Showing papers on "Cepstrum published in 1973"

Spectral analysis of speech by linear prediction

Abstract: The autocorrelation method of linear prediction is formulated in the time, autocorrelation, and spectral domains. The analysis is shown to be that of approximating the short-time signal power spectrum by an all-pole spectrum. The method is compared with other methods of spectral analysis such as analysis-by-synthesis and cepstral smoothing. It is shown that this method can be regarded as another method of analysis-by-synthesis where a number of poles is specified, with the advantages of noniterative computation and an error measure which leads to a better spectral envelope fit for an all-pole spectrum. Compared to spectral analysis by cepstral smoothing in conjunction with the chirp z transform (CZT), this method is expected to give a better spectral envelope fit (for an all-pole spectrum) and to be less sensitive to the effects of high pitch on the spectrum. The normalized minimum error is defined and its possible usefulness as a voicing detector is discussed.

Evaluation of various parameter sets in spoken digits recognition

Abstract: Various parameter sets-including a spectrum envelope, cepstrum, autocorrelation function, linear predictive coefficients, and partial autocorrelation coefficients (PAC's)- are evaluated experimentally to determine which constitutes the best parameter in spoken digit recognition. The principle of recognition is simple pattern matching in the parameter space with nonlinear adjustment of the time axis. The spectrum envelope and cepstrum attain the best recognition score of 100 percent for ten spoken digits of a single-male speaker. PAC's seem to be preferable because of their ease of extraction and theoretical orthogonalities; however, these PAC's tend to suffer from computation errors when computed by fixed-point arithmetic with a short accumulator length. We find two effective means to improve the errors; one is variable use of the PAC dimensions controlled by computation accuracy, and the other is smoothing along the time axis. With these improvements the PAC's offer almost 100 percent recognition.

Real-time pitch extraction by adaptive prediction of the speech waveform

Abstract: With the exception of relatively sophisticated methods such as cepstrum analysis, the problem of reliable pitch-period extraction has remained largely unsolved. This paper examines the feasibility of pitch-period extraction by means of the nonstationary error process resulting from adaptive-predictive quantization of speech. A real-time hard-ware system that may be realized at low cost is described.