BACKGROUND In pediatric echocardiography, pulse wave Doppler, and tissue Doppler imaging velocities are widely used to assess cardiac function. Current reference values and Z scores, allowing adjustment for growth are limited by inconsistent methodologies and small sample size. Using a standardized approach for parametric modeling and Z score quality assessment, we propose new pediatric referen...

the mel frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. in this paper to achieve a satisfactorily performance in automatic speech recognition (asr) applications we introduce a noise robust new set of mfcc vector estimated through following steps. first, spectral mean normalization is a pre-processing which applies to t...

Computational Paralinguistics has several unresolved issues, one of which is coping with large variability due to speakers, spoken content and corpora. In this paper, we address the variability compensation issue by proposing a novel method composed of i) Fisher vector encoding of low level descriptors extracted from the signal, ii) speaker z-normalization applied after speaker clustering iii) ...

This paper describes the system developed by the UTH-CCB team from the University of Texas Health Science Center at Houston (UTHealth), for the 2015 BioCreative V shared tasks of Track 3 on extraction of chemical disease relation (CDR). We participated in both tasks: Task A for “Disease Named Entity Recognition and Normalization (DNER)” and Task B for “Chemical-induced Diseases Relation Extract...

To develop a German computer assisted language learning (CALL) system for students whose mother’s tongues are syllableor mora-timed, a multi-stage feature normalization scheme which takes both word stress and sentence intonation patterns into consideration is proposed for German stressed/unstressed syllable classification. The main idea is to first apply Fujisaki model and band-pass filtering t...

In this thesis multivariate methods were used to evaluate pretreatment methods, such as normalization, as well as classification possibilities of data collected with Laser Induced Breakdown Spectroscopy (LIBS). The LIBS system that FOI is currently developing for the purpose of classifying biological airborne threats was used to collect data from ten different samples in a laboratory environmen...

The success of support vector machines (SVMs) for classification problems is often dependent on an appropriate normalization of the input feature space. This is particularly true in topic identification, where the relative contribution of the common but uninformative function words can overpower the contribution of the rare but informative content words in the SVM kernel function score if the f...

In this study, we investigated the effectiveness of augmented data for encoderdecoder-based neural normalization models. Attention based encoder-decoder models are greatly effective in generating many natural languages. In general, we have to prepare for a large amount of training data to train an encoderdecoder model. Unlike machine translation, there are few training data for textnormalizatio...

A multimodal biometric authentication system based on plastic surgery face image using text dependent speech signal is described in this paper. In addition, the system is designed to keep the rate as high as possible for the plastic surgery face image by using text dependent speech signal. Each module of the system, i.e. the face and speech, is developed separately and fusion is done at matchin...

A multimodal biometric authentication system based on plastic surgery face image using text dependent speech signal is described in this paper. In addition, the system is designed to keep the rate as high as possible for the plastic surgery face image by using text dependent speech signal. Each module of the system, i.e. the face and speech, is developed separately and fusion is done at matchin...