Abstract the co-articulation is one of the main reasons that makes the speech recognition difficult. However, the traditional Hidden Markov Models(HMM) can not model the co-articulation, because they depend on the first-order assumption. In this paper, for modeling the co-articulation, we propose a more perfect HMM than traditional first order HMM on the basis of our previous works and they giv...

Mapping knowledge structures is a key task in Knowledge Discovery in Databases (KDD). In order to display the thematic organization of knowledge, we compare and evaluate two different cartography approaches: principal components analysis (PCA) and a multilayer perceptron (MLP) in "self-association" mode. This kind of MLP can be used to perform a PCA when the activation function is set to the id...

This paper describes a very efficient Parallel Phone Recognizers followed by Language Modeling (PPRLM) system in terms of both performance and processing speed. The system uses context-independent phone recognizers trained on MLP features concatenated with the conventional PLP and pitch features. MLP features have several interesting properties that make them suitable for speech processing, in ...

We describe the development of a speech recognition system for conversational telephone speech (CTS) that incorporates acoustic features estimated by multilayer perceptrons (MLP). The acoustic features are based on frame-level phone posterior probabilities, obtained by merging two different MLP estimators, one based on PLP-Tandem features, the other based on hidden activation TRAPs (HATs) featu...

the aim of this study was to evaluate the effects of mentha longofolia plant (mlp) and its essential oils (mle) on ruminal fermentation and protozoa population in goat. the mlp at six levels 0, 25, 35, 55, 75 and 100 mg/30 ml, and the essential oil at six levels 0, 1700,3000,6700,8300 and 10000 mg/l plus monensin (as positive control, 50 mg and dissolved in ethanol) added to rumen fluid respect...

| A methodology is described for evolving a Rough-fuzzy multi layer perceptron with modular concept using a genetic algorithm to obtain a structured network suitable for both classiication and rule extraction. The modular concept, based on \divide and conquer" strategy, provides accelerated training and a compact network suitable for generating a minimum number of rules with high certainty valu...

We apply multilayer perceptron (MLP) based hierarchical Tandem features to large vocabulary continuous speech recognition in Mandarin. Hierarchical Tandem features are estimated using a cascade of two MLP classifiers which are trained independently. The first classifier is trained on perceptual linear predictive coefficients with a 90 ms temporal context. The second classifier is trained using ...

We consider simple cube-curves in the orthogonal 3D grid. The union of all cells contained in such a curve (also called the tube of this curve) is a polyhedrally bounded set. The curve’s length is defined to be that of the minimum-length polygonal curve (MLP) fully contained and complete in the tube of the curve. So far no provable general algorithm is known for the approximative calculation of...

A pruning schema is applied to Multi-Layer Perceptron (MLP) gender classi£er. MLP uses eigenvector coef£cients of the face space created by Principal Component Analysis (PCA). We show that pruning improves the initial MLP performance by preserving the most effective input while eliminating most of the units and connections. Pruning is also used as a tool to monitor which eigenvectors contribute...