Re: [Kaldi-users] LM weight

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

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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