HumIT ex1gr3

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(Created page with "= Exercise 1 - Group 3 = == List of topics for HumIT and other HFOSS learning activities == Working with an HFOSS project - Build towards a Sign-Language recognition packag...")
 
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Build towards a Sign-Language recognition package
 
Build towards a Sign-Language recognition package
  
    Learn to use the SPHINX speech recognition package
+
Learn to use the SPHINX speech recognition package
 
      
 
      
        Obtain and install the software
+
Obtain and install the software
 
          
 
          
        Run a demo dataset
+
Run a demo dataset
            This is a substantial learning activity.  It involves becoming familiar with
+
*This is a substantial learning activity.  It involves becoming familiar with formats of audiology datasets, and their adaptation to SPHINX.
            formats of audiology datasets, and their adaptation to SPHINX.
+
 
              
 
              
    Modify SPHINX for alternative kinds of data (e.g. vectors extracted from images/videos
+
Modify SPHINX for alternative kinds of data (e.g. vectors extracted from images/videos of sign language in use)
    of sign language in use)
+
 
          
 
          
        Understand topologies of models for training
+
Understand topologies of models for training
 
      
 
      
  
 
[http://foss.unh.edu/mediawiki/index.php/Speech:Home Speech @ UNH Manchester]
 
[http://foss.unh.edu/mediawiki/index.php/Speech:Home Speech @ UNH Manchester]

Revision as of 18:41, 31 August 2017

Exercise 1 - Group 3

List of topics for HumIT and other HFOSS learning activities

Working with an HFOSS project -

Build towards a Sign-Language recognition package

Learn to use the SPHINX speech recognition package

Obtain and install the software

Run a demo dataset

  • This is a substantial learning activity. It involves becoming familiar with formats of audiology datasets, and their adaptation to SPHINX.

Modify SPHINX for alternative kinds of data (e.g. vectors extracted from images/videos of sign language in use)

Understand topologies of models for training


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