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1answer
34 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 ...
6
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2answers
47 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 ...
1
vote
1answer
48 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: ...
2
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2answers
149 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 ...
0
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1answer
125 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 ...
2
votes
1answer
36 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
70 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 ...
2
votes
1answer
70 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 ...
3
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1answer
170 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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0answers
512 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 ...
2
votes
2answers
81 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 ...
4
votes
1answer
478 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 ...
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2answers
520 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 ...
3
votes
1answer
87 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 ...