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A multivariate speech activity detector based on the syllable rate

A multivariate speech activity detector based on the syllabl...

引用

SPIE Conference on advanced signal processing algorithms, architectures, and implementations VIII

作者： Smith, D Townsend, J Nelson, DJ US Dept Def Ft George G Meade MD 20755 USA

ISBN: (纸本)0819429163

Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is desirable to extract intervals of speech which are bounded by segments of other signal types (fax/modem, music, static, dial tones, etc.). In the past, algorithms which successfully discriminate between speech and one specific other signal type have been developed. Frequently, these algorithms fail when the specific non-speech signal is replaced by a different non-speech signal. Little work has been done on combining such discriminators in order to solve the general speech vs. non-speech discrimination problem. Typically, several signal specific discriminators are blindly combined with predictable negative results. Moreover, when a large number of discriminators are involved, dimension reduction is achieved using Principal Components, which optimally compresses signal variance into the fewest number of dimensions. Unfortunately, these new coordinates are not necessarily optimal for discrimination. In this paper we apply graphical tools to determine a set of discriminators which produce excellent speech vs. non-speech clustering, thereby eliminating the guesswork in selecting good feature vectors. This cluster structure provides a basis for a general multivariate speech vs. non-speech discriminator, which compares very favorably with the TALKATIVE speech extraction algorithm.

关键词： signal processing

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CONTRIBUTION OF THE POLARIZATION DIVERSITY IN HF DIRECTION FINDING SYSTEMS

CONTRIBUTION OF THE POLARIZATION DIVERSITY IN HF DIRECTION F...

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5th SPIE Conference on advanced signal processing - algorithms, architectures, and implementations

作者： ERHEL, Y EDJEOU, A BERTEL, L CTR RECH ECOLES COETQUIDAN F-56381 GUERFRANCE

ISBN: (纸本)0819416207

The aim of the paper is to estimate the contribution of the polarization diversity in high frequency (3 - 30 MHz) direction finding systems. We first describe the peculiarities of H.F. propagation and the resulting signal model involved in computer simulations. Next, we analyze the behavior of some particular direction finding systems using linear and circular geometries and polarization diversity. Some algorithms (non linear frequential analysis, M.U.S.I.C.) are tested in several conditions (narrowband or broadband signals, polarization filtering reiterated or no, sub-sampling). Theoretical and experimental results show that polarization diversity based upon the knowledge of the antenna complex responses improves greatly the efficiency of direction finding.

关键词： DIRECTION FINDING POLARIZATION ARRAY processing HIGH RESOLUTION algorithms HF PROPAGATION

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Optimal inversions of uncertain matrices - an estimation and control perspective

Optimal inversions of uncertain matrices - an estimation and...

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Conference on advanced signal processing algorithms architectures and implementations XIII

作者： Tao, KM SRI Int Menlo Pk CA 94025 USA

ISBN: (纸本)0819450782

Many system and signal related problems involve matrix inversion of some kind. For example, in estimation and signal recovery applications, inversion of the channel response matrix is often required in order to estimate the source signals. In the control of multivariable systems, inverting a process gain matrix may be called for in order to deliver appropriate control actions. There are situations where these matrices should be considered as uncertain (or random): for example, when the process/channel environments vary randomly, or when significant uncertainties are involved in estimating these matrices. Based on a unified approach, this paper considers both the right inversion (for control) and the left inversion (for estimation) of random matrices. In both cases, minimizing a statistical error function leads to the determination of optimal or linear optimal inversion. Connections with related techniques, such as the total least squares (TLS), the ridge regression, the Levenberg-Marquardt algorithm and the regularization theory are discussed. A variant Kalman filtering problem with randomly varying measurement gain matrix is among the applications addressed. Monte Carlo simulation results show substantial benefits by taking process/model uncertainty into consideration.

关键词： statistical inversion of uncertain matrices signal processing estimation control Kalman filtering with random measurement matrix channel equalization

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TIME-VARYING POLYSPECTRA AND REDUCED WIGNER-VILLE TRISPECTRUM

TIME-VARYING POLYSPECTRA AND REDUCED WIGNER-VILLE TRISPECTRU...

