Showing papers on "Cepstrum published in 1969"

Speech analysis-synthesis system based on homomorphic filtering.

Abstract: A digital speech analysis‐synthesis system based on a recently proposed approach to the deconvolution of speech is presented. The analyzer is based on a computation of the cepstrum considered as the inverse Fourier transform of the log magnitude of the Fourier transform. The transmitted parameters represent pitch and voiced unvoiced information and the low‐time portion of the cepstrum representing an approximation to the cepstrum of the vocal‐tract impulse response. In the synthesis, the low‐time cepstral information is transformed to an impulse response function, which is then convolved with a train of impulses during voiced portions or a noise waveform during unvoiced portions to reconstruct the speech. Since no phase information is retained in the analysis, phase must be regenerated during synthesis. Either a zero‐phase or minimum‐phase characteristic can be obtained by simple weighting of the cepstrum before transformation.

Speech analyzer-synthesizer system employing improved formant extractor

Abstract: An important step in speech signal analysis is the identification of formant frequencies of voiced speech. Formant data is necessary in the synthesizer used, for example, in a resonance vocoder. To derive these data, i.e., to obtain an estimate of the pitch period of the signal and its spectral envelope, a cepstrum of a speech signal is used. The lowest three formants of a voiced speech signal are then estimated from a smoothed spectral envelope using constraints on formant frequency ranges and relative levels of spectral peaks at the formant frequencies. These constraints allow detection in cases where formants are too close together to be resolved from the initial spectral envelope.

Real time cepstrum analyzer

Abstract: The periodicity or aperiodicity of a signal is determined, in a signal analyzer, from the so-called ''''cepstrum'''' of the signal; that is, from the Fourier transform of the logarithm of the power spectrum of the signal. The short-time cepstrum is obtained by passing the signal through a first spectrum analyzer followed by a logarithmic amplifier and a second spectrum analyzer. The cepstrum signal is characterized by a peak at a time proportional to the fundamental period during periodic portions of the signal, and by the absence of a peak during aperiodic portions of the signal.

Restoration of degraded photographic images

Abstract: Photographs which are blurred, for example, by uniform motion of a camera relative to an image during exposure, are restored by identifying certain parameters of the blurring, e.g., direction and displacement, using the parameters to transform the distortion into an additive periodic component in the picture (blur), and by estimating (or identifying) and subtracting the periodic components from the picture. Two-dimensional spectral analysis, or the cepstrum technique, may be employed to identify the blur parameters, and a transversal filter arrangement, adjusted in accordance with parameter values is used to perform the estimation and subtraction.

Narrow-Band Sampled-Data Techniques for Detection via the Underwater Acoustic Communication Channel

Abstract: Utilization of the fast Fourier transform to detect and classify signals generated in the underwater acoustic channel is considered. A quadrature sampling technique is developed that permits efficient coefficient representation of narrow-band signals. A spatially distributed target composed of Gaussian scatterers is used to derive optimum detection and classification techniques. The optimum detector for spatially distributed targets is presented. In addition, cepstrum analysis is employed to extract significant classification clues such as target size and highlight structure. Typical experimental results of target echo, envelope, spectrum, and cepstrum are presented.

Narrow-Band Sampled-Data Techniques for Detection via the Underwater Acoustic Communication Channel

Abstract: Utilization of the fast Fourier transform to detect and classify signals generated in the underwater acoustic channel is considered. A quadrature sampling technique is developed that permits efficient coefficient representation of narrow-band signals. A spatially distributed target composed of Gaussian scatterers is used to derive optimum detection and classification techniques. The optimum detector for spatially distributed targets is presented. In addition, cepstrum analysis is employed to extract signikant classification clues such as target size and highlight structure. Typical experimental results of target echo, envelope, spectrum, and cepstrum are presented.