    julius

JULIUS(1)                                                            JULIUS(1)



NAME
           julius
          - open source multi-purpose LVCSR engine

SYNOPSIS
       julius [-C jconffile] [options...]

DESCRIPTION
       julius is a high-performance, multi-purpose, open-source speech
       recognition engine for researchers and developers. It is capable of
       performing almost real-time recognition of continuous speech with over
       60k-word 3-gram language model and triphone HMM model, on most current
       PCs.  julius can perform recognition on audio files, live microphone
       input, network input and feature parameter files.

       The core recognition module is implemented as C library called
       "JuliusLib". It can also be extended by plug-in facility.

   Supported Models
       julius needs a language model and an acoustic model to run as a speech
       recognizer.  julius supports the following models.

       Acoustic model
              Sub-word HMM (Hidden Markov Model) in HTK ascii format are
              supported. Phoneme models (monophone), context dependent phoneme
              models (triphone), tied-mixture and phonetic tied-mixture models
              of any unit can be used. When using context dependent models,
              inter-word context dependency is also handled. Multi-stream
              feature and MSD-HMM is also supported. You can further use a
              tool mkbinhmm to convert the ascii HMM file to a compact binary
              format for faster loading.

              Note that julius itself can only extract MFCC features from
              speech data. If you use acoustic HMM trained for other feature,
              you should give the input in HTK parameter file of the same
              feature type.

       Language model: word N-gram
              Word N-gram language model, up to 10-gram, is supported. Julius
              uses different N-gram for each pass: left-to-right 2-gram on 1st
              pass, and right-to-left N-gram on 2nd pass. It is recommended to
              use both LR 2-gram and RL N-gram for Julius. However, you can
              use only single LR N-gram or RL N-gram. In such case,
              approximated LR 2-gram computed from the given N-gram will be
              applied at the first pass.

              The Standard ARPA format is supported. In addition, a binary
              format is also supported for efficiency. The tool mkbingram(1)
              can convert ARPA format N-gram to binary format.

       Language model: grammar
              The grammar format is an original one, and tools to create a
              recognirion grammar are included in the distribution. A grammar
              consists of two files: one is a 'grammar' file that describes
              sentence structures in a BNF style, using word 'category' name
              as terminate symbols. Another is a 'voca' file that defines
              words with its pronunciations (i.e. phoneme sequences) for each
              category. They should be converted by mkdfa.pl(1) to a
              deterministic finite automaton file (.dfa) and a dictionary file
              (.dict), respectively. You can also use multiple grammars.

       Language model: isolated word
              You can perform isolated word recognition using only word
              dictionary. With this model type, Julius will perform rapid one
              pass recognition with static context handling. Silence models
              will be added at both head and tail of each word. You can also
              use multiple dictionaries in a process.

   Search Algorithm
       Recognition algorithm of julius is based on a two-pass strategy. Word
       2-gram and reverse word 3-gram is used on the respective passes. The
       entire input is processed on the first pass, and again the final
       searching process is performed again for the input, using the result of
       the first pass to narrow the search space. Specifically, the
       recognition algorithm is based on a tree-trellis heuristic search
       combined with left-to-right frame-synchronous beam search and
       right-to-left stack decoding search.

       When using context dependent phones (triphones), interword contexts are
       taken into consideration. For tied-mixture and phonetic tied-mixture
       models, high-speed acoustic likelihood calculation is possible using
       gaussian pruning.

       For more details, see the related documents.

OPTIONS
       These options specify the models, system behaviors and various search
