How to Install and Uninstall openfst.i686 Package on Fedora 34

Last updated: April 25,2024

1. Install "openfst.i686" package

This guide covers the steps necessary to install openfst.i686 on Fedora 34


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                openfst.i686
            
                    
    
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2. Uninstall "openfst.i686" package

This tutorial shows how to uninstall openfst.i686 on Fedora 34:


    
        
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                sudo dnf remove
            
                        
                openfst.i686
            
                    
    
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            $
        

        
            
                sudo dnf autoremove
            
                    
    
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3. Information about the openfst.i686 package on Fedora 34

Last metadata expiration check: 1:42:24 ago on Tue Sep 6 02:10:55 2022.
Available Packages
Name : openfst
Version : 1.6.9
Release : 8.fc34
Architecture : i686
Size : 4.0 M
Source : openfst-1.6.9-8.fc34.src.rpm
Repository : fedora
Summary : Weighted finite-state transducer library
URL : http://www.openfst.org/
License : ASL 2.0
Description : OpenFst is a library for constructing, combining, optimizing, and
: searching weighted finite-state transducers (FSTs). Weighted
: finite-state transducers are automata where each transition has an input
: label, an output label, and a weight. The more familiar finite-state
: acceptor is represented as a transducer with each transition's input and
: output label equal. Finite-state acceptors are used to represent sets
: of strings (specifically, regular or rational sets); finite-state
: transducers are used to represent binary relations between pairs of
: strings (specifically, rational transductions). The weights can be used
: to represent the cost of taking a particular transition.
:
: FSTs have key applications in speech recognition and synthesis, machine
: translation, optical character recognition, pattern matching, string
: processing, machine learning, information extraction and retrieval among
: others. Often a weighted transducer is used to represent a
: probabilistic model (e.g., an n-gram model, pronunciation model). FSTs
: can be optimized by determinization and minimization, models can be
: applied to hypothesis sets (also represented as automata) or cascaded by
: finite-state composition, and the best results can be selected by
: shortest-path algorithms.