The offline grammar compiler contains advanced parameters
that are used for language model building.
The advanced SLM parameters listed below are complex
parameters that are best understood by speech language specialists.
These are advanced parameters that require a deep understanding of
statistical language models and cannot be easily explained by themselves.
Specify the following advanced SLM parameters:
- -ngramlength <positive integer value>
- Specify the maximum length of n-grams to count when processing
the sentence input. The default is 3. Usually
this value is 2 or 3,
rarely 4. This field reflects the size of the
training data to generate when building the model. The -ngramlength must
be greater than or equal to -ngramorder.
- -ngramorder <positive integer value>
- Specify the order of the n-gram model, which is the maximum length
of n-grams to build into the model from the training data. The default
is 3; rarely should this value be 4.
This field reflects the size of the model; a higher value typically
means higher accuracy. The -ngramlength must
be greater than or equal to -ngramorder.
- -ngramcutoffs <string>
- Specify the cutoffs, which is a string containing thresholds for
each n-gram level separated by commas; no spaces are allowed. Cutoffs
represent the maximum count that is removed, to reduce the size of
the generated model. The number of cutoffs must match the -ngramorder,
i.e. if you use 3, then you need to specify
3 values, such as 1,1,1 for (unigram,
bigram, trigram).
Note: Specify the threshold parameter
to control the size of the language model. If all information in the
training data is contained in the model (i.e., no thresholds applied),
the model size can be prohibitively large for the targeted application,
for example, because of memory or CPU limitations. In such situations,
the thresholds can be used selectively to remove the information about
infrequent events from the model. The higher the value of each threshold,
the smaller the model will be. The values have to be increased with
caution, if they become too high, it may happen that there will not
be enough training data available and the attempt to build the model
will end in an error.
- -contextsize < positive integer value or zero>
- Specify how many cross word phones should be considered. A value
greater than 1 (up to 4)
slows the compilation time significantly, but may provide a small
increase in recognition accuracy. This field is used to mostly determine
compilation time. The default is 1.
- -insertioncost <positive float value or zero>
- Specify the cost of a word insertion. The value can be set from 0.0 to +inf.
The value of 0 corresponds to the highest probability
of word insertion; increasing this value will cause fewer but longer
words to be considered in the model. The default is 0.0.
- -silenceloglikelihood <negative float value or zero>
- Specify the Log likelihood of silence. The value can be set from 0 to -inf.
The value of 0 corresponds to the highest log-likelihood
of silence insertion. The default is -0.6.