--- In icsi-speech-tools@yahoogroups.com, "qingqing.zhang"
<qingqing.zhang@...> wrote:
>
> When I use MLP as my HMM features, the POSITIVE posteriori
> probabilities always occurred. The POSITIVE posteriori probabilities
> will break the decoding rule and result in bad performances. I don't
> know whether you found the same problem, and what can I do to avoid
> this? Thank you very much!
>

I'm not sure I understand. If you're using softmax as the output layer
of the MLP, then all the values should be between 0.0 and 1.0. If
you're not using softmax, the values can be pretty much anything.

Perhaps your decoder wants log probabilities? Taking -24*log(p) and
then clipping between 0 and 255 is the usual way we do this (called
"lna format"). Also, sometimes the systems take scaled likelihoods
rather than posteriors as input. In this case, you can just divide by
the priors of the phones.

If this doesn't answer your question, could you please post more details?

Adam