I am doing Sphinx training. It starts fine. Every test passed in initial
steps. Trees have been built. In the Module 50, first gaussian iterations are
finished without problem. when it splits to two gaussians I am gettting error.
MODULE: 50 Training Context dependent models (2011-12-18 03:17)
Phase 1: Cleaning up directories:
accumulator... logs... qmanager... completed
Phase 2: Copy CI to CD initialize
init_mixw Log File
Current Overall Likelihood Per Frame = 5.27179472944965
Convergence Ratio = 0.280849058955256
Baum welch starting for 2 Gaussian(s), iteration: 4 (1 of 1)
bw Log File
completed
Only 0 parts of 1 of Baum Welch were successfully completed
Parts 1 failed to run!
When I opened Log File, I found the following error
When you report about the training problem please learn to provide as much
information as possible:
What sphinxtrain version are you using
What is the size of the training database
What modifications in default training parameters have you made
Such information could help to answer your problem quickly. For example one
could easily figure out that you just don't have enough data to train the
parameters you configured.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
I am sorry for not providing enough information. I am using sphinxtrain build
nightly which I downloaded in July. I have enough speech data which is 25
hours. I am training for 16 gaussians and 1000 senones.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
I have already trained successfully 20 hours data with 16 gaussians. The
vocabulary is about 7000. But Now I have added 4 hours more and I am training
it again. Vocabulary increased to 13000. I don't see the question of not
having enough data for training.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
I am doing Sphinx training. It starts fine. Every test passed in initial
steps. Trees have been built. In the Module 50, first gaussian iterations are
finished without problem. when it splits to two gaussians I am gettting error.
MODULE: 50 Training Context dependent models (2011-12-18 03:17)
Phase 1: Cleaning up directories:
accumulator... logs... qmanager... completed
Phase 2: Copy CI to CD initialize
init_mixw Log File
Current Overall Likelihood Per Frame = 5.27179472944965
Convergence Ratio = 0.280849058955256
Baum welch starting for 2 Gaussian(s), iteration: 4 (1 of 1)
bw Log File
completed
Only 0 parts of 1 of Baum Welch were successfully completed
Parts 1 failed to run!
When I opened Log File, I found the following error
-0.16
bw: gauden.c:1348: gauden_scale_densities_bwd: Assertion `finite(den)' failed.
column defns
<seq>
<id>
<n_frame_in>
<n_frame_del>
<n_state_shmm>
<avg_states_alpha>
<avg_states_beta>
<avg_states_reest>
<avg_posterior_prune>
<frame_log_lik>
<utt_log_lik>
... timing info ...
utt> 0 10-1 2964 0 936 14 Sun Dec 18 03:28:03 2011 </utt_log_lik></frame_log_lik></avg_posterior_prune></avg_states_reest></avg_states_beta></avg_states_alpha></n_state_shmm></n_frame_del></n_frame_in></id></seq>
Can you please guide me what could be the reason
When you report about the training problem please learn to provide as much
information as possible:
What sphinxtrain version are you using
What is the size of the training database
What modifications in default training parameters have you made
Such information could help to answer your problem quickly. For example one
could easily figure out that you just don't have enough data to train the
parameters you configured.
I am sorry for not providing enough information. I am using sphinxtrain build
nightly which I downloaded in July. I have enough speech data which is 25
hours. I am training for 16 gaussians and 1000 senones.
I have already trained successfully 20 hours data with 16 gaussians. The
vocabulary is about 7000. But Now I have added 4 hours more and I am training
it again. Vocabulary increased to 13000. I don't see the question of not
having enough data for training.