Subject:New pitch estimatorFrom:Arturo Camacho <acamacho@xxxxxxxx>Date:Thu, 31 Jan 2008 02:58:11 -0500List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>Dear members of the list, I want to share with you a new pitch estimation algorithm that I have created as part of my PhD dissertation. The algorithm is similar to autocorrelation, in the sense that it performs an integral transform of the spectrum using a cosine as kernel (recall the Wiener-Khinchin Theorem). However, instead of using the square of the magnitude of spectrum, it uses its square root. Also, it introduces some modifications to the cosine kernel to avoid some of the problems of autocorrelation. First, it zeroes the first quarter of the first cycle of the cosine to avoid the maximum that autocorrelation has at zero lag. Second, it multiplies the kernel by an envelope that decays as 1/f to avoid the periodicity of the autocorrelation function for periodic signals. Third, it normalizes the kernel and uses a pitch-dependant window size to make the width of the main spectral lobes match the width of the positive cosine lobes. This last step is done to avoid the tendency that autocorrelation has to give higher values to periodic signals with high F0 than to periodic signals with low F0 (why?). It can be shown that the type of signals that maximizes the inner product between the spectrum and the kernel are periodic signals whose spectral envelope decay as 1/f (e.g., sawtooth waveforms). A substantial improvement on the algorithm is achieved by analyzing the spectrum only at its first and prime harmonics. This is performed by removing from the kernel the non-prime peaks (positive cosine lobes) and their neighboring valleys (negative cosine lobes). The algorithm was tested using three speech databases and one musical instrument database. It outperformed other well known algorithms like YIN, TEMPO, SHS, and several variations of autocorrelation that are found in programs like Praat, Speech Filing System, and Festival. The dissertation is available at http://www.cise.ufl.edu/~acamacho/publications/dissertation.pdf. A Matlab implementation of the algorithm is available in one of the appendices. Thanks, Arturo -- __________________________________________________ Arturo Camacho, PhD Computer and Information Science and Engineering University of Florida E-mail: acamacho@xxxxxxxx Web page: www.cise.ufl.edu/~acamacho __________________________________________________

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