Hello!!
I have a basic question about he model of recognition of Cmu Sphinx.
When I read the tutorial "Basic Concept of Speech" it is written that the model of recognition is based on Hidden Markov Model.
But then I read a text "Grapheme to Phoneme Tools based on sequence-to-sequence learning" where it seems that the model used is based on neural networks.
What kind of model is finally used in CMU Sphinx (excuse for my basic question) ??
Could someone explain me ? Has CmuSphinx something to do with Machine Learning?
Thanks in advance for any answer
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Thanks Nickolay V. Shmyrev
On Wikipedia I read the different approaches of machine learning :
decision tree learning, association rule learning, neural networks, deep learning, inductive logic programming, support vector machines, clustering, bayesian networks, reinforcement learning, representation learnng, etc...
cf https://en.wikipedia.org/wiki/Machine_learning#Decision_tree_learning
What kind of approach (as specified i Wikipedia) is Hidden Markov Model belonging to ??
Thanks
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Hidden markov model sequence modeling is one of the core machine learning algorithms, but it is not listed on the page you cited. It is listed on the extended version though:
Hello!!
I have a basic question about he model of recognition of Cmu Sphinx.
When I read the tutorial "Basic Concept of Speech" it is written that the model of recognition is based on Hidden Markov Model.
But then I read a text "Grapheme to Phoneme Tools based on sequence-to-sequence learning" where it seems that the model used is based on neural networks.
What kind of model is finally used in CMU Sphinx (excuse for my basic question) ??
Could someone explain me ? Has CmuSphinx something to do with Machine Learning?
Thanks in advance for any answer
cmusphinx used hidden markov models. g2p-seq2seq is an experimental submodule only.
cmusphinx is all about machine learning. The goal is to teach machine to recognize speech.
Thanks Nickolay V. Shmyrev
On Wikipedia I read the different approaches of machine learning :
decision tree learning, association rule learning, neural networks, deep learning, inductive logic programming, support vector machines, clustering, bayesian networks, reinforcement learning, representation learnng, etc...
cf https://en.wikipedia.org/wiki/Machine_learning#Decision_tree_learning
What kind of approach (as specified i Wikipedia) is Hidden Markov Model belonging to ??
Thanks
Hidden markov model sequence modeling is one of the core machine learning algorithms, but it is not listed on the page you cited. It is listed on the extended version though:
https://en.wikipedia.org/wiki/List_of_machine_learning_concepts