Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 214 for “"Hidden markov model"”.
-
Hidden Markov model based visual speech recognition
… processing are presented. Classifiers based on Hidden Markov Model (HMM) are first explored for modeling and identifying the basic visual speech elements. Considering that the temporal features of visual speech elements may be confusable and sensitive to their contexts, three novel training …
-
Face recognition using hidden Markov model supervectors
This project attempts to boost the results of face recognition algorithms already established to perform face recognition by augmenting the architecture and using HMM-based supervector classification. In this thesis, the work of Tang’s 2010 dissertation is used such that the HMM based classifier …
-
Graphical analysis of hidden Markov model experiments
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
-
Hidden Markov model analysis of subcellular particle trajectories
… the application of several variants of hidden Markov models (HMMs) to analyzing the trajectories of such particles. And we compare the performance of our proposed algorithms with traditional approaches that involve fitting a mean square displacement (MSD) curve calculated from the …
-
Hidden Markov Model with Binned Duration and Its Application
<p>Hidden Markov models (HMM) have been widely used in various applications such as speech processing and bioinformatics. However, the standard hidden Markov model requires state occupancy durations to be geometrically distributed, which can be inappropriate in some real-world applications where …
-
On improving the forecast accuracy of the hidden Markov model
The forecast accuracy of a hidden Markov model (HMM) may be low due first, to the measure of forecast accuracy being ignored in the parameterestimation method and, second, to overfitting caused by the large number of parameters that must be estimated. A general approach to forecasting is described …
-
Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification
Using a generalized-clique hidden Markov model (HMM) as the starting point for a eukaryotic gene finder, the objective here is to strengthen the signal information at the transitions between coding and non-coding (c/nc) regions. This is done by enlarging the primitive hidden states associated with …
-
A multilevel logistic hidden Markov model for learning under cognitive diagnosis
… Trajectories, we propose a multilevel logistic hidden Markov model for learning based on cognitive diagnosis models, where the probability that a learner acquires the target skill depends not only on the general difficulty of the skill and the learner's mastery of other skills in the curriculum, …
-
Hidden Markov Model inference copy number change in array-CGH data
Cancer development and progression typically features genomic instability frequently resulting in genomic changes involving DNA copy number gains or losses. Identifying the genomic location of these regional alterations provides important opportunities for the discovery of potential novel oncogenes …
-
Application of Hidden Markov Model in Finite Mixture Modeling of High-Dimensional Data
Finite mixture models (FMMs) are widely used in practice and are famous for modeling heterogeneous data in a convenient and effective way. Owing to their flexibility, finitemixtures have since been applied to a wide range of problems in diverse fields, includingimage analysis, medicine, …
-
Visualizing speech production with a hidden Markov model tracker to aid speech therapy and communication
… and coherent parts of speech tracked by a hidden Markov model. The goal of these visualizations is to help the user understand speech better by providing a system where users can see the words they speak and experience, develop and practice speech skills using the statistical speech model …
-
Adaptation of hybrid deep neural network-hidden Markov model speech recognition system using a sub-space approach
… with speakers in the training data. DNNs last hidden layer activations are found to be more useful in identifying phoneme classes of frames as compared with traditional raw Mel-frequency cepstral coefficients as features. Finally, speaker adaptation of ASR is presented by augmenting the speech …
-
Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting
… to forecast such a vital commodity. However, Hidden Markov Model, ARMA Model and Artificial Neural Network has many drawbacks in forecasting such as linear limitations of ARMA model which is in contrast to the financial time series which are often nonlinear, ANN is very weak in terms of …
-
Application of Hidden Markov Model to Auto Telematics Data and the Effect of Universal Demand Law Change on Corporate Risk Taking in the U.S. Property & Casualty Insurance Industry
… insurance industry, and the application of hidden Markov model to auto telematics data. The first chapter presents my study in the first theme and the rest two chapters present the other theme. In Chapter 1, "Does Shareholder Litigation Affect Corporate Risk-Taking? Evidence from the …
-
Bayesian nonparametric learning with semi-Markovian dynamics
… interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data. However, in many settings the HDP-HMM's strict Markovian constraints are …
-
Behaviour recognition and monitoring of the elderly using wearable wireless sensors. Dynamic behaviour modelling and nonlinear classification methods and implementation.
… of its elderly user. In this research, a Hidden Markov Model incorporating Fuzzy Logic-based sensor fusion is created for the behaviour detection within Verity, with a method of Fuzzy-Rule induction designed for the system's adaptation to a user during operation. A dimension reduction and …
-
Extracting fields from free-text
… named-entity extraction within free text. FEL models the content structure of the specified named-entities rather than relying on brittle, context-specific separator logic. Users specify the names of the fields they wish to extract, which determine the number of states for an underlying Hidden …
-
A medication extraction framework for electronic health records
… hand-built rules and constrained conditional models. We focus on two concept types (i.e., medications and medical conditions) and the pairwise administered-for relation between these two concepts. For medication extraction, we design a rule-based baseline medNERRgreedy med that identifies …
Page 1 of 11