My scenario is i have maximum 20-30 words. and i expect a sentence in its
exact same order. so can say , expect one word at a time. So do you have any
advice to increase the accuracy by changing the parameters or number of hmms
or method of searching?
Change the dictionary to only have those 20-30 words, and generate a new
language model from the sentences that you expect. Also, instead of a
statistical LM, you could also use a rule-based LM, though I don't know if
pocketSphinx specifically supports that.
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Anonymous
-
2011-07-03
Youy can use JSGF grammars by passing the -jsgf command line arg. See the
cmdln_macro.h source file. I use the the W3C docs for grammar docs http://www.w3.org/TR/jsgf/
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Hi all
thanks for the links and advices, especially to Anuj
it seems like the pocket sphinx is doing a great recognition. But i am facing
a new problem now. The recognition accuracy for female sounds and children
sounds are not great with respect to the accuracy for male voices, is there
special HMMs available for women and children voice?
Thanks in advance for the replays.
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Change the dictionary to only have those 20-30 words, and generate a new
language model from the sentences that you expect. Also, instead of a
statistical LM, you could also use a rule-based LM, though I don't know if
pocketSphinx specifically supports that.
Youy can use JSGF grammars by passing the -jsgf command line arg. See the
cmdln_macro.h source file. I use the the W3C docs for grammar docs
http://www.w3.org/TR/jsgf/
Hi all
thanks for the links and advices, especially to Anuj
it seems like the pocket sphinx is doing a great recognition. But i am facing
a new problem now. The recognition accuracy for female sounds and children
sounds are not great with respect to the accuracy for male voices, is there
special HMMs available for women and children voice?
Thanks in advance for the replays.
You can adapt existing acoustic model to improve accuracy. See
http://cmusphinx.sourceforge.net/wiki/tutorialadapt