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Pitch Estimation Method using Linear Interpolation in Integrated Autocorrelation Domain

Sung‐Joo Park, Chai-Jong Song, Seok-Pil Lee, Kyeung-Hak Seo

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Abstract

To removing the errors of pitch doubling and having, an autocorrelation method is used in pitch estimation. Autocorrelation values in time and frequency domains, which have different characteristics, correspond to the pitch period and fundamental frequency, respectively. In this study, an integrated autocorrelation method is utilized in time and frequency domains. In the time and frequency domains, pitch period and fundamental frequency have reciprocal relation to each other. Especially, fundamental frequency estimation ends up as an error because of the resolution of FFT. To reduce these artifacts, interpolation methods are applied in the integrated autocorrelation domain, which decreases pitch errors. Moreover, only for the pitch candidates found in a time domain, the corresponding frequency-domain autocorrelation values are calculated with reduced computational complexity. Based on performance evaluation, we prove that the required number of FFT coefficients is decreased and the accuracy of pitch extraction is improved.

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What this paper is about

To removing the errors of pitch doubling and having, an autocorrelation method is used in pitch estimation. Autocorrelation values in time and frequency domains, which have different characteristics, correspond to the pitch period and fundamental frequency, respectively. In this study, an integrated autocorrelation method is utilized in time and frequency domains. In the time and frequency domains, pitch period and fundamental frequency have reciprocal relation to each other. Especially, fundamental frequency estimation ends up as an error because of the resolution of FFT. To reduce these artifacts, interpolation methods are applied in the integrated autocorrelation domain, which decreases pitch errors. Moreover, only for the pitch candidates found in a time domain, the corresponding frequency-domain autocorrelation values are calculated with reduced computational complexity. Based on performance evaluation, we prove that the required number of FFT coefficients is decreased and the accuracy of pitch extraction is improved.

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Available abstract

To removing the errors of pitch doubling and having, an autocorrelation method is used in pitch estimation. Autocorrelation values in time and frequency domains, which have different characteristics, correspond to the pitch period and fundamental frequency, respectively. In this study, an integrated autocorrelation method is utilized in time and frequency domains. In the time and frequency domains, pitch period and fundamental frequency have reciprocal relation to each other. Especially, fundamental frequency estimation ends up as an error because of the resolution of FFT. To reduce these artifacts, interpolation methods are applied in the integrated autocorrelation domain, which decreases pitch errors. Moreover, only for the pitch candidates found in a time domain, the corresponding frequency-domain autocorrelation values are calculated with reduced computational complexity. Based on performance evaluation, we prove that the required number of FFT coefficients is decreased and the accuracy of pitch extraction is improved.

Key concepts: Autocorrelation, Pitch detection algorithm, Fast Fourier transform, Frequency domain, Autocorrelation technique, Time domain, Mathematics, Interpolation (computer graphics)

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