Questions tagged [hidden-markov-models]

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Next-Word Prediction, Language Models, N-grams

I was looking into how a next-word prediction engine like swift key or XT9 can be implemented. Here's what I did. I read about n-grams here - and
superuser's user avatar
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What is the meaning of the output weights of a Conditional Random Field (CRF) model?

Problem When train my linear chain CRF with annotated observations, I feed it with a number of sequences containing observation values and a "ground-truth" label for each observation. I'm currently ...
s1lence's user avatar
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How can you use HMMs and ANNs for on-line handwriting recognition?

On-line handwriting recognition is the task of converting a series of $(x(t),y(t))$ coordinates to symbols and words. In contrast to off-line handwriting recognition, where you only have a bitmap of ...
Martin Thoma's user avatar
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Applying Baum-Welch to multiple observed sequences iteratively

When using the Baum-Welch algorithm to train a hidden markov model you normally repeat it on some observed sequence iteratively until your values converge. If you have multiple observed sequences, ...
felher's user avatar
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Baum-Welch Algorithm

I was reading the book by Jurafsky and this is written by the author on HMM Although in principle the forward-backward algorithm can do completely unsu- pervised learning of the A and B parameters, ...
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Performance of smooting vs viterbi algorithm with HMMs

To experiment, I implemented a discrete HMM; the transition matrix and emission model are randomly, uniformly generated. Then, a sequence of random states and emissions are produced by the HMM. Then I ...
Jack Grundy's user avatar
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Hidden Markov Model with empty states

I am using a Hidden Markov Model with Gaussian mixture emissions to cluster a sequential data (I am using hmmlearn in python 3). Initially, I used the log likelihood to find the number of clusters and ...
dduque's user avatar
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HMM Baum-Welch training and pruning

I am working on a HMM tagger that should be initialized with some small data and then supposedly improved with Baum-Welch algorithm on the data. However, the number of states is huge, almost $459^2$, ...
cubeception's user avatar
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Viterbi algorithm for object tracking

I want to solve a problem of object tracking along time. The problem is - I have a sequence of images, and I need to find and track the creation of the objects, than their movement, and than their ...
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In Viterbi's algorithm what is the difference between the observation space and the sequence of observations?

Wikipedia has an explanation for the viterbi algorithm, in particular it describes the following summary of the inputs: What is the difference between O and Y? Also I am trying to understand what the ...
Makogan's user avatar
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Is there any toolbox for Markov Random Field Structure Learning?

I need a toolbox or software that takes a dataset as input, detect independencies among its random variables and produces the relative Markov Random Field graphical structure from that. Can anyone ...
Masih Zaamari's user avatar
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Find consensus trajectory of how a genetic algorithm solves an optimization

I have implemented a genetic algorithm to find the evolutionary outcomes of a biological scenario. I simulate the evolution (i.e. optimization) of five traits in my model. I ran my code 100 times and ...
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multiple sequence alignment using HMM and simulated annealing

Can anyone help me with Multiple Sequence Alignment (MSA) using Hidden Markov Model (HMM) by giving an example or a reference except these 2 references: 1-Eddy, Sea.R., et al.Multiple alignment using ...
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Continuous Observation Densities in HMM

I've been reading about hidden Markov models and stumbled upon A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition by Lawrence R. Rabiner (Proc. IEEE, 77(2):257–...
Allen Huang's user avatar