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CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： BOASHASH, B RISTIC, B Queensland Univ. of Technology (Australia)

ISBN: (纸本)081940943X

This paper consists of two parts. The first part reviews a class of higher-order Wigner-Ville distributions projected onto a single frequency axis. This class is referred to as polynomial Wigner-Ville distributions (PWVDs). For random processes, the expected value of PWVDs represent time-varying higher-order moment spectra. The second part defines and studies a particular member of a class of time-varying higher-order spectra based on PWVDs, namely a reduced Wigner-Ville trispectrum (RWVT). This novel time-frequency representation is shown to be a very efficient tool for analysis of FM signals affected by Gaussian amplitude modulation. In the paper, we present a statistical comparison of the RWVT and WVD based instantaneous frequency estimates for linear FM signals in absence and in presence of multiplicative noise. For multicomponent signals, the RWVT has to be re-defined and calculated in the full multi-lag domain.

关键词： Fermium Frequency modulation Interference (communication) signal to noise ratio Time-frequency analysis Modulation signal processing Statistical analysis Amplitude modulation signal analyzers

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An algorithm for weighted least squares positive time-frequency distributions

An algorithm for weighted least squares positive time-freque...

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Conference on advanced signal processing - algorithms, architectures, and implementations VII

作者： Pitton, JW MathSoft Seattle WA 98109 1700 Westlake Ave N United States

ISBN: (纸本)0819425842

An algorithm for computing positive time-frequency distributions (TFDs) for nonstationary signals is presented. This work extends the earlier work of the author and his colleagues in computing positive TFDs [11, 15]. A general approach to the problem of computing these signal-dependent distributions is derived. The method is based on an evolutionary spectrum formulation of positive TFDs. Following earlier work [15], a relationship is derived between positive TFDs and the ambiguity function of the observed signal. In particular, it is shown that the TFD is approximately equal to the two-dimensional Fourier transform of the ambiguity function. A method for computing the positive TFD is then presented based on minimizing the squared error in this approximation subject to the TFD being positive and satisfying the time and frequency marginals. The squared error may be weighted non-uniformly, resulting in a constrained weighted least-squares optimization problem. A solution to this optimization problem based on an alternating projections framework is presented, and an example is provided. The resulting TFD provides excellent time-frequency resolution while maintaining positivity and satisfying the marginals.

关键词： signal processing time-frequency analysis time-varying signals optimization alternating projections

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Application of time-frequency analysis methods to speaker verification

Application of time-frequency analysis methods to speaker ve...

引用

Conference on advanced signal processing algorithms, architectures, and implementations xvI

作者： Williams, W. J. Bossemeyer, R. W. Quantum Signal LLC Ann Arbor MI 48176 USA Univ Michigan EECS Ann Arbor MI 48109 USA Speech Technol Appl Res Inc St Charles IL USA

ISBN: (纸本)0819463922

Time-Frequency Analysis has previously been successfully applied to characterize and quantify a variety of acoustic signals, including marine mammal sounds. In this research, Time-Frequency analysis is applied to human speech signals in an effort to reveal signal structure salient to the biometric speaker verification challenge. Prior approaches to speaker verification have relied upon signal processing analysis such as linear prediction or weighted Cepstrum spectral representations of segments of speech and classification techniques based on stochastic pattern matching. The authors believe that the classification of identity of a speaker based on time-frequency representation of short time events occurring in speech could have substantial advantages. Using these ideas, a speaker verification algorithm was developed(1) and has been refined over the past several years. In this presentation, the authors describe the testing of the algorithm using a large speech database, the results obtained, and recommendations for further improvements.

关键词： time-frequency speaker verification multimodal biometrics homeland security pattern recognition

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APPLICATION OF CUMULANT TVHOS TO THE ANALYSIS OF COMPOSITE FM signalS IN MULTIPLICATIVE AND ADDITIVE NOISE 4

APPLICATION OF CUMULANT TVHOS TO THE ANALYSIS OF COMPOSITE F...

