(no subject)

[akshat dashore]

while creating decoder i.e

config.set_string('-hmm', path.join(MODELDIR, 'en-us/en-us'))
config.set_string('-lm', path.join(MODELDIR, 'en-us/en-us.lm.bin'))
config.set_string('-dict', path.join(MODELDIR, 'en-us/cmudict-en-us.dict'))

i understood files for -lm and -dict but for -hmm i have 9 files i.e feat.params,feature_transform,mdef,means,mixture_weights,noisedict,noisedict.save,transition_matrices,variances which one to pass till now i didn't found accurate results for hyp().hypstr i.e i got none value

here is my code

from os import environ, path
from pocketsphinx.pocketsphinx import *
from sphinxbase.sphinxbase import *

MODELDIR = "/home/user/scribe/model/"
DATADIR = "/home/user/scribe/pocketsphinx/test/data/"

config = Decoder.default_config()
config.set_string('-hmm', path.join(MODELDIR, 'hmm'))
config.set_string('-lm', path.join(MODELDIR, 'lm/en-us.lm.bin'))
config.set_string('-dict', path.join(MODELDIR, 'dict/cmu07a.dic'))

decoder = Decoder(config)

print("value of decoder",decoder)

print ("Pronunciation for word 'hello' is ", decoder.lookup_word("hello"))
print ("Pronunciation for word 'abcdf' is ", decoder.lookup_word("abcdf"))

decoder.start_utt()
stream = open(path.join(DATADIR, 'goforward.raw'), 'rb')

while True:
buf = stream.read(1024)
if buf:
decoder.process_raw(buf, False, False)
else:
break
decoder.end_utt()

hypothesis = decoder.hyp()
logmath = decoder.get_logmath()
print ('Best hypothesis: ', hypothesis.hypstr, " model score: ", hypothesis.best_score, " confidence: ", logmath.exp(hypothesis.prob))

[sheharyar masood]

Hi,
brother I have an issue. That I am confused about sphinx_lm_convert I
want to convert .lm to .dmp! but it do not recognises the command please
tell me I am stuck here for a long time! thanks....

On Wed, 12 Sep 2018, 1:21 pm akshat dashore, akshat@users.sourceforge.net
wrote:

while creating decoder i.e

config.set_string('-hmm', path.join(MODELDIR, 'en-us/en-us'))
config.set_string('-lm', path.join(MODELDIR, 'en-us/en-us.lm.bin'))
config.set_string('-dict', path.join(MODELDIR, 'en-us/cmudict-en-us.dict'))

i understood files for -lm and -dict but for -hmm i have 9 files i.e
feat.params,feature_transform,mdef,means,mixture_weights,noisedict,noisedict.save,transition_matrices,variances
which one to pass till now i didn't found accurate results for hyp().hypstr
i.e i got none value

here is my code

from os import environ, path
from pocketsphinx.pocketsphinx import *
from sphinxbase.sphinxbase import *

MODELDIR = "/home/user/scribe/model/"
DATADIR = "/home/user/scribe/pocketsphinx/test/data/"

config = Decoder.default_config()
config.set_string('-hmm', path.join(MODELDIR, 'hmm'))
config.set_string('-lm', path.join(MODELDIR, 'lm/en-us.lm.bin'))
config.set_string('-dict', path.join(MODELDIR, 'dict/cmu07a.dic'))

decoder = Decoder(config)

print("value of decoder",decoder)

print ("Pronunciation for word 'hello' is ", decoder.lookup_word("hello"))
print ("Pronunciation for word 'abcdf' is ", decoder.lookup_word("abcdf"))

decoder.start_utt()
stream = open(path.join(DATADIR, 'goforward.raw'), 'rb')

while True:
buf = stream.read(1024)
if buf:
decoder.process_raw(buf, False, False)
else:
break
decoder.end_utt()

hypothesis = decoder.hyp()
logmath = decoder.get_logmath()
print ('Best hypothesis: ', hypothesis.hypstr, " model score: ",
hypothesis.best_score, " confidence: ", logmath.exp(hypothesis.prob))

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[akshat dashore]

i resolved the issue by the way thanks lets close the discussion

[akshat dashore]

@sheharyar send me the link of model you downloaded

[sheharyar masood]

Hi Akshat,
Actually, I had created it by LMTool, right now I have file available, which is here.... If link is necessary then please tell me I will do something.....

[sheharyar masood]

Hi Akshat,
Actually, I had created it by LMTool, right now I have
file available, which is here.... If link is necessary then please tell me
I will do something.....

On Thu, 13 Sep 2018, 11:52 am akshat dashore, akshat@users.sourceforge.net
wrote:

@sheharyar send me the link of model you downloaded

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