while creating acoustic model i created dictionary ,filler dictionary ,fields file and transcript all file required for the acoustic model training
setting acoustic model using scripts(setup_SphinxTrain.pl) in sphinx train.
then creating feature for the wav file using make_feat.pl script in SphinxTrain.
running ./scripts_pl/RunAll.pl to train model
Html log file created by sphinx Train show warning and errors relating to the
training acoustic model:
Phase 3: Forward-Backward
Baum welch starting for 1 Gaussian(s), iteration: 1 (1 of 1)
bw Log File
This step had 28 ERROR messages and 12 WARNING messages. Please check the log
file for details.
**
ERROR MESSAGE
utt> 13 FM014014 104 0 20 12 WARNING: "gauden.c", line 1370: Scaling factor
too small: -873.324838
ERROR: "backward.c", line 1171: alpha(3.315119e-05) <> beta(3.588999e-81)
1 3 1.423793e-12ERROR: "baum_welch.c", line 331: train/FM014014 ignored
**same error is repeating with 14 annotation out of 4494.
and error repeats in each iteration.
whereas after completion of training i am able to run pocketsphinx_continous
,batch commands with new hmm model created by this and also give results.
Is this problem with respect to speech files as only some of speech files are
ignored.Is there any way to remove these errors .
Error is related to alpha and beta values calculated using speech file.Does
ignoring this error hamper performance of acoustic model.
I will be obliged if some one can point me resources which can let me know how
small values of alpha and beta leads to ignoring features of these speech
file.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Is this problem with respect to speech files as only some of speech files
are ignored
Yes
Is there any way to remove these errors.
Probably files have noise, zero energy regions or some other issues. Remove
those files from training database or fix their transcription. Or record them
once again.
Does ignoring this error hamper performance of acoustic model.
No
I will be obliged if some one can point me resources which can let me know
how small values of alpha and beta leads to ignoring features of these speech
file
we were trying to build a acoustic model on collection of data (speech wav
file) using http://cmusphinx.sourceforge.net/wiki/tutorialam .
Html log file created by sphinx Train show warning and errors relating to the
training acoustic model:
Phase 3: Forward-Backward
Baum welch starting for 1 Gaussian(s), iteration: 1 (1 of 1)
bw Log File
This step had 28 ERROR messages and 12 WARNING messages. Please check the log
file for details.
**
ERROR MESSAGE
utt> 13 FM014014 104 0 20 12 WARNING: "gauden.c", line 1370: Scaling factor
too small: -873.324838
ERROR: "backward.c", line 1171: alpha(3.315119e-05) <> beta(3.588999e-81)
1 3 1.423793e-12ERROR: "baum_welch.c", line 331: train/FM014014 ignored
**same error is repeating with 14 annotation out of 4494.
and error repeats in each iteration.
whereas after completion of training i am able to run pocketsphinx_continous
,batch commands with new hmm model created by this and also give results.
Is this problem with respect to speech files as only some of speech files are
ignored.Is there any way to remove these errors .
Error is related to alpha and beta values calculated using speech file.Does
ignoring this error hamper performance of acoustic model.
I will be obliged if some one can point me resources which can let me know how
small values of alpha and beta leads to ignoring features of these speech
file.
Yes
Probably files have noise, zero energy regions or some other issues. Remove
those files from training database or fix their transcription. Or record them
once again.
No
Rabiner HMM Tutorial
http://www.cs.ubc.ca/~murphyk/Bayes/rabiner.pdf
thanks...