# Questions tagged [hidden-markov-model]

For questions related to the hidden Markov model and related algorithms such as the forward algorithm.

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### How to estimate the number of training samples to train a HMM Model with Baum-Welch Algorithm

Is there a thumb rule that tells us how many data sample a HMM model needs to be trained by Baum-Welch Algorithm?
59 views

### How to validate a trained HMM Model?

What are some approaches to validate a HMM Model ? I want to check if a trained model is good enough to put it into operation or if it does need more training. I am using the Baum Welch algorithm to ...
35 views

### What is meant by decoding in a Hidden Markov Model?

HMM contains two types of states: observable and hidden. Let $\{ h_1,h_2,h_3,\cdots,h_n\}$ be hidden states and $\{o_1,o_2,o_3,\cdots, o_m\}$ be the observable states. Suppose the $n^2$ transition ...
14 views

### Looking for help on initializing continuous HMM model for word level ASR

I have been studying HMM implementation approaches on ASR for the last couple of weeks. This probabilistic model is very new to me. I am currently using a Python package called Pomegranate to ...
96 views

### Determining observation and state spaces for viterbi algorithm in a simple word recognition system using HMM

The system I'm trying to implement is a microcontroller with a connected microphone which have to recognise single words. the feature extraction is done using MFCC (and is working). the system have ...
41 views

### Is there an equivalent model to the Hidden Markov Model for continuous hidden variables?

I understand that Hidden Markov Models are used to learn about hidden variables $z_i$ with the help of observable variables $\xi_i$. On Wikipedia, I read that while the $\xi_i$'s can be continuous (...
13 views

### How do multiple coordinate systems help in capturing invariant features?

I've been reading this paper that formulates invariant task-parametrized HSMMs. The task parameters are represented in $F$ coordinate systems defined by $\{A_j,b_j\}_{j=1}^F$, where $A_j$ denotes the ...
62 views

### How to deal with very, very small time-series?

I have an ensemble of 231 time series, the largest among them being 14 lines long. The task at hand is to try to predict these time-series. But I'm finding this difficult due to the very small size of ...
61 views

### What is a Hidden Markov Model - Artificial Neural Network (HMM-ANN)?

As far as I know, neural networks have hidden computational units and HMM has hidden states. Hidden Markov Models can be used to generate a language, that is, list elements from a family of strings. ...
68 views

### How can I use a Hidden Markov Model to recognize images?

How could I use a 16x16 image as an input in a HMM? And at the same time how would I train it? Can I use backpropagation?
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### Expected duration in a state

I am going through Rabiner 1989 and he writes that the discrete probability density function of duration $d$ in state $i$ (that is, staying in a state for duration $d$, conditioned on starting in that ...
38 views

### is a "word prediction" problem, applicable using HMMs?

I'm learning HMMs and decided to model a problem for learning purposes. I came to this idea of word predicting by letters. here is the model : while typing, the word is typed letter by letter, so we ...
161 views

### What are the differences between CRF and HMM?

What I know about CRF is that they are discriminative models, while HMM are generative models, but, in the inference method, both use the same algorithm, that is, the Viterbi algorithm, and forward ...
18 views

### Predicting Hot Categories In a Reference Manager

Reference managers like Zotero or Mendeley allow researchers to categorize papers into hierarchical categories called collections. The User navigates through a listing of these collections when filing ...
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### Can HMM, MRF, or CRF be used to classify the state of a single observation, not the entire observation sequence?

I learn that the Viterbi algorithm used for Hidden Markov Model (HMM) can classify a sequence of hidden states from the corresponding observations; Markov Random Field (MRF) and Conditional Random ...