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EFFICIENT SOLUTION OF COVARIANCE EQUATIONS FOR linear PREDICTION

IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1977年第5期25卷 429-433页

作者： MORF, M DICKINSON, B KAILATH, T VIEIRA, A STANFORD UNIV INFORMAT SYST LABSTANFORDCA 94305 PRINCETON UNIV DEPT ELECT ENGN & COMP SCIPRINCETONNJ 08540

An algorithm for the solution of the linear equations for the "covariance method" of linear prediction is stated and proved. The algorithm requires only O(p 2 ) arithmetic operations, and in form resembles the Levinson algorithm for solution of the linear equations for the "correlation method" of linear prediction. The structural properties of the problem and its solution are emphasized in the analysis presented.

关键词： Equations Signal processing algorithms Covariance matrix Arithmetic Correlation Least squares methods linear predictive coding Prediction algorithms Books Information systems

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OPTIMUM BROAD-BAND STEPS FOR A SLIDING LOAD

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 1977年第4期26卷 292-295页

作者： MARTINI, C RIDELLA, S CNR CIRCUITI ELETTR LABI-16145 GENOAITALY UNIV GENOA DEPT ELECT ENGNI-16132 GENOAITALY

The broad-band (2-18 GHz) optimum steps of a commercial sliding load have been determined by simulation on a digital computer. The influence of the load, which is slided, is taken into account. The results have been tested through a sliding short and by measuring a very good fixed load. An equivalent directivity greater than 59 dB has been obtained.

关键词： Frequency Impedance Computational modeling Software algorithms Iterative algorithms Computer simulation Testing Calibration Connectors linear predictive coding

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STATISTICAL TESTS AND DISTANCE MEASURES FOR LPC COEFFICIENTS

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1977年第6期25卷 554-559页

作者： DESOUZA, P UNIV OTAGO SCH MED DEPT PREVENT & SOCIAL MED DUNEDIN NEW ZEALAND

This paper considers the problem of comparing two sets of (LPC) coefficients or, more generally, that of comparing two short segments of speech via LPC techniques. It is shown that Itakura's prediction-residual ratio is intuitively unsatisfactory and theoretically misleading as a distance measure. Two slower, but more accurate statistical means of comparison are suggested, and these are supported by evidence from a simulation study.

关键词： linear predictive coding Statistical analysis Speech analysis Acoustic testing Terminology Speech coding Speech recognition Computer science Autocorrelation

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On Reflection Coefficients and the Cholesky Decomposition

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IEEE Transactions on Acoustics, Speech, and Signal Processing 1977年第1期25卷 93-96页

作者： Gibson, Jerry D. Department of Electrical Engineering University of Nebraska Lincoln NE 68588 United States

The autocorrelation and covariance methods are the two most popular analysis techniques for linear predictive coding of speech. Recent work on the covariance method has utilized the Cholesky decomposition for solving the normal equations. A set of intermediate parameters in the Cholesky approach closely resembles the reflection coefficients in the autocorrelation method, and some workers have treated them as such since several computational and operational advantages thus accrue. The Cholesky decomposition is examined in this paper, and it is shown that when the covariance matrix is not Toeplitz, the intermediate parameters are not the reflection coefficients and do not behave like the reflection coefficients. It is also shown that when the covariance matrix is Toeplitz and the vector of dependent variables consists of autocorrelation terms, the intermediate parameters can be interpreted as reflection coefficients. Copyright © 1977 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： Reflection Autocorrelation Speech analysis Covariance matrix Filters Stability linear predictive coding Speech coding Equations Signal processing algorithms

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A subjective evaluation of pitch detection methods using LPC synthesized speech

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IEEE Transactions on Acoustics, Speech, and Signal Processing 1977年第3期25卷 221-229页

作者： C. McGonegal L. Rabiner A. Rosenberg Bell Laboratories Inc. Murray Hill NJ USA

A subjective evaluation of seven pitch detectors has been carried out using synthetic speech. The evaluation is intended to complement the objective performance evaluation of the same pitch detection algorithms in the investigation of Rabiner et al. [1]. In the earlier study, each of the seven algorithms was evaluated on the basis of its performance with respect to four different types of errors. The standard of comparison was a semiautomatically determined pitch contour of each utterance in the experimental corpus. In the present study, the quality of LPC (linear predictive coding) analyzed and synthesized speech was evaluated. The pitch contour used in the synthesis was obtained either from one of the seven pitch detectors or from the semiautomatic pitch analysis. Using a computer-controlled sort board, an experiment was run in which each of eight listeners was asked to rank the nine versions of each utterance (the natural version was included to provide a stable anchor point). Results are presented on the overall preference for each pitch detector. In addition, subject preference as a function of the pitch range of the speaker and the transmission environment used in the recording is discussed. The present results are compared to those obtained in the earlier objective performance study.

