Hidden Markov Models are used for modelling systems that are assumed to be Markov processes with hidden (i.e. unobserved) states.

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How tho choose the number of components in a Bayesian Hidden markov model

I'm implementing a bayesian Hidden markov model. I now face the problem of how to choose the number of components. I have two problems: 1) which index is better to use? 2) suppose i decide to use the ...
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11 views

What should be done to deal with missing observations ( or outlier observation ) for Viterbi?

I want to use Viterbi algorithm, to decode an HMM sequence, but very few observations are missing in some of the steps or outliers. The hidden states in these steps are assumed to be the same as ...
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71 views

How do I train HMM's for classification?

So I understand that when you train HMM's for classification the standard approach is: Separate your data sets into the data sets for each class Train one HMM per class On the test set compare the ...
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31 views

Why are after training 5-state HMM only few entries of transition matrix left greater than zero?

I try to create the speech recognition system based on 5-state HMM + Multivariate Gaussian function. I use my own feature vector derived from MFCC (Mel-frequency cepstral coefficients). The problem is ...
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20 views

Exact inference in a Factorial HMM with 2 hidden state chains

I am trying to understand the process of exact inference in Factorial HMM models. While it is explained here (Appendix B, page 20). I think my goal is slightly different and I am struggling to fill in ...
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8 views

How to combine states of viterbi path?

I am using HMM in my project. After Viterbi, I can get a sequence, such as 0000000000011111011111100000000000111111111111....... The 0 in subsequence 111110111111 may be wrongly decoded. Because in ...
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34 views

Scaling the backward variable in HMM Baum-Welch

I am just trying to implement the scaled Baum-Welch algorithm and I have run into a problem where my backward variables, after scaling, are over the value of 1. Is this normal? After all, ...
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46 views

How to incorporate per-observation emission priors into HMM

I have a two-state HMM, in which my belief in emission probabilities depends on the observation. Basically, in addition to the two vectors of emission spectra (one for each state), I also have two ...
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101 views

Initial Probabilities of an HMM

I have a learned Hidden Markov Model (HMM) from a certain sequential data using Gibbs sampling. I have managed to obtain the transition probabilities (transition matrix) of the Markov chain and the ...
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29 views

Restrictions on the type of HMM observations

I am working on developing an HMM (or DBN) to detect vigilance from time-series observations of eye-closure. Vigilance is defined as a binary variable (vigilant or non-vigilant). While I understand ...
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44 views

Filtering with HMM

I want to use HMM for filtering, i.e. to find $p(x_t|y_{1:t})$. I see that the forward algorithm calculates the forward variable as a joint probability; $\alpha_t(i) = p(y_{1:t},x_t=S_i|\lambda)$, ...
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32 views

Nod and shake detection

I am trying to build a system to automatically detect head nods and shakes in videos. I have reliable eyes position information at each frame and I'd like to use the info to perform the detection of ...
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37 views

Hidden Markov Model: Average steps needed for the filtering density to reach a certain value

I need a hint for solving the following problem. The movement of a certain robot is modeled with a HMM. The robot moves on a circular path and at every time step, it either stays in the same location ...
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74 views

Using R and hidden Markov models to predict pseudorandom binary sequences better than P > .5?

I would to predict a pseudo-random binary sequence of 0's and 1's. I am thinking of using the HMM package in R. I have a binary sequence like ... 0 1 0 0 1 1 0 1 x(n+1)? with thousands of values. ...
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1answer
235 views

How to interpret Hidden Markov Model parameters (transition matrix, emission matrix, and pi values)?

I am working on channel modeling for cognitive radio using HMM. I've written a MATLAB program for forward, backward and Baum-Welch algorithm for multiple sequences. After given some random input and ...
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1answer
125 views

Why discriminative models are preferred to generative models for sequence labeling tasks?

I understand that discriminative models, such as CRF(Conditional Random Fields), model conditional probabilities $P(y|x)$, while generative models, such as HMM(Hidden Markov Model), model joint ...
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5answers
243 views

Is there any alternative to HMM?

I've been using Hidden Markov Models (HMM) for some time. Now I would like to know about any other statistical model that can prove to be as useful as HMM. For example I was exploiting HMM for gesture ...
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115 views

How to use prior probability in inferencing from HMM for activity recognition?

I am interested in modelling human activities using sensor data with HMMs and would like to incorporate prior knowledge during inference. The normal procedure is to model K different activities with K ...
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104 views

How to generalize Particle Filters (w.r.t. multiple states)

I'm using particle filters for inference in a hidden markov model with an infinite state-space. My current state-variable is multidimensional and there are interdependencies between some dimensions. I ...
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68 views

How to use Viterbi algorithm for multiple chain HMM?

I need to build a HMM with two chains: the structure is as the figure below. How can I use the Viterbi algorithm for this model?
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114 views

R: HMM package functions code - probObservations, pseudocounts and

I am trying to augment the functions from HMM package in R, in order to accomodate for a variant of HMM that includes a separate Transition Probability Matrix A_n for each sequence. The functions are ...
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2answers
236 views

How to handle high dimensional feature vector in probability graph model?

I was doing some NLP related stuff which involves training a hidden Markov model, and use the model to segment sentences. For every sentence, I translate the tokens into feature vectors. The features ...
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103 views

Output of Baum-Welch algorithm and clustering of HMM

I have trouble understanding the output of Baum-Welch algorithm in the context of clustering of time series of unequal length using HMM. Suppose I have N sequences with length L_i. An article that ...
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37 views

Confusion related to HMM

I was reading this book related to Pattern Recognition and Machine learning by Bishop. However, I have a confusion related to a derivation In the book when they calculate the marginal posterior of ...
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1answer
114 views

Confusion related to EM algorithm

I was reading this tutorial related to EM algorithm at http://aass.oru.se/~tdt/ml/extra-readings/EM_algorithm.pdf. As given in the tutorial we can see that at each E step we calculate the ...
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143 views

How to understand the label-bias problem in HMM?

How can I understand the label-bias problem in Hidden Markov Models? And why is CRF able to solve this problem?
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244 views

Criteria for selecting the “best” model in a Hidden Markov Model

I have a time series data set to which I am trying to fit a Hidden Markov Model (HMM) in order to estimate the number of latent states in the data. My pseudo code for doing this is the following: ...
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172 views

How do sudden spikes affect hidden Markov models

I have some data that has two sudden spikes (almost like extreme masses or Dirac delta functions) within my time series data and I was wondering if that is a problem when building hidden Markov ...
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128 views

Estimating the number of states via Hidden Markov Models

I have time series data from an accelerometer, and was wondering if hidden markov models (which I am not too familiar with) can be used to estimate the number of states in the model? I know typically ...
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1answer
92 views

Can first-order Markov chain be considered a special case of a hidden Markov model?

I am trying to apply R depmixS4 package in order to cluster time series with model based clustering. The model consists of K components, each being a first order Markov models. The ...
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49 views

Beyond observable and unobservable data, is there any term “semi-observable” defined?

When dealing with data in fields such as Natural Language Processing(NLP) or Speech Recognition(ASR) and trying to model the data using Hidden Markov Model(HMM) one should first make it clear that if ...
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1answer
197 views

Training a hidden Markov model

When it comes to the training of a Hidden Markov Model using multiple training instances should I first take a single instance and train the model until the convergence and then move on to the next ...
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95 views

Significance of a 1 state Hidden Markov Model

I've been training different observation sequences to obtain different HMMs corresponding to each observed data. Something intriguing is that I get one observation sequence represented by 1 state. ...
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153 views

Confusion about hidden Markov model

I've gone through Hidden Markov models (HMM) for the past few months. However there are a few things that are confusing. The set up is simple: I have to model some human gestures such as walking, ...
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219 views

How to calculate the log likelihood in HMM from the output of the forward algorithm in R?

How can I get the log likelihood or the probability value from the forward algorithm for an observed sequence? For example, when I executed the forward algorithm in ...
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151 views

Hidden Markov Model (HMM) training in R

I am working on a stock price prediction model using R. I am stuck at the "training a Hidden Markov Model (HMM)". In sklearn we have "fit method" to train a HMM. Is "initHMM" is training method in R? ...
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111 views

How is the Gaussian mixture model used in a hidden Markov model for speech recognition?

How is the Gaussian mixture model used in a hidden Markov model for speech recognition? How do you apply the EM algorithm to estimate the parameters of each Gaussian? How to utilized the transcription ...
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101 views

time complexity and space complexity for HMM forward recursion

When Reading the HMM models, I found the following discussion on the time complexity and space complexity regarding forward recursion. I am sort of confusing on the reason of getting O(K^2N) and ...
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1answer
81 views

gaussian mixture HMM

What is the difference of gaussian HMM and gaussian mixture HMM (the emission is gaussian or gaussian mixture)? I want to know if it is the same thing. What is the point when estimating the ...
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73 views

Hidden Markov model & statistical significance

I am using HMM to explore the language development of one individual with six variables as input, which are trained into three sequences. In the first state, the covariance of variable A and B is ...
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520 views

Predicting high frequency finance time series with HMM

I have a the following time series ...
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1k views

HMM forward algorithm in MATLAB

Does anyone know where can I find a pseudo code or MATLAB code of the HMM forward algorithm?
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102 views

HMM initialization

I'm working on implementing HMM Forward Algorithm in Matlab. I am having some difficulty in coding the $\alpha_{j}(t)$ initialize $t <- ,$ $a_{ij}, b_{jk}$, visible sequence $V^T, \alpha_j(0)$ ...
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212 views

Baum-welch algorithm: probabilities after each step

In an effort to understand machine learning, at least to some degree, I've been implementing the various algorithms to solve the three problems in a Hidden Markov Model. I've been using Rabiner's ...
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238 views

Two sequences, one HMM

I know how to fit a hidden markov model to a data sequence, using the matlab-implementation of the baum-welch algorithm. But what should I do if I do not have one data sequence, but a bunch of them? ...
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207 views

Comparison between MDL and BIC

I'm currently studying Hidden Markov Models. There's a set of observations from which I need to determine the optimal number of states. After having found the maximum likelihood using Baum-Welch, I ...
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168 views

Training Hidden Markov Models for multiple input observations

I'm working with Hidden Markov Models and I have a dataset composed by independent phrases, where each word is an observation. Hence, the best way to adjust my parameters (via Baum-Welch algorithm) is ...
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1answer
159 views

How to generate the most common clickstream sequence

I have logs with the following information: date-time username view action action_data These logs are generated from a web-application which consists of several views where the users can perform a ...
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87 views

How to handle new observations on HMM decoding?

I'm implementing the HMM algorithms described in Rabiner's tutorial. But there is several issues to considered when we apply HMM for real problems. One of this problems is how to consider new ...
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167 views

Question about classification with hidden Markov models using depmixS4

I am using the depmixS4 package to fit HMMs. I have three different classes of data and I have fitted 3 separate HMMs using the depmixS4 depmix and fit functions and given a new sequence of ...