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Maximum Likelihood Linear Transformations for HMMBased Speech Recognition
 Computer Speech and Language
, 1998
"... This paper examines the application of linear transformations for speaker and environmental adaptation in an HMMbased speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple bias ..."
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Cited by 538 (65 self)
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This paper examines the application of linear transformations for speaker and environmental adaptation in an HMMbased speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple
Linear Transforms
"... Very important class of functions: signal processing, scientific computing, … Mathematically: Change of basis = Multiplication by a fixed matrix T Equivalent definition: Summation form x= ..."
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Very important class of functions: signal processing, scientific computing, … Mathematically: Change of basis = Multiplication by a fixed matrix T Equivalent definition: Summation form x=
Lineartransform
"... techniques for processing shearwave anisotropy in fourcomponent seismic data ..."
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techniques for processing shearwave anisotropy in fourcomponent seismic data
An analysis of transformations
 Journal of the Royal Statistical Society. Series B (Methodological
, 1964
"... In the analysis of data it is often assumed that observations y,, y,,...,y, are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal, homoscedasti ..."
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Cited by 1029 (3 self)
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, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's. Inferences about the transformation and about the parameters of the linear model are made by computing the likelihood function and the relevant posterior distribution. The contributions of normality
Survey on Independent Component Analysis
 NEURAL COMPUTING SURVEYS
, 1999
"... A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation of the ..."
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Cited by 2241 (104 self)
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A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation
Linear Transformations on Codes
"... This paper studies and classifies linear transformations that connect Hamming distances of codes. These include irreducible linear transformations and their concatenations. Their e#ect on the Hamming weights of codewords is also studied. Both linear and nonlinear codes over fields are considered. W ..."
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This paper studies and classifies linear transformations that connect Hamming distances of codes. These include irreducible linear transformations and their concatenations. Their e#ect on the Hamming weights of codewords is also studied. Both linear and nonlinear codes over fields are considered
Representing Coastlines with Linear Transforms
"... Contents 1 Introduction 2 1.1 How to generate coastlines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Overview of the project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Linear transforms 5 2.1 Nomenclature . . . . . . . . . . . . . . . . . . . ..."
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Contents 1 Introduction 2 1.1 How to generate coastlines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Overview of the project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Linear transforms 5 2.1 Nomenclature
Lambertian Reflectance and Linear Subspaces
, 2000
"... We prove that the set of all reflectance functions (the mapping from surface normals to intensities) produced by Lambertian objects under distant, isotropic lighting lies close to a 9D linear subspace. This implies that, in general, the set of images of a convex Lambertian object obtained under a wi ..."
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Cited by 514 (20 self)
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We prove that the set of all reflectance functions (the mapping from surface normals to intensities) produced by Lambertian objects under distant, isotropic lighting lies close to a 9D linear subspace. This implies that, in general, the set of images of a convex Lambertian object obtained under a
Shiftable Multiscale Transforms
, 1992
"... Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal. Wavel ..."
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Cited by 557 (36 self)
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Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal
BDD Minimization by Linear Transformations
 IN ADVANCED COMPUTER SYSTEMS
, 1998
"... Binary Decision Diagrams (BDDs) are a powerful tool and are frequently used in many applications in VLSI CAD, like synthesis and verification. Unfortunately, BDDs are very sensitive to the variable ordering and their size often becomes infeasible. Recently, a new approach for BDD minimization bas ..."
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Cited by 11 (2 self)
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based on linear transformations, i.e. a special type of spectral techniques, has been proposed. In this paper we study this minimization method in more detail. While so far only experimental results are known, we prove for a family of Boolean functions that by linear transformations an exponential
Results 1  10
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