Discriminative training for continuous speech recognition

Discriminative training techniques for Hidden-Markov Models were recently proposed and successfully applied for automatic speech recognition. In this paper a discussion of the Minimum Classification Error and the Maximum Mutual Information objective is presented. An extended reestimation formula is used for the HMM parameter update for both objective functions. The discriminative training methods were utilized in speaker independent phoneme recognition experiments and improved the phoneme recognition rates for both discriminative training techniques

A hybrid RBF-HMM system for continuous speech recognition

A hybrid system for continuous speech recognition, consisting of a neural network with Radial Basis Functions and Hidden Markov Models is described in this paper together with discriminant training techniques. Initially the neural net is trained to approximate a-posteriori probabilities of single HMM states. These probabilities are used by the Viterbi algorithm to calculate the total scores for the individual hybrid phoneme models. The final training of the hybrid system is based on the "Minimum Classification Error\u27; objective function, which approximates the misclassification rate of the hybrid classifier, and the "Generalized Probabilistic Descent\u27; algorithm. The hybrid system was used in continuous speech recognition experiments with phoneme units and shows about 63.8% phoneme recognition rate in a speaker-independent task

A new model-discriminant training algorithm for hybrid NN-HMM systems

This paper describes a hybrid system for continuous speech recognition consisting of a neural network (NN) and a hidden Markov model (HMM). The system is based on a multilayer perceptron, which approximates the a-posteriori probability of a sequence of states, derived from semi-continuous hidden Markov models. The classification is based on a total score for each hybrid model, attained from a Viterbi search on the state probabilities. Due to the unintended discrimination between the states in each model, a new training algorithm for the hybrid neural networks is presented. The utilized error function approximates the misclassification rate of the hybrid system. The discriminance between the correct and the incorrect models is optimized during the training by the "Generalized Probabilistic Descent Algorithm\u27;, resulting in a minimum classification error. No explicit target values for the neural net output nodes are used, as in the usual backpropagation algorithm with a quadratic error function. In basic experiments up to 56% recognition rate were achieved on a vowel classification task and up to 69 % on a consonant cluster classification task

Neural networks for nonlinear discriminant analysis in continuous speech recognition

In this paper neural networks for Nonlinear Discriminant Analysis in continuous speech recognition are presented. Multilayer Perceptrons are used to estimate a-posteriori probabilities for Hidden-Markov Model states, which are the optimal discriminant features for the separation of the HMM states. The a-posteriori probabilities are transformed by a principal component analysis to calculate the new features for semicontinuous HMMs, which are trained by the known Maximum-Likelihood training. The nonlinear discriminant transformation is used in speaker-independent phoneme recognition experiments and compared to the standard Linear Discriminant Analysis technique

Chemical interaction at the buried silicon/zinc oxide thin-film solar cell interface as revealed by hard x-ray photoelectron spectroscopy

Hard X-ray photoelectron spectroscopy (HAXPES) is used to identify chemical interactions (such as elemental redistribution) at the buried silicon /aluminum-doped zinc oxide thin-film solar cell interface. Expanding our study of the interfacial oxidation of silicon upon its solid-phase crystallization (SPC), in which we found zinc oxide to be the source of oxygen, in this investigation we address chemical interaction processes involving zinc and aluminum. In particular, we observe an increase of zinc- and aluminum-related HAXPES signals after SPC of the deposited amorphous silicon thin films. Quantitative analysis suggests an elemental redistribution in the proximity of the silicon/aluminum-doped zinc oxide interface – more pronounced for aluminum than for zinc – as explanation. Based on these insights the complex chemical interface structure is discussed

EMIL The energy materials in situ laboratory Berlin a novel characterization facility for photovoltaic and energy materials

A knowledge based approach towards developing a new generation of solar energy conversion devices requires a fast and direct feedback between sophisticated analytics and state of the art processing test facilities for all relevant material classes. A promising approach is the coupling of synchrotron based X ray characterization techniques, providing the unique possibility to map the electronic and chemical structure of thin layers and interface regions with relevant in system in situ sample preparation or in operando analysis capabilities in one dedicated laboratory. EMIL, the Energy Materials In situ Laboratory Berlin, is a unique facility at the BESSY II synchrotron light source. EMIL will be dedicated to the in system, in situ, and in operando X ray analysis of materials and devices for energy conversion and energy storage technologies including photovoltaic applications and photo electrochemical processes. EMIL comprises up to five experimental end stations, three of them can access X rays in an energy range of 80 eV 10 keV. For example, one key setup of EMIL combines a suite of advanced spectroscopic characterization tools with industry relevant deposition facilities in one integrated ultra high vacuum system. These deposition tools allow the growth of PV devices based on silicon, compound semiconductors, hybrid heterojunctions, and organo metal halide perovskites on up to 6 sized substrates. EMIL will serve as a research platform for national and international collaboration in the field of photovoltaic photocatalytic energy conversion and beyond. In this paper, we will provide an overview of the analytic and material capabilities at EMIL

