<b>
WARNING: "gauden.c", line 1418: Scaling factor too small: -913.889597
ERROR: "backward.c", line 975: alpha(1.478608e-01) <> sum of alphas * betas (0.000000e+00) in frame 206
ERROR: "baum_welch.c"
</b>
Please shed some light on this. Thanks in advance.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
These errors usually mean either that something is pathological about your training data, or that there is a mismatch between the model used to run forward-backward and the data on which you are running it.
The assertion has been triggered (as the message indicates) because of an infinity in the Gaussian density calculation. This could occur if the variance for some mixture is zero.
Could you say a bit more about the features you're using?
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
hi,
we were training the sphinx recognizer using features (not mfcc) when we got this error:
<b>
bw: gauden.c:1425: gauden_scale_densities_bwd: Assertion `finite(den[c][j][k])' failed.
</b>
and this warning
<b>
WARNING: "gauden.c", line 1418: Scaling factor too small: -913.889597
ERROR: "backward.c", line 975: alpha(1.478608e-01) <> sum of alphas * betas (0.000000e+00) in frame 206
ERROR: "baum_welch.c"
</b>
Please shed some light on this. Thanks in advance.
Hi,
These errors usually mean either that something is pathological about your training data, or that there is a mismatch between the model used to run forward-backward and the data on which you are running it.
The assertion has been triggered (as the message indicates) because of an infinity in the Gaussian density calculation. This could occur if the variance for some mixture is zero.
Could you say a bit more about the features you're using?
thanks !
we are testing some new features developed in our lab.
rgds