Skip to content

Makefile recipe to train htk acoustic models using the spanish data on voxforge. It should be working by just updating the paths and typing: make all.

Notifications You must be signed in to change notification settings

thomaskisler/spanish_voxforge_htk_asr

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Here are the scripts I used to train an HTK recognizer using 
the spanish data I found on Voxforge (approx. 20 hours). The 
data are not perfect but one can build a baseline recognizer using them. The
recipe is based on Keith Vertanen's scripts for HTK TIMIT + WSJ 
ASR training (http://www.keithv.com/software/htk).

Experimenting with Makefiles these days, I wrote the entire 
process as a Makefile and I have to say it can be quite convenient for this task.
However, there are many things that I haven't really fixed and haven't
yet fully harnessed the power of make :) This is yet to be done.

The idea is to just write (after updating the paths in the makefile):
make all

and wait. Of course you may need to delve deeper into the code if you have more 
specific needs. I haven't really tested it yet in an independent setup so it
may need minor modifications to work for a different dataset or on a 
different machine. I will be working on it and this code should only 
be considered as a working version and not an official release.

In case you just need the spanish acoustic models for HTK, please feel free
to contact me and I could share them with you. If you have spanish data
you would like to train an ASR on, we could work on that together. 

Nassos Katsamanis

About

Makefile recipe to train htk acoustic models using the spanish data on voxforge. It should be working by just updating the paths and typing: make all.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Perl 58.9%
  • Makefile 22.4%
  • Shell 15.0%
  • Python 3.7%