关键词： Speech synthesis linear predictive coding Speech analysis Detectors Acoustic signal detection Speech processing Speech coding Disk recording Detection algorithms Performance analysis

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A pitch extraction algorithm based on LPC inverse filtering and AMDF

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IEEE Transactions on Acoustics, Speech, and Signal Processing 1977年第6期25卷 565-572页

作者： Chong Un Shih-Chien Yang SRI International Inc. Menlo Park CA USA Korea Advanced Institute of Science and Technology Seoul South Korea Chung-Shan Institute of Sciences and Technology Lungtan Taiwan

We present an efficient algorithm for determining fundamental frequency and voiced/unvoiced (V/UV) decision of speech. The pitch extractor utilizes the cross-correlation average magnitude difference function (AMDF) waveform that is obtained from the linear prediction residual signal. The decision logic used in pitch extraction is simple and reliable. The periodicity and null depth of AMDF waveforms, together with the average residual energy and the past pitch information, are used in the decision logic for fundamental frequency and V/UV decision. Computer simulation of the algorithm yielded accurate results, even for difficult phonemes for pitch extraction.

关键词： Filtering algorithms linear predictive coding Data mining Vocoders Autocorrelation Logic Speech processing Signal processing algorithms Frequency Computer simulation

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A fixed point computation of partial correlation coefficients

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IEEE Transactions on Acoustics, Speech, and Signal Processing 1977年第3期25卷 257-259页

作者： J. Le Roux C. Gueguen Laboratoire de Theorie des Systemes Ecole Nationale Supérieure des TéIécommunications Paris France

This paper introduces a new computational algorithm for the partial correlation coefficients of a linear system given the covariance of its output when excited by a white input noise. Although derived from Levinson's well-known procedure, the proposed algorithm does not make use of the usual parameters in the linear prediction recursion. It may be implemented using fixed point arithmetics. Application to speech waves is emphasized.

关键词： Signal processing algorithms Digital filters Equations Hardware PROM Speech processing linear systems White noise linear predictive coding Autocorrelation

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An isolated word recognition system based on acoustic-phonetic analysis and statistical pattern recognition

An isolated word recognition system based on acoustic-phonet...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： W. Lin C. Chan Case Western Reserve University Cleveland OH USA

A polynomial discriminant function is used to establish the probability density function for voice/unvoice/silence parts of speech. Based on these densities, segmentation accuracy of 95% were obtained. Voice segments are further segmented into phonemic units using threshold functions based on energy and first formant changes (80% accuracy). Multi-dimensional probability density functions based on LPC, energy, and zero crossing serves as prototype for each phonemic unit. Prototypes are also establish for a set of phoneme-pairs. Bayes' rule is used to assign probabilities for each phoneme and phoneme-pair in the unknown speech. Word Recognition is achieved by finding the word with the highest score for its phonemic units.

关键词： Pattern recognition Pattern analysis Speech analysis Probability density function Finite impulse response filter Polynomials Prototypes Low pass filters Speech recognition linear predictive coding

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Speaker verification using composite reference

Speaker verification using composite reference

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M. Vidalon M. Shridhar M. Canas Institute Venezolano de Incestigaciones Cientificas Caracas Venezuela Department of Electrical Engineering University of Windsor Windsor ONT Canada Instituto Venezolano de Investigaciones Cientificas Caracas Venezuela

This paper examines the effectiveness of parametric representation of speech derived from the linear prediction model using the new concept of composite reference for speaker verification. In the proposed verification system the combined information of the identity of several speakers is given. That is, the existence of an overall reference contour is assumed which contains the information corresponding to the identities of several speakers in a given population. The verification task consists of authenticating an individual's claimed identity by an LPC analysis of his speech. A time warping procedure based strictly on correlation also has been incorporated. Automatic verification based on the predictor and parcor coefficients and using composite reference yielded a verification accuracy of about 96 percent.

关键词： Speech analysis predictive models Computer aided analysis linear predictive coding Information analysis Distance measurement Autocorrelation Feature extraction

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A fixed point computation of partial correlation coefficients in linear prediction

A fixed point computation of partial correlation coefficient...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： J. Le Roux C. Gueguen E.N.S.T. Paris Cedex France Laboratoire de Théorie des Systemes E. N. S. Paris France

This paper introduces a new method for the computation of the partial correlation coefficients from the autocorrelation sequence. Derived from Levinson's algorithm, it involves the calculation of the crosscorrelations between the inputs and the outputs of the successive models which are formed. Using these, a fixed-point implementation is found for real time speech analysis on a 16-bits microprocessor. The method also gives an approximation of the impulse response of the system, which may be useful for identification with moving average models.

关键词： Equations Speech analysis Speech synthesis Fixed-point arithmetic Signal processing Signal generators linear predictive coding Polynomials predictive models Stability

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