Journal ArticleDOI
A parametrically controlled spectral analysis system for speech
Harvey F. Silverman,N. Dixon +1 more
TLDR
The parametrically controlled analyzer (PCA) is a large PL/I program which has been designed to perform spectral analysis of speech signals and features parametric selection of several analysis methods, including discrete Fourier transformation and linear predictive coding.Abstract:
The parametrically controlled analyzer (PCA) is a large PL/I program which has been designed to perform spectral analysis of speech signals. PCA features parametric selection of several analysis methods, including discrete Fourier transformation and linear predictive coding. Also, selection may be made among various smoothing, normalization, and interpolation methods. PCA develops high-quality spectrographic representations of speech for standard line printers and CRT displays. The PCA is described and numerous examples of various parameter settings are presented and discussed.read more
Citations
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Journal ArticleDOI
Continuous speech recognition by statistical methods
TL;DR: Experimental results are presented that indicate the power of the methods and concern modeling of a speaker and of an acoustic processor, extraction of the models' statistical parameters and hypothesis search procedures and likelihood computations of linguistic decoding.
Journal ArticleDOI
Signal modeling techniques in speech recognition
TL;DR: A tutorial on signal processing in state-of-the-art speech recognition systems is presented, reviewing those techniques most commonly used, and three important trends that have developed in the last five years in speech recognition are examined.
Journal ArticleDOI
Speech recognition by machine: A review
TL;DR: This paper provides a review of recent developments in speech recognition research and the concept of sources of knowledge is introduced and the use of knowledge to generate and verify hypotheses is discussed.
Journal ArticleDOI
An algorithm for determining the endpoints of isolated utterances
Lawrence R. Rabiner,M. Sambur +1 more
TL;DR: The algorithm proposed for locating the endpoints of an utterance is based on two measures of the signal, zero crossing rate and energy, and is inherently capable of performing correctly in any reasonable acoustic environment in which the signal-to-noise ratio is on the order of 30 dB or better.
Journal ArticleDOI
Speech coding: a tutorial review
TL;DR: The objective of this paper is to provide a tutorial overview of speech coding methodologies with emphasis on those algorithms that are part of the recent low-rate standards for cellular communications.
References
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B. S. Atal,Suzanne L. Hanauer +1 more
TL;DR: Application of this method for efficient transmission and storage of speech signals as well as procedures for determining other speechcharacteristics, such as formant frequencies and bandwidths, the spectral envelope, and the autocorrelation function, are discussed.
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Cepstrum Pitch Determination
TL;DR: Algorithms were developed heuristically for picking those peaks corresponding to voiced‐speech segments and the vocal pitch periods, which were then used to derive the excitation for a computer‐simulated channel vocoder.
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The chirp z-transform algorithm
TL;DR: A computational algorithm for numerically evaluating the z -transform of a sequence of N samples is discussed, based on the fact that the values of the z-transform on a circular or spiral contour can be expressed as a discrete convolution.
Journal ArticleDOI
An algorithm for computing the mixed radix fast Fourier transform
TL;DR: This paper presents an algorithm for computing the fast Fourier transform, based on a method proposed by Cooley and Tukey, and includes an efficient method for permuting the results in place.