Re: [Kaldi-developers] decoding with noise words

[Daniel P. <dp...@gm...>]

Also, you can just add a self-loop at each state (or just at the unigram
backoff state) in the LM, for each noise type, with an appropriate cost.
 In IBM I think we did it just at the unigram backoff state (this was for
silence modeling).
Dan


On Tue, Nov 6, 2012 at 6:39 AM, Arnab Ghoshal <ar...@gm...> wrote:

> Of course you need those words in your LM if you need them in your
> output. You can use a single <NOISE> tag like in the WSJ recipe, or
> use more fine-grained noise tags like in the Switchboard recipe (or
> the particular tags you suggest). Under normal circumstances, you are
> supposed to remove the noises from transcript and output before
> scoring.
>
> On Mon, Nov 5, 2012 at 9:08 PM, mark li <mar...@gm...> wrote:
> > Hi, Guys:
> >
> > I am using the Kaldi to decode my data, which includes 5 percent noise
> > words (e.g. UM UHMM, Laughter, ++BRTH++, ++Music++, etc ). Those words
> > are not in LM.  I found the Kaldi is really great except for those
> > noise words.  Whenever such words occur,  the decoding output an error
> > result.  Is there a way to deal with them during decoding the noise
> > words even if they are not in LM. It is almost not possible to model
> > those noise word in the LM because they may appear anywhere. I mean is
> > there a way like that Sphinx dealing with filler words)?
> >
> > thanks
> >
> > Mark
> >
> >
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