Pitch Estimation Enhancement Employing Neural Network-based Music Prediction

M. Szczerba and A. Czy┼╝ewski (Poland)



In this paper a new method for pitch estimation enhancement was presented. Pitch estimation methods are widely used for extracting musical data from digital signal. A brief review of these methods is included in the paper. However, since processed signal may contain noise and distortions, the estimation results can be erroneous. The proposed method was developed in order to override disadvantages of standard pitch estimation algorithms. The new -approach is based on both pitch estimation in terms of signal processing and pitch prediction based on musical knowledge modeling. First, signal is partitioned into segments roughly analogous to consecutive notes. Thereafter, for each segment an autocorrelation function is calculated. Autocorrelation function values are then altered using pitch predictor output. A music predictor based on artificial neural networks was introduced for this task. The description of the proposed pitch estimation enhancement method is included and some details concerning music prediction are discussed in the paper.

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