Re: [Kaldi-users] LM weight

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

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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