julius.txt

about sound recognition.i want to downlod

              larger,  but  distortion  of  the  resulting signal also becomes
              remarkable.  (default: 2.0)

       -ssfloor value
              Flooring coefficient  of  spectral  subtraction.   The  spectral
              parameters  that go under zero after subtraction will be substi-
              tuted by the source signal  with  this  coefficient  multiplied.
              (default: 0.5)

   GMM-based Input Verification and Rejection
       -gmm filename
              GMM definition file in HTK format. If specified, GMM-based input
              verification will be performed concurrently with the  1st  pass,
              and  you  can reject the input according to the result as speci-
              fied by "-gmmreject".  Note that the GMM should  be  defined  as
              one-state  HMMs, and their training parameter should be the same
              as the acoustic model you want to use with.

       -gmmnum N
              Number of Gaussian components to be computed per  frame  on  GMM
              calculation.   Only  the  N-best  Gaussians will be computed for
              rapid calculation.  The default is  10  and  specifying  smaller
              value  will  speed up GMM calculation, but too small value (1 or
              2) may cause degradation of identification performance.

       -gmmreject string
              Comma-separated list of GMM names  to  be  rejected  as  invalid
              input.   When  recognition,  the log likelihoods of GMMs accumu-
              lated for the entire input will be  computed  concurrently  with
              the  1st  pass.   If the GMM name of the maximum score is within
              this string, the 2nd pass will not be  executed  and  the  input
              will be rejected.

   Language Model (word N-gram)
       -nlr 2gram_filename
              2-gram language model file in standard ARPA format.

       -nrl rev_3gram_filename
              Reverse  3-gram  language  model file.  This is required for the
              second search pass.  If this is not defined then only the  first
              pass will take place.

       -d bingram_filename
              Use  binary  format language model instead of ARPA formats.  The
              2-gram and 3-gram model can be combined and  converted  to  this
              binary format using mkbingram.  Julius can read this format much
              faster than ARPA format.

       -lmp lm_weight lm_penalty

       -lmp2 lm_weight2 lm_penalty2
              Language model score weights and word  insertion  penalties  for
              the first and second passes respectively.

              The hypothesis language scores are scaled as shown below:

              lm_score1  =  lm_weight  * 2-gram_score + lm_penalty lm_score2 =
              lm_weight2 * 3-gram_score + lm_penalty2

              The defaults are dependent on acoustic model:

                First-Pass | Second-Pass
               --------------------------
                5.0 -1.0   |  6.0  0.0 (monophone)
                8.0 -2.0   |  8.0 -2.0 (triphone,PTM)
                9.0  8.0   | 11.0 -2.0 (triphone,PTM, setup=v2.1)

       -transp float
              Additional insertion penalty for  transparent  words.  (default:
              0.0)

   Word Dictionary
       -v dictionary_file
              Word dictionary file (required).

       -silhead {WORD|WORD[OUTSYM]|#num}

       -siltail {WORD|WORD[OUTSYM]|#num}
              Sentence  start  and  end silence word as defined in the dictio-
              nary.  (default: "<s>" / "</s>")

              Julius deal these words as  fixed  start-word  and  end-word  of
              recognition.   They  can  be defined in several formats as shown
              below.


                                       Example
           Word_name                     <s>
           Word_name[output_symbol]   <s>[silB]
           #Word_ID                      #14

            (Word_ID is the word position in the dictionary
             file starting from 0)

       -forcedict
              Ignore dictionary errors and force running.  Words  with  errors
              will be dropped from dictionary at startup.

   Acoustic Model (HMM)
       -h hmmfilename
              HMM definition file to use.  Format (ascii/binary) will be auto-
              matically detected. (required)

       -hlist HMMlistfilename
              HMMList file to use.  Required when using triphone  based  HMMs.
              This file provides a mapping between the logical triphones names
              genertated from phone sequence in the  dictionary  and  the  HMM
              definition names.

       -iwcd1 {best N|max|avg}
              When  using a triphone model, select method to handle inter-word
              triphone context on the first and last phone of a  word  in  the
              first pass.

              best N: use average likelihood of N-best scores from the same
                      context triphones (default, N=3)
              max: use maximum likelihood of the same
                   context triphones
              avg: use average likelihood of the same
                   context triphones

       -force_ccd / -no_ccd
              Normally  Julius determines whether the specified acoustic model
              is a context-dependent model from the model names, i.e., whether
              the  model names contain character '+' and '-'.  You can explic-
              itly specify by these options  to  avoid  mis-detection.   These
              will override the automatic detection result.

       -notypecheck
              Disable checking of input parameter type. (default: enabled)

   Acoustic Computation
       Gaussian  Pruning will be automatically enabled when using tied-mixture
       based acoutic model.  It is disabled by default  for  non  tied-mixture
       models,  but  you  can  activate  pruning to those models by explicitly
       specifying "-gprune".  Gaussian Selection needs a monophone model  con-
       verted by mkgshmm.

       -gprune {safe|heuristic|beam|none}
              Set the Gaussian pruning technique to use.
              (default:  'safe' (setup=standard), 'beam' (setup=fast) for tied
              mixture model, 'none' for non tied-mixture model)

       -tmix K
              With Gaussian Pruning, specify the number of Gaussians  to  com-
              pute  per  mixture  codebook. Small value will speed up computa-
              tion, but likelihood error will grow larger. (default: 2)

       -gshmm hmmdefs
              Specify monophone hmmdefs to use for Gaussian Mixture  Selectio.
              Monophone  model for GMS is generated from an ordinary monophone
              HMM model using mkgshmm.  This option is  disabled  by  default.
              (no GMS applied)

       -gsnum N
              When using GMS, specify number of monophone state to select from
              whole monophone states. (default: 24)

   Inter-word Short Pause Handling
       -iwspword
              Add a word entry to the dictionary  that  should  correspond  to
              inter-word  short  pauses  that may occur in input speech.  This
              may improve recognition accuracy in some language model that has
              no  inter-word  pause modeling.  The word entry can be specified
              by "-iwspentry".

       -iwspentry
              Specify the word  entry  that  will  be  added  by  "-iwspword".
              (default: "<UNK> [sp] sp sp")

       -iwsp  (Multi-path  version  only) Enable inter-word context-free short
              pause handling.  This option appends  a  skippable  short  pause
              model  for  every  word end.  The added model will be skipped on
              inter-word context handling.  The HMM model to be  appended  can
              be specified by "-spmodel" option.

       -spmodel
              Specify  short-pause  model  name  that will be used in "-iwsp".
              (default: "sp")

   Short-pause Segmentation
       The short pause segmentation can be used for sucessive  decoding  of  a
       long utterance.  Enabled when compiled with '--enable-sp-segment'.

       -spdur Set  the short-pause duration threshold in number of frames.  If
              a short-pause word has  the  maximum  likelihood  in  successive
              frames longer than this value, then interrupt the first pass and
              start the second pass. (default: 10)

   Search Parameters (First Pass)
       -b beamwidth
              Beam width (number of HMM nodes) on the first pass.  This  value
              defines  search  width  on the 1st pass, and has great effect on
              the total processing time.  Smaller  width  will  speed  up  the
              decoding,  but  too  small  value  will  result in a substantial
              increase of recognition errors due to  search  failure.   Larger
              value  will make the search stable and will lead to failure-free
              search, but processing time and memory usage will grow  in  pro-
              portion to the width.

              Default value is acoustic model dependent:
                400 (monophone)
                800 (triphone,PTM)
               1000 (triphone,PTM, setup=v2.1)

       -sepnum N
              Number  of high frequency words to be separated from the lexicon
              tree. (default: 150)

       -1pass Only perform the first pass search.  This mode is  automatically
              set when no 3-gram language model has been specified (-nlr).

       -realtime

       -norealtime
              Explicitly  specify whether real-time (pipeline) processing will
              be done in the first pass or not.  For file input,  the  default
              is  OFF  (-norealtime),  for  microphone,  adinnet  and NetAudio
              input, the default is ON (-realtime).  This  option  relates  to
              the  way  CMN is performed: when OFF, CMN is calculated for each
              input using cepstral mean of the whole input.  When the realtime
              option is ON, MAP-CMN will be performed.  When MAP-CMN, the cep-
              stral mean of last 5 seconds are used as  the  initial  cepstral
              mean  at the beginning of each input.  Also refer to "-progout".

       -cmnsave filename
              Save last CMN parameters computed while recognition to the spec-
              ified  file.   The  parameters will be saved to the file in each
              time a input is recognized, so the output file always keeps  the
              last  CMN  parameters.  If output file already exist, it will be
              overridden.

       -cmnload filename
              Load initial CMN parameters previously saved in a file by "-cmn-
              save".   Loading  an initial CMN enables Julius to better recog-
              nize the first utterance on a microphone / network input.   Also
              see "-cmnnoupdate".

       -cmnmapweight
              Specify weight of initial cepstral mean at the beginning of each
              utterance for microphone / network input.  Specify larger  value
              to  retain  the  initial  cepstral mean for a longer period, and
              smaller value to rely more  on  the  current  input.   (default:
              100.0)

       -cmnnoupdate
              When microphone / network input, this option makes engine not to
              update the cepstral mean at each input and force engine  to  use
              the initial cepstral mean given by "-cmnload" parmanently.

   Search Parameters (Second Pass)
       -b2 hyponum
              Beam  width (number of hypothesis) in second pass.  If the count
              of word expantion at a certain length of hypothesis reaches this
              limit while search, shorter hypotheses are not expanded further.
              This prevents search to fall in breadth-first-like status stack-
              ing on the same position, and improve search failure.  (default:
              30)