Cepstrum

About: Cepstrum is a research topic. Over the lifetime, 3346 publications have been published within this topic receiving 55742 citations.

Measurements of vocal tract shapes using magnetic resonance imaging

Abstract: Magnetic resonance imaging is used to determine the vocal tract area functions of a speaker producing five steady vowel sounds. The data is used in an acoustic tube model, formed by concatenating short uniform sections, and the acoustic spectra of the computed output from the model are compared with those of natural speech. For all but one of the vowels good agreement (typically within 120 Hz) is obtained for the first three formant frequencies. To compensate for measurement errors, optimisation procedures are applied, aimed at adjusting the areas to minimise a chosen cost function. A cost function which combines a windowed cepstral error with a Euclidean distance penalty for the areas is effective in finding area functions that gave much closer spectral matches, but which still lie largely within the estimated errors of measurement. These adjusted functions provide suitable root shapes for use in articulatory speech synthesis.

Fundamental frequency identification method for detecting cord force of cable-stayed bridge

Abstract: The invention discloses an identification method of fundamental frequency for detection of the force of the cable of a stayed-cable bridge, which gets a first fundamental frequency by an autopower spectrum module, a second fundamental frequency by a cepstrum module, and then determines whether the quotient of the following two values is less than or equal to the set threshold: 1. the absolute value of the difference of the first fundamental frequency and the second fundamental frequency; 2. a half of the sum of the first fundamental frequency and the second fundamental frequency. In this way, whether the fundamental frequency of the pull cable is a half of the first fundamental frequency and the second fundamental frequency is determined. By adopting the method, the accuracy and the precision of the fundamental frequencies got are significantly improved. In addition, as the vibration acceleration response time interval signal got by an acceleration sensor passes through a signal conditioning module for filtration and smooth processing firstly, the environmental noise in the vibration acceleration response time interval signal is effectively suppressed; the antijamming capability of the stayed-cable bridge is improved so that the fundamental frequency is identified more clearly and accurately.

Short‐Time “Cepstrum” Pitch Detection

Abstract: A short‐time cepstrum analyzer for vocal‐pitch detection has been simulated on an IBM‐7094 digital computer (The cepstrum of a signal is defined as the square of the Fourier transform of the logarithm of the amplitude spectrum of the signal) Since temporal periodicities in a speech signal cause periodic ripples in the amplitude spectrum, Fourier transformation of the spectrum gives the “frequency” of the ripple, which is inversely proportional to the fundamental frequency of the speech Taking the logarithm of the amplitude spectrum makes the effects of the vocal tract (spectrum envelope) and the vocal source (spectrum fine structure) additive, thereby separating the low “frequencies” of the spectrum envelope from the usually higher frequencies of the spectrum fine structure Cepstrum pitch detection is insensitive to phase distortion, amplitude distortion, additive noise, and the absence of the fundamental speech frequency A general description of the technique and some recent results and examples are