant pitch. Experimental results show that this computationally efficient method provides an robust estimate of predominant pitch in real-world audio signals with 85% success rate.

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