Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in order to model accurately the underlying dynamics of a physical system. Moreover, it is typically crucial to process data…
Acoustics, Speech and Signal Processing
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89,107 papers
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We are developing a dual panel breast-dedicated PET system using LSO scintillators coupled to position sensitive avalanche photodiodes (PSAPD). The charge output is amplified and read using NOVA RENA-3 ASICs. This paper shows that the coincidence…
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This paper gives an exposition of linear prediction in the analysis of discrete signals. The signal is modeled as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given…
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Conventional approaches to sampling signals or images follow Shannon's theorem: the sampling rate must be at least twice the maximum frequency present in the signal (Nyquist rate). In the field of data conversion, standard analog-to-digital…
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This tutorial provides an overview of the basic theory of hidden Markov models (HMMs) as originated by L.E. Baum and T. Petrie (1966) and gives practical details on methods of implementation of the theory along with a description of selected…
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A new method of measuring reverberation time is described. The method uses tone bursts (or filtered pistol shots) to excite the enclosure. A simple integral over the tone-burst response of the enclosure yields, in a single measurement, the ensemble…
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A novel measurement technique of the transfer function of weakly not-linear, approximately time-invariant systems is presented. The method is implemented with low-cost instrumentation; it is based on an exponentially-swept sine signal. It is…
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Matrix identities, relations and approximations. A desktop reference for quick overview of mathematics of matrices.
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Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene…
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Several parametric representations of the acoustic signal were compared with regard to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary included many phonetically similar monosyllabic words,…
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The classical filtering and prediction problem is re-examined using the Bode- Shannon representation of random processes and the state transition method of analysis of dynamic systems. New results are: (1) The formulation and methods of solution of…
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Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sensing literature have focused on characterizing the achievable…
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Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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This paper introduces and motivates the use of Gaussian mixture models (GMM) for robust text-independent speaker identification. The individual Gaussian components of a GMM are shown to represent some general speaker-dependent spectral shapes that…
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A tutorial on signal processing in state-of-the-art speech recognition systems is presented, reviewing those techniques most commonly used. The four basic operations of signal modeling, i.e. spectral shaping, spectral analysis, parametric…
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In the absence of chemical-specific data, the threshold of toxicological concern (TTC) provides a method to determine a conservative estimate of a chronic oral exposure below which there is a very low probability of risk. The TTC approach was…
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In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive…
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The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist…
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An overview of beamforming from a signal-processing perspective is provided, with an emphasis on recent research. Data-independent, statistically optimum, adaptive, and partially adaptive beamforming are discussed. Basic notation, terminology, and…
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A novel method is proposed for realizing exact inverse filtering of acoustic impulse responses in room. This method is based on the principle called the multiple-input/output inverse theorem (MINT). The inverse is constructed from multiple…
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Ph.D. Student -
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Ph.D. StudentInstitute of Acoustics, Chinese Academy of Sciences -
Ph.D. StudentDepartment of Electrical and Computer Engineering, University of Patras -
Student (Master)Salford, United Kingdom