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Abstract:

Physical modelling of musical instruments is one possible approach to digital sound synthesis techniques. By the term physical modelling, we refer to the simulation of sound production mechanism of a musical instrument, which is modelled with reference to the physics using wave-guides. One of the fundamental parameters of such a physical model is the pitch, and so pitch period estimation is one of the first tasks of any analysis of such a model. In this paper, an algorithm based on the Dyadic Wavelet Transform has been investigated for pitch detection of musical signals. The wavelet transform is simply the convolution of a signal f(t) with a dialated and translated version of a single function called the mother wavelet that has to satisfy certain requirements. There are a wide variety of possible wavelets, but not all are appropriate for pitch detection. The performance of both linear phase wavelets (Haar, Morlet, and the spline wavelet) and minimum phase wavelets (Daubechies ’ wavelets) have been investigated. The algorithm proposed here has proved to be simple, accurate, and robust to noise; it also has the potential of acceptable speed. A comparative study between this algorithm and the well-known autocorrelation function is also given. Finally, illustrative examples of different real guitar tones and other sound signals are given using the proposed algorithm. KEYWORDS Physical modeling – wavelet transform – pitch – autocorrelation function. 1.

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