Re: [Kaldi-users] LM weight

[Kirill K. <kir...@sm...>]

Aha, thanks, I see a pattern! I've got roughly same number of insertions and deletions at the original weight 0.5. I'll split off a dev set and try to tune the penalty.

Is there any theory behind this optimal ins/del ratio, or is it just a trick of the art?

 -kkm

> -----Original Message-----
> From: Daniel Povey [mailto:dp...@gm...]
> Sent: 2015-06-22 2357
> To: Kirill Katsnelson
> Cc: Nagendra Goel; kal...@li...
> Subject: Re: [Kaldi-users] LM weight
> 
> It could still be about insertion errors.  Typically you want insertion
> rates about 1/3 to 1/2 as big as deletion rates.  If your setup is
> getting too many insertions, it could be using the LM scale to
> compensate.  Playing with an insertion penalty may help (see the more
> recent scoring scripts).
> Dan
> 
> 
> On Tue, Jun 23, 2015 at 1:04 AM, Kirill Katsnelson
> <kir...@sm...> wrote:
> > Yes, I am using the pretty standard nnet2_online model with the
> librispeech data, with a 8 kHz conversion and a squished frequency
> range of the high-res features, as I am finding there is a lot of
> rather useless variance in the very low range, given the data are
> coming mostly from cell phones. But nothing fancy there overall.
> >
> >  -kkm
> >
> >> -----Original Message-----
> >> From: Daniel Povey [mailto:dp...@gm...]
> >> Sent: 2015-06-22 2131
> >> To: Kirill Katsnelson
> >> Cc: Nagendra Goel; kal...@li...
> >> Subject: Re: [Kaldi-users] LM weight
> >>
> >> By a lot of context I mean left-context and right-context, in the
> >> splicing.  But I guess you are using one of the standard types of
> >> model.
> >> Dan
> >>
> >>
> >> On Tue, Jun 23, 2015 at 12:24 AM, Kirill Katsnelson
> >> <kir...@sm...> wrote:
> >> > The majority of the WER comes from subs, so this part looks pretty
> >> normal.
> >> >
> >> > A lot of acoustic context--probably, depending on the definition
> of
> >> "a lot." :-) Not sure I understand this part. How can I tell? It
> >> makes sense, looking at the base dev set figures that I got training
> >> the model from the first 500 hr of the librispeech corpus (best
> range
> >> of 16-17). Which are still higher than the reference in the RESULTS
> >> for the full 1Khr corpus, which is rather in the 12-15 range.
> >> >
> >> >  -kkm
> >> >
> >> >> -----Original Message-----
> >> >> From: Daniel Povey [mailto:dp...@gm...]
> >> >> Sent: 2015-06-22 2059
> >> >> To: Kirill Katsnelson
> >> >> Cc: Nagendra Goel; kal...@li...
> >> >> Subject: Re: [Kaldi-users] LM weight
> >> >>
> >> >> Usually if there is a lot of acoustic context in your model you
> >> >> will require a larger LM weight.
> >> >> Also, if for some reason there tend to be a lot of insertions in
> >> >> decoding (e.g. something weird went wrong in training, or there
> is
> >> >> some kind of normalization problem), a large LM weight can help
> >> >> reduce insertions and so improve the WER.
> >> >>
> >> >> Dan
> >> >>
> >> >>
> >> >> On Mon, Jun 22, 2015 at 11:36 PM, Kirill Katsnelson
> >> >> <kir...@sm...> wrote:
> >> >> > I am getting the same ratio on both small and more targeted,
> and
> >> >> > a
> >> >> quite large general LM. I do not understand what to make out if
> it!
> >> >> >
> >> >> >  -kkm
> >> >> >
> >> >> >> -----Original Message-----
> >> >> >> From: Nagendra Goel [mailto:nag...@go...]
> >> >> >> Sent: 2015-06-22 2032
> >> >> >> To: Kirill Katsnelson; kal...@li...
> >> >> >> Subject: RE: [Kaldi-users] LM weight
> >> >> >>
> >> >> >> Or maybe your domain is limited and LM very nicely matched to
> >> >> >> the task at hand?
> >> >> >>
> >> >> >> -----Original Message-----
> >> >> >> From: Kirill Katsnelson
> >> [mailto:kir...@sm...]
> >> >> >> Sent: Monday, June 22, 2015 11:29 PM
> >> >> >> To: kal...@li...
> >> >> >> Subject: [Kaldi-users] LM weight
> >> >> >>
> >> >> >> I my test sets I am getting the best WER at LM/acoustic weight
> >> >> >> in
> >> >> the
> >> >> >> range of 18-19, with multiple LMs of different size and
> origin.
> >> >> >> I
> >> >> was
> >> >> >> usually thinking the usual ballpark figure about 10, give or
> >> take.
> >> >> >> From your experience, does this larger LM weight mean
> anything,
> >> >> >> and what if it does? I am guessing an inadequate acoustic
> >> >> >> model, requiring more LM "pull"--am I making sense?
> >> >> >>
> >> >> >>  -kkm
> >> >> >>
> >> >> >> --------------------------------------------------------------
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