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Hidden Markov model speech recognition systems typically use Gaussian mixture models to estimate the distributions of decor-related acoustic feature vectors that correspond to individual sub-word units. By contrast, hybrid connectionist-HMM systems use discriminatively-trained neural networks to estimate the probability distribution among subword units(More)
Hidden Markov model speech recognition systems typically use Gaussian mixture models to estimate the distributions of decor-related acoustic feature vectors that correspond to individual sub-word units. By contrast, hybrid connectionist-HMM systems use discriminatively-trained neural networks to estimate the probability distribution among subword units(More)
We evaluate the performance of several feature sets on the AURORA task as defined by ETSI. We show that after a non-linear transformation, a number of features can be effectively used in a HMM-based recognition system. The non-linear transformation is computed using a neural network which is discriminatively trained on the phonetically labeled (forcibly(More)
The mutual information concept is used to study the distribution of speech information in frequency and in time. The main focus is on the information that is relevant for phonetic classiication. A large database of hand-labeled uent s p e e c h is used to (a) compute the mutual information (MI) between a phonetic classiication variable and one spectral(More)
Rather long temporal trajectory of critical band logarithmic power spectrum energy at a given frequency is used as an input feature vector in a MLP-based phoneme classiier, trained on a task-independent hand-labeled development data. Class-speciic log likelihood vectors from the individual sub-classiiers form input to a merging MLP classiier trained on the(More)
Patient care can be intense and stressful, especially in emergency care situations. Emergency care has two parts, field care by a paramedic and in-hospital care. Paramedics often consult with physicians before the patient reaches the hospital. To do this effectively, they must convey the patient's condition rapidly and effectively. Upon hospital arrival(More)
BACKGROUND Research indicates that a diet rich in whole grains may reduce the risk of prevalent chronic diseases, including cardiovascular disease, diabetes, and some cancers, and that risk for these diseases varies by ethnicity. The objective of the current study was to identify major dietary sources of grains and describe their contribution to B vitamins(More)