National Cancer Institute, USPHS. Presented in part at the 62nd Annual Meeting of the American Association for Cancer Research, Inc., Chicago. 111..April 1971 (37). 2Career Development Awardee of the National Cancer Institute (IK4-CA-8245-05). 3The abbreviations used are: HMM, hexamethylmelamine [2,4,6tris(dimethylamino)-i-lriazine] (NSC-13875); TEM, triethylenemelamine [2,4,6-tris(l-aziridinyl...

today, there arevarious statistical models for the discrete simulation of the rainfall occurrence/non-occurrence with more emphasizing on long-term climatic statistics. nevertheless, the accuracy of such models or predictions should be improved in short timescale. in the present paper, it is assumed that the rainfall occurrence/non-occurrence sequences follow a two-layer hidden markov model (hm...

In this paper, we describe an application of the Forward-Backwards (F-B) algorithm for maximum likelihood training of hybrid HMM/Bayesian Network (BN) acoustic models. Previously, HMM/BN parameter estimation was based on a Viterbi training algorithm that requires two passes over the training data: one for BN learning and one for updating HMM transition probabilities. In this work, we first anal...

The most popular model used in automatic speech recognition is the hidden Markov model (HMM). Though good performance has been obtained with such models there are well known limitations in its ability to model speech. A variety of modifications to the standard HMM topology have been proposed to handle these problems. One approach is the factorial HMM. This paper introduces a new form of factori...

In this paper, a study of topology of Hidden Markov Model (HMM) used in speech recognition is addressed. Our main contribution is the introduction of the notion of trajectory folding phenomenon of HMM. In complex phonetic contexts and in speaker-variability, this phenomenon degrades the discriminability of HMM. The goal of this paper is to give some explanation and experimental evidence suggest...

Localization as a technique to solve the complex and challenging problems besetting line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions has recently attracted considerable attention in the wireless sensor network field. This paper proposes a strategy for eliminating NLOS localization errors during calculation of the location of mobile terminals (MTs) in unfamiliar indoor environments...

Phosphorylation of smooth muscle heavy meromyosin (HMM) has been shown to result in about a 25-fold increase in the steady-state Vmax of the actin-activated MgATPase activity from 0.07 s-1 for unphosphorylated HMM to 1.9 s-1 for phosphorylated HMM. The steady-state MgATPase activity of unphosphorylated HMM in the absence of actin is 0.004 s-1. The true extent of regulation might be even larger ...

Relaxation of both smooth and skeletal muscles appears to be caused primarily by inhibition of the step associated with Pi release in the actomyosin ATPase cycle, rather than by a block in the binding of the myosin X ATP and myosin X ADP X Pi complexes to actin. In skeletal muscle, troponin-tropomyosin not only causes marked inhibition of Pi release, but it also markedly inhibits the binding of...

In this paper, we extend the Maximum Likelihood (ML) training algorithm to the Minimum Classiica-tion Error (MCE) training algorithm for discriminatively estimating the state-dependent polynomial coeecients in the stochastic trajectory model or the trended HMM originally proposed in 2]. The main motivation of this extension is the new model space for smoothness-constrained, state-bound speech t...

This paper examines F0 modeling and generation techniques for spontaneous speech synthesis. In the previous study, we proposed a prosodic-unit HMM where the synthesis unit is defined as a segment between two prosodic events represented by a ToBI label framework. To take the advantage of the prosodicunit HMM, continuous F0 sequences must be modeled from discontinuous F0 data including unvoiced r...