Measurement of inclusive D*+- and associated dijet cross sections in photoproduction at HERA

Inclusive photoproduction of D*+- mesons has been measured for photon-proton centre-of-mass energies in the range 130 < W < 280 GeV and a photon virtuality Q^2 < 1 GeV^2. The data sample used corresponds to an integrated luminosity of 37 pb^-1. Total and differential cross sections as functions of the D* transverse momentum and pseudorapidity are presented in restricted kinematical regions and the data are compared with next-to-leading order (NLO) perturbative QCD calculations using the "massive charm" and "massless charm" schemes. The measured cross sections are generally above the NLO calculations, in particular in the forward (proton) direction. The large data sample also allows the study of dijet production associated with charm. A significant resolved as well as a direct photon component contribute to the cross section. Leading order QCD Monte Carlo calculations indicate that the resolved contribution arises from a significant charm component in the photon. A massive charm NLO parton level calculation yields lower cross sections compared to the measured results in a kinematic region where the resolved photon contribution is significant.Comment: 32 pages including 6 figure

Measurement of Jet Shapes in Photoproduction at HERA

The shape of jets produced in quasi-real photon-proton collisions at centre-of-mass energies in the range $134-277$ GeV has been measured using the hadronic energy flow. The measurement was done with the ZEUS detector at HERA. Jets are identified using a cone algorithm in the $\eta - \phi$ plane with a cone radius of one unit. Measured jet shapes both in inclusive jet and dijet production with transverse energies $E^{jet}_T>14$ GeV are presented. The jet shape broadens as the jet pseudorapidity ($\eta^{jet}$) increases and narrows as $E^{jet}_T$ increases. In dijet photoproduction, the jet shapes have been measured separately for samples dominated by resolved and by direct processes. Leading-logarithm parton-shower Monte Carlo calculations of resolved and direct processes describe well the measured jet shapes except for the inclusive production of jets with high $\eta^{jet}$ and low $E^{jet}_T$. The observed broadening of the jet shape as $\eta^{jet}$ increases is consistent with the predicted increase in the fraction of final state gluon jets.Comment: 29 pages including 9 figure

Measurement of event shapes in deep inelastic scattering at HERA

Inclusive event-shape variables have been measured in the current region of the Breit frame for neutral current deep inelastic ep scattering using an integrated luminosity of 45.0 pb^-1 collected with the ZEUS detector at HERA. The variables studied included thrust, jet broadening and invariant jet mass. The kinematic range covered was 10 < Q^2 < 20,480 GeV^2 and 6.10^-4 < x < 0.6, where Q^2 is the virtuality of the exchanged boson and x is the Bjorken variable. The Q dependence of the shape variables has been used in conjunction with NLO perturbative calculations and the Dokshitzer-Webber non-perturbative corrections (`power corrections') to investigate the validity of this approach.Comment: 7+25 pages, 6 figure

Plastisol Foaming Process. Decomposition of the Foaming Agent, Polymer Behavior in the Corresponding Temperature Range and Resulting Foam Properties

The decomposition of azodicarbonamide, used as foaming agent in PVC - plasticizer (1/1) plastisols was studied by DSC. Nineteen different plasticizers, all belonging to the ester family, two being polymeric (polyadipates), were compared. The temperature of maximum decomposition rate (in anisothermal regime at 5 K min-1 scanning rate), ranges between 434 and 452 K. The heat of decomposition ranges between 8.7 and 12.5 J g -1. Some trends of variation of these parameters appear significant and are discussed in terms of solvent (matrix) and viscosity effects on the decomposition reactions. The shear modulus at 1 Hz frequency was determined at the temperature of maximum rate of foaming agent decomposition, and differs significantly from a sample to another. The foam density was determined at ambient temperature and the volume fraction of bubbles was used as criterion to judge the efficiency of the foaming process. The results reveal the existence of an optimal shear modulus of the order of 2 kPa that corresponds roughly to plasticizer molar masses of the order of 450 ± 50 g mol-1. Heavier plasticizers, especially polymeric ones are too difficult to deform. Lighter plasticizers such as diethyl phthalate (DEP) deform too easily and presumably facilitate bubble collapse