How to Install and Uninstall festvox-kal-diphone.noarch Package on CentOS Stream 8

Last updated: February 06,2025

1. Install "festvox-kal-diphone.noarch" package

This guide let you learn how to install festvox-kal-diphone.noarch on CentOS Stream 8


    
        
            $
        

        
            
                sudo dnf update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf install
            
                        
                festvox-kal-diphone.noarch
            
                    
    
    Copied

2. Uninstall "festvox-kal-diphone.noarch" package

Learn how to uninstall festvox-kal-diphone.noarch on CentOS Stream 8:


    
        
            $
        

        
            
                sudo dnf remove
            
                        
                festvox-kal-diphone.noarch
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the festvox-kal-diphone.noarch package on CentOS Stream 8

Last metadata expiration check: 5:14:31 ago on Sun Feb 25 03:03:59 2024.
Available Packages
Name : festvox-kal-diphone
Version : 0.19990610
Release : 14.el8
Architecture : noarch
Size : 3.7 M
Source : festival-2.5.0-14.el8.src.rpm
Repository : epel
Summary : American English male speaker "Kevin" for Festival
URL : http://www.cstr.ed.ac.uk/projects/festival/
License : MIT and GPL+ and TCL and BSD
Description : American English male speaker ("Kevin") for Festival.
:
: This voice provides an American English male voice using a residual excited
: LPC diphone synthesis method. It uses the CMU Lexicon pronunciations.
: Prosodic phrasing is provided by a statistically trained model using part of
: speech and local distribution of breaks. Intonation is provided by a CART
: tree predicting ToBI accents and an F0 contour generated from a model
: trained from natural speech. The duration model is also trained from data
: using a CART tree.