In this paper we present an efficient system for independent speaker speech recognition based on neural network approach. The proposed architecture comprises two phases: a preprocessing phase which consists in segmental normalization and features extraction and a classification phase which uses neural networks based on nonparametric density estimation namely the general regression neural networ...

Supplementing log filter-bank energies with i-vectors is a popular method for adaptive training of deep neural network acoustic models. While offline i-vectors (the target utterance or other relevant adaptation material is available for i-vector extraction prior to decoding) have been well studied, there is little analysis of online i-vectors and their robustness in multi-user scenarios where s...

Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV ) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation ...

To precisely model the time dependency of features, segmental unit input HMM with a dimensionality reduction method has been widely used for speech recognition. Linear discriminant analysis (LDA) and heteroscedastic discriminant analysis (HDA) are popular approaches to reduce the dimensionality. We have proposed another dimensionality reduction method called power linear discriminant analysis (...

In this paper, the compensation of mismatch between clean training hidden Markov models (HMMs) and noisy test speech is addressed. The purpose is to approach the performance of Aurora2 multi-condition training but use only clean training material. The idea is to integrate three methods including (1) mean subtraction, variance normalization and ARMA filtering (MVA) post-processing for Mel-scaled...

We present a novel multi-level HMM in which an intermediate ‘articulatory’ representation is included between the state and surface-acoustic levels. A potential difficulty with such a model is that advantages gained by the introduction of an articulatory layer might be compromised by limitations due to an insufficiently rich articulatory representation, or by compromises made for mathematical o...

Sub-wavelength nanostructured systems with tunable electromagnetic properties, such as hyperbolic metamaterials (HMMs), provide a useful platform to tailor spontaneous emission processes. Here, we investigate system comprising Eu3+(NO3)3·6H2O nanocrystals on an HMM structure featuring hexagonal array of Ag nanowires in porous Al2O3 matrix. The HMM-coupled Eu3+ ions exhibit up 2.4 fold increase ...

conclusion ped software of dual-source ct combined with perfusion imaging can significantly improve the detection rate of peripheral pulmonary embolism. results ctpa images revealed 50 (7.81%) segmental and 56 (4.38%) sub-segmental pulmonary embolisms, while the ped images showed 68 (10.63%) segmental and 94 (7.34%) sub-segmental pulmonary embolisms. thus, the detection rate on ped images for p...