1. First compile the Julian grammar files (i.e. the one you added to you test directory in Step 2) as follows:
$mkdfa.pl sample |
2. Next, create a file in your test directory to tell Julius where
all your wav files are
located (Julius can use the same mfc files as does HTK, but recognition
rates seem better when using the original wav files). It should
look like this:
wavlst
3. Next update your Julian configuration file as follows:
4. Then use Julian to recognize the test data as follows:
a. If you created your Acoustic Model using the VoxForge How-to or Tutorial, execute the following command:
| $ julian -input rawfile
-filelist wavlst -smpFreq 48000 -C julian.jconf >
juliusOutput |
b. If you Adapted the VoxForge Speaker Independent Acoustic Models to your voice using the adaptation tutorial, execute the following command:
| $ julian -input rawfile
-filelist wavlst -smpFreq 8000 -C julian.jconf >
juliusOutput |
which creates the following file:
juliusOutput
6. Then execute it as follows (note: you may need to make this script executable - see Cheat Sheet on the Docs page):
| $./ProcessJuliusOutput.pl juliusOutput juliusProcessed |
7. Finally, run the following command to determine the actual recognition performance of the Acoustic Model:
| $HResults -I testref.mlf tiedlist juliusProcessed |
which will display output similar to this (note: these are results
for the 8kHz:16-bit VoxForge Speaker Independent Acoustic Model, build
396, which includes speech audio using my voice, so the results are better than what you would get):
| ====================== HTK Results Analysis ======================= Date: Fri Sep 29 12:42:14 2006 Ref : testref.mlf Rec : juliusProcessed ------------------------ Overall Results -------------------------- SENT: %Correct=82.00 [H=41, S=9, N=50] WORD: %Corr=96.83, Acc=94.71 [H=183, D=2, S=4, I=4, N=189] =================================================================== |
What this means is that: