In spontaneous speech, various speech style and speed changes can be observed, which are known to degrade speech recognition accuracy. In this paper, we describe an optimized multi-duration HMM (OMD). An OMD is a kind of multi-path HMM with at most two parallel paths. Each path is trained using speech samples with short or long phoneme duration. The thresholds to divide samples of phonemes are ...

In this paper, we propose a system for recognition handwritten characters Tifinagh, with the use of neural networks (the multi layer perceptron MLP), the hidden Markov model (HMM), the hybrid Model MLP/HMM and a feature extraction method based on mathematical morphology, this method is tested on the database of handwritten isolated characters Tifinagh size consistent (1800 images in learning an...

INTRODUCTION Different serum levels of the IgG/IgE for Paracoccidioides brasiliensis high mass molecular (hMM) fraction (~366 kDa) in the acute and chronic forms of the disease have been reported. Considering the nonexistence of hMM fraction investigation involving clinical isolates of P. brasiliensis, the present study aimed to investigate the presence of the hMM fraction (~366 kDa) in cell fr...

In this paper, a learning controller is constructed by using a discrete Hidden Markov Model (HMM). The HMM states are deened based on the external force/torque sensor information, and the HMM ob-versation symbols are deened by the velocity command information. In the learning phase of the HMM controller, the Baum-Welch method is used based on the training data obtained from some successful robo...

Giant enhancement of spin Hall effect of tunneling light (SHETL) is theoretically proposed in a frustrated total internal reflection (FTIR) structure with hyperbolic metamaterial (HMM). We calculate the transverse shift of right-circularly polarized light in a SiO2-air-HMM-air-SiO2 waveguide and analyze the physical mechanism of the enhanced SHETL. The HMM anisotropy can greatly increase the tr...

The main goal of this paper is to compare the performance which can be achieved by five different approaches analyzing their applications’ potentiality on real world paradigms. We compare the performance obtained with (1) Multi-network RBF/LVQ structure (2) Discrete Hidden Markov Models (HMM) (3) Hybrid HMM/MLP system using a Multi LayerPerceptron (MLP) to estimate the HMM emission probabilitie...

In this paper we look at real-time computing issues in large vocabulary speech recognition. We use the French broadcast audio transcription task from ETAPE 2011 for this evaluation. We compare word error rate (WER) versus overall computing time for hidden Markov models with Gaussian mixtures (GMM-HMM) and deep neural networks (DNN-HMM). We show that for a similar computing during recognition, t...

Heavy meromyosin (HMM) forms characteristic arrowhead complexes with actin filaments in situ. These complexes are readily visualized in sectioned muscle. Following HMM treatment similar complexes appear in sectioned fibroblasts, chondrogenic cells, nerve cells, and several types of epithelial cells. Thin filaments freshly isolated from chondrogenic cells also bind HMM and form arrowhead structu...

This paper discusses a hidden Markov model (HMM) based on multi-space probability distribution (MSD). The HMMs are widelyused statistical models to characterize the sequence of speech spectra and have successfully been applied to speech recognition systems. From these facts, it is considered that the HMM is useful for modeling pitch patterns of speech. However, we cannot apply the conventional ...