I am using Sphinx 3. I am getting diffenrent warnings and errors at different steps. I need to know what is the meaning each of these errors and why are they coming.
In step 20.ci_hmm:
./hindi.1.2-1.bw.log:WARNING: "mod_inv.c", line 368: Model inventory n_density not set; setting to value in mixw file, 1.
./hindi.1.2-1.bw.log:WARNING: "mod_inv.c", line 256: n_top 4 > n_density 1. n_top <- 1
./hindi.1.2.norm.log:WARNING: NEGATIVE CONVERGENCE RATIO! CHECK YOUR DATA AND TRASNCRIPTS
In 30.cd_hmm_untied:
ERRORS:
./hindi.1-1.bw.log:ERROR: "backward.c", line 975: alpha(2.972315e-02) <> sum of alphas * betas (0.000000e+00) in frame 1233
./hindi.1-1.bw.log:ERROR: "baum_welch.c", line 331: hindi022 ignored
./hindi.2-1.bw.log:utt> 5 hindi006 999 0 372 13 ERROR: "backward.c", line 401: final state not reached
./t:./t:./hindi.3-1.bw.log:ERROR: "baum_welch.c", line 331: hindi054 ignored
./t:./t:./hindi.3-1.bw.log:utt> 54 hindi055 999 0 312 3 ERROR: "backward.c", line 401: final state not reached
WARNINGS:
./hindi.1-1.bw.log:utt> 167 hindi171 899 0 236 20 WARNING: "gauden.c", line 1382: Scaling factor too small: -758.437908
./hindi.1.norm.log:WARNING: "gauden.c", line 1606: (mgau= 1114, feat= 0, density= 0) never observed
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I've got the "NEGATIVE CONVERGENCE RATIO" warning when doing SphinxTrain. Could you elaborate on "missing some silences in prompts" ?
About using broken dictionary, I have checked my dictionary and i think it's just fine. The verify_all.pl scripts didn't give any warning or error.
regards
Eka
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I don't quite get what is your trouble in understanding this. The training process diverge because the phonetic transcription extracted from your transcriptoin file and your dictionary is not well suitable for the actual recording you made.
For example there is a silence in a recorded audio and it's not present in transcription file. Or all your speakers say HELLO as H EH L OW while your dictionary has the entry
HELLO G UH D B AY
verify_all doesn't check that obviously.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
I am using Sphinx 3. I am getting diffenrent warnings and errors at different steps. I need to know what is the meaning each of these errors and why are they coming.
In step 20.ci_hmm:
./hindi.1.2-1.bw.log:WARNING: "mod_inv.c", line 368: Model inventory n_density not set; setting to value in mixw file, 1.
./hindi.1.2-1.bw.log:WARNING: "mod_inv.c", line 256: n_top 4 > n_density 1. n_top <- 1
./hindi.1.2.norm.log:WARNING: NEGATIVE CONVERGENCE RATIO! CHECK YOUR DATA AND TRASNCRIPTS
In 30.cd_hmm_untied:
ERRORS:
./hindi.1-1.bw.log:ERROR: "backward.c", line 975: alpha(2.972315e-02) <> sum of alphas * betas (0.000000e+00) in frame 1233
./hindi.1-1.bw.log:ERROR: "baum_welch.c", line 331: hindi022 ignored
./hindi.2-1.bw.log:utt> 5 hindi006 999 0 372 13 ERROR: "backward.c", line 401: final state not reached
./t:./t:./hindi.3-1.bw.log:ERROR: "baum_welch.c", line 331: hindi054 ignored
./t:./t:./hindi.3-1.bw.log:utt> 54 hindi055 999 0 312 3 ERROR: "backward.c", line 401: final state not reached
WARNINGS:
./hindi.1-1.bw.log:utt> 167 hindi171 899 0 236 20 WARNING: "gauden.c", line 1382: Scaling factor too small: -758.437908
./hindi.1.norm.log:WARNING: "gauden.c", line 1606: (mgau= 1114, feat= 0, density= 0) never observed
I can only repeat:
CHECK YOUR DATA AND TRASNCRIPTS
Probably you are missing some silences in prompts and Baum-Welsh doesn't converge. Or you are just using broken dictionary.
Hi Nickolay
I've got the "NEGATIVE CONVERGENCE RATIO" warning when doing SphinxTrain. Could you elaborate on "missing some silences in prompts" ?
About using broken dictionary, I have checked my dictionary and i think it's just fine. The verify_all.pl scripts didn't give any warning or error.
regards
Eka
I don't quite get what is your trouble in understanding this. The training process diverge because the phonetic transcription extracted from your transcriptoin file and your dictionary is not well suitable for the actual recording you made.
For example there is a silence in a recorded audio and it's not present in transcription file. Or all your speakers say HELLO as H EH L OW while your dictionary has the entry
HELLO G UH D B AY
verify_all doesn't check that obviously.