Sir,
I have trained a .cont model for a single speaker and I have finally reduced the word error rate to 24.9%,
but when model is used for recognition it is giving very less accuracy,
when using this model for recognition it is picking up the noise from the surrounding and the accuracy of model becomes very less, and in the FAQ it is mentioned that if any kind of noice reduction is applied on noise than the speech spectrum will be disturbed and feature extraction will be disturbed,
So sir how to deal with that noise?
And in FAQ it is also mentioned that there is a feature remove_noise in sphinx train, but I cannot find it in sphinx train, and I am using the latest version of availavble on Github.
And is there any possible way to increase the accuracy on live mic?
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Sir,
I have trained a .cont model for a single speaker and I have finally reduced the word error rate to 24.9%,
but when model is used for recognition it is giving very less accuracy,
when using this model for recognition it is picking up the noise from the surrounding and the accuracy of model becomes very less, and in the FAQ it is mentioned that if any kind of noice reduction is applied on noise than the speech spectrum will be disturbed and feature extraction will be disturbed,
So sir how to deal with that noise?
http://cmusphinx.sourceforge.net/wiki/faq
And in FAQ it is also mentioned that there is a feature remove_noise in sphinx train, but I cannot find it in sphinx train, and I am using the latest version of availavble on Github.
And is there any possible way to increase the accuracy on live mic?
Here is the log with word error rate of 24.9%
Get noise cancelling microphone
Your data is not sufficient much less than recommended by tutorial.
can i apply a noise filter for live speech instead of a noise cancelling microphone
It will not help much. Noise cancellation corrupts speech and reduces speech recognizer accuracy.