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# Questions tagged [hidden-markov-models]

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### 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 ...
917 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 ...
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 ...
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/...
162 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 ...
51 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 ...
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, ...
232 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 ...
910 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 ...
217 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 ...
106 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 ...
142 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 ...
232 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 ...
280 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....
140 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 ...
91 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 ...
99 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 ...
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 '...
324 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: ...
50 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 ...
494 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 ...
810 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 ...
267 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 ...
28 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. ...
74 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 ...
30 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 ...
82 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 $459^2$, ...
51 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 ...
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 ...
23 views

### Can Hidden Markov Models be used for real-time analysis?

From what I understand, HMMs construct a underlying sequence of states to maximize the probability of a sequence of observations. As far as I can tell, that should make them inappropriate to use ...
15 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 ...