Pitch Estimation Method in an Integrated Time and Frequency Domain by Applying Linear Interpolation
Kichul Kim, Sung‐Joo Park, Seok-Pil Lee, Moo-Young Kim
Abstract
Kichul Kim, Sung‐Joo Park, Seok-Pil Lee, Moo-Young Kim
Abstract
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. We utilize an integrated autocorrelation method in time and frequency domains. It can remove the errors of pitch doubling and having. 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. Using linear interpolation, we can decrease the required number of FFT coefficients by 8 times. Thus, compared to the conventional methods, computational complexity can be reduced by 9.5 times.
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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. We utilize an integrated autocorrelation method in time and frequency domains. It can remove the errors of pitch doubling and having. 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. Using linear interpolation, we can decrease the required number of FFT coefficients by 8 times. Thus, compared to the conventional methods, computational complexity can be reduced by 9.5 times.
Key concepts: Autocorrelation, Fast Fourier transform, Pitch detection algorithm, Frequency domain, Time domain, Interpolation (computer graphics), Algorithm, Mathematics