TUTORIAL : How I trained a specific french model to control my robot


(Murugan R) #85

@karthikeyank sir. i think no need to build new LM. it will adapt for ds-lm.


(karthikeyan k) #86

so only fine tuning the acoustic model will give better results right…


(Vincent Foucault) #87

Yes.
But your words must be in the lm (it should be the case)


(karthikeyan k) #88

okay in that case, how can i add my corpus words to the existing lm. so that i can get the existing knowledge base as well as the new word’s knowledge… is there any way for that…


(Vincent Foucault) #89

Yep.
Download the complete vocabulary file of the last ds model,
Add your own sentences, build LM.


(Vincent Foucault) #90

Yep.
Download the complete vocabulary file of the last ds model,
Add your own sentences, build LM.

But, are you sure that your words aren t in the model ??

An easy way : record the needed sentences, with a good online us text to speech,
Convert it to 16k mono, and test the model…

I did it for some tests, and it works perfectly.

Hope it Will help


(karthikeyan k) #91

okay i will try. can you please share the link where i can get the vocabulary file of the last model if you know.
thanks


(karthikeyan k) #92

this is the issue am facing…! can anyone help me with this…!


(karthikeyan k) #93

hi @elpimous_robot, if you dont mind can you please explain the below lines…
--early_stop True --earlystop_nsteps 6 --estop_mean_thresh 0.1 --estop_std_thresh 0.1 --dropout_rate 0.22


(Vincent Foucault) #94

Hello.
Early stop and its params are used to limit the overfitting.
Dropout_rate too.
Perhaps could you investigate on tensorflow learning params.
Have a nice day.
Vincent


(karthikeyan k) #95

yeah … Thank you…