引用

4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： BOASHASH, B RISTICH, B Queensland Univ. of Technology (Australia)

ISBN: (纸本)0819412767

The paper addresses two questions of time-varying higher-order spectra (TVHOS), whose solutions are essential for the further development of these methods and their applicability to a wide range of situations. They are: (1) defining cumulant TVHOS and (2) predicting the behavior of TVHOS of composite signals. It is shown first that the cumulant Wigner-Ville trispectrum (as a particular member of cumulant TVHOS), can preserve the essential properties of cumulant higher-order spectra (e.g., eliminates Gaussian additive noise) and at the same time is able to characterize the time-variations of the signal's spectral (i.e., trispectral) content. Secondly, when dealing with composite FM signals, a special kind of `non-oscillating cross-terms' appear in the moment TVHOS time-frequency subspace. These cross-terms cannot be eliminated by smoothing the WVT, but rather by appropriate slicing of the full time-multi-frequency space.

关键词： Fermium Frequency modulation Composites Time-frequency analysis Interference (communication) signal processing Smoothing signal analyzers Chromium Nonlinear optics

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Segmented chirp features and hidden Gauss-Markov models for classification of wandering-tone signals

Segmented chirp features and hidden Gauss-Markov models for ...

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Conference on advanced signal processing algorithms, architectures and implementations XII

作者： Ainsleigh, PL USN Undersea Warfare Ctr Newport RI 02840 USA

ISBN: (纸本)0819445584

A new feature set and decision function are proposed for classifying transient wandering-tone signals. signals are partitioned in time and modeled as having piecewise-linear instantaneous frequency and piecewise-constant amplitude. The initial frequency, chirp rate, and amplitude are estimated in each segment. The resulting sequences of estimates are used as features for classification. The decision function employs a linear Gaussian dynamical model, or hidden Gauss-Markov model (HGMM). The parameters that characterize the HGMM for each class are estimated from labeled training sequences, and the trained models are used to evaluate the class-conditional likelihoods of an unlabeled signal. The signal is assigned to the-class whose model gives the maximum conditional likelihood. Simulation experiments demonstrate perfect classification performance in a three-class forced-choice problem.

关键词： Ferroelectric materials Bismuth Picosecond phenomena Information technology Weapons of mass destruction signal processing

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A novel signal detection technique based on generalized scale transforms - art. no. 63130Y

A novel signal detection technique based on generalized scal...

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Conference on advanced signal processing algorithms, architectures, and implementations xvI

作者： Nickel, Robert M. Penn State Univ Dept Elect Engn University Pk PA 16802 USA

ISBN: (纸本)0819463922

We are presenting an extension to the classic multiple signal classification method (MUSIC) developed by Schmidt and Bienvenu in 1979.(1) While the classic MUSIC algorithm is limited to the detection of constant frequency sinusoids in white noise, the proposed new method is capable of detecting signals with a continuously varying instantaneous frequency. The method is based on the development of a discrete-time version of the generalized scale transform (GST) which was introduced by Nickel and Williams in 1999.(2) As a byproduct we obtain techniques for discrete-time warp-shift invariant filtering which can be used in addition to the signal detection to separate signals with different instantaneous frequency contours.

关键词： warping functions sampling theory generalized scale transform signal detection multiple signal classification (MUSIC)

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Binary openings and closings in one pass using finite-state machines 6

Binary openings and closings in one pass using finite-state ...

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Conference on advanced signal processing algorithms, architectures, and implementations VI

作者： Waltz, FM Consultant (United States)

ISBN: (纸本)0819422347

In a series of ten papers published since 1994, a radically new technique for implementing a wide range of standard image processing operations has been presented, under the acronym SKIPSM (Separated-Kernel Image processing using finite State Machines). Key steps are: (1) the operation is separated into a row operation followed by a column operation, (2) these row and column operations are put in recursive form. That is, in a form compatible with either one-step software implementation or pipelined raster-scan hardware implementation, (3) the resulting operations are realized as FSMs (finite-state machines), and (4) these FSMs are implemented in software or in inexpensive off-the-shelf integrated circuits. Note that this technique does not require separability, in the usual sense. In this paper, the SKIPSM technique is applied to computing binary openings and closings in one pass using arbitrary binary structuring elements. Whether the resulting finite state machines are implemented in software or hardware, the result is generally much faster and/or much cheaper than conventional implementations. Furthermore, this same SKIPSM architecture is highly versatile and programmable, allowing it to be software-reconfigured to perform hundreds of other software- based or pipelined image processing operations, such a binary and grey-level morphology, the Grassfire Transform, binary and grey-level template matching, binary skeletonization, etc.

关键词： fast implementations image processing finite-state machines separability pipelining real-time inspection

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