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Questions tagged [hidden-markov-models]

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7
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2answers
209 views

Why are HMMs appropriate for speech recognition when the problem doesn't seem to satisfy the Markov property

I'm learning about HMMs and their applications and trying to understand their usages. My knowledge is a bit spotty, so please correct any incorrect assumptions I'm making. The specific example I'm ...
4
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2answers
850 views

Combining multiple HMM models

Is there any way to combine multiple Hidden Markov Models trained from different sets of data? For example, I want to detect the phases of a sequential activity. I collect two sets of data by using ...
4
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1answer
47 views

Hidden Markov Model initial probability reestimate: Why $\pi^*_i = \gamma_i(1)$ instead of $\pi^*_i = \frac{\gamma_i(1)}{\sum_{j = 1}^N \gamma_j(1)}$

In the sources I consulted it states that in the Baum Welch algorithm the reestimate of the initial probability of state $i$ of the HMM is $\pi^*_i = \gamma_i(1)$. But $\gamma_i(t)$ is the probability ...
4
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1answer
1k views

Viterbi training vs. Baum-Welch algorithm

I'm trying to find the most probable path (i.e., sequence of states) on an hidden Markov model (HMM) using the Viterbi algorithm. However, I don't know the transition and emission matrices, which I ...
4
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0answers
2k views

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 - en.wikipedia.org/wiki/N-gram and aicat.inf.ed.ac.uk/...
3
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1answer
158 views

Is it viable to use an HMM to evaluate how well a catalogue is used?

I was interested on evaluating a catalogue that students would be using to observe how is it being used probabilistically. The catalogue works by choosing cells in a temporal sequence, so for ...
3
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1answer
27 views

HMM tagger - Baum Welch training

I am trying to implement a trigram HMM tagger for a language that has over 1000 tags. In my training data I have 459 tags. Now if we consider that states of the HMM are all possible bigrams of tags, ...
3
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1answer
213 views

How do POMDPs and Dynamic Influence Diagrams differ?

To give some perspective, first consider the following diagram comparing Markov Chains, HMMs, MDPs, and POMDPs (I'm not sure who to credit for it). Fully observable ...
3
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1answer
866 views

Viterbi algorithm recursive justification

I have a question regarding recursion in Viterbi algorithm. Define $\pi(k; u; v)$ which is the maximum probability for any sequence of length $k$, ending in the tag bigram $(u; v)$. The base case ...
2
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1answer
194 views

counteracting numerical instability in HMM training

I am training a HMM with Baum Welch for part of speech tagging. I am training the model with 79 hidden variables (part of speech tags) and 80,000 observed variables (words). I am working with log ...
2
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1answer
105 views

Solving the part-of-speech tagging problem with HMM

There is a famous part-of-speech tagging problem in Natural Language Processing. The popular solution is to use Hidden Markov Models. So that, given the sentence $x_1 \dots x_n$ we want to find the ...
2
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2answers
141 views

Hidden Markov Model in Tagging Problem

I try to understand the details regarding using Hidden Markov Model in Tagging Problem. The best concise description that I found is the Course notes by Michal Collins. The goal is to find a ...
2
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1answer
170 views

Viterbi Algorithm: initial state with ONE probability

The Viterbi Algorithm can be used to calculate the most likely path, based on observations in a Hidden Markov Model. Using the same notations as Wikipedia, "each element ...
2
votes
1answer
259 views

Convergence of Markov model

I was learning Hidden Markov model, and encountered this theory about convergence of Markov model. For example, consider a weather model, where on a first-day probability of weather being sunny was 0....
2
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1answer
129 views

What type of HMM-GMM I need

Context: I have 100 speech sentences that I asked my friend to speak. The vocabulary in the sentences are same but only the order of words are changed. My friend says that he spoke exactly what was ...
2
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0answers
71 views

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 ...
2
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0answers
97 views

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 ...
1
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2answers
2k views

Machine learning algorithm(s) for recognizing simple graph patterns

I generate some simple graphs based on usage stats of a website, and they may look like these: I call the 'pattern' on the left 'convergence', and the 'pattern' on the right 'divergence'. The terms '...
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2answers
309 views

How to properly solve this Hidden Markov Model problem?

I got a an exercise problem which should be seen as a HMM scenario and argument some statements. However I'm quite confused about how to properly solve and argument my solutions. Problem tells: ...
1
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1answer
44 views

Examples of difference between Hidden Markov Model and Bayesian Network?

I am trying to more deeply understand the difference between Hidden Markov Models and Bayesian Network? The general idea is that HMMs have a single variable which has probabilities of entering ...
1
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1answer
446 views

Training a HMM with Baum-Welch gives different results across runs

I am running a Baum-Welch HMM algorithm (in R). The sequence vector contains a series of observations which have been gathered from a dataset where the data has 17 states. I can successfully run the ...
1
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2answers
806 views

Any very user friendly resources on the Baum-Welch algorithm?

I'd like to understand the Baum-Welch algorithm. I liked this video on the Forward-Backward algorithm so I'd like a similar one for Baum-Welch. I'm having trouble coming up with good resources for ...
1
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1answer
247 views

Bayesian Nets & Markov Blanket

As i passed PHD entrance exam, some days ago, i want to find solutions for challenging problem. In Bayes network on X={X1,...Xn} each random variable has P parents and Q child's. for Xi we want to ...
1
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1answer
16 views

Prior probability in HMM

This is the HMM model considered in the question And this is the emission probabilities for the respective states. There are two emission values, bringing an umbrella and not bringing an umbrella. ...
1
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0answers
48 views

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 ...
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0answers
26 views

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 ...
1
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0answers
72 views

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 $459^2$, ...
1
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0answers
48 views

Machine Learning Algorithm Recommendation For Sensor Data [closed]

I would like to classify data coming from a sensor. In the literature Hidden Markov Model and SVM are used, but I would like to improve results with another methods.The picture how data and classes ...
0
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1answer
4k views

Build Automatic Speech Recognition (ASR) from scratch [closed]

I want to build a Automatic Speech Recognition (ASR) engine for myself, but I've no idea from where to start. I've read that most ASR's are build upon Hidden Markov Models, but also I've read that ...
0
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0answers
11 views

How do I re-estimate exit probabilities in a HMM using Baum-Welch training?

We are currently learning about HMMs at university. I managed to understand almost everything about B-W training. However, I find it a bit confusing when it comes to exit probabilities. Are they ...
0
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0answers
9 views

requisites for building a HMM model

I have been reading some literature about HMM and for what I know the Baum-Welch algorithm can be used for training a HMM model. So my question would be, which are the minimum components that I need ...
0
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0answers
27 views

Hidden Markov Model with likelihood sampling method

I have a revision question for an exam which I'm unsure about. The question includes Hidden Markov Model which I'm well aware of, but I'm just not sure how to use the weighted sampling method in this ...
0
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1answer
300 views

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 ...
0
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0answers
383 views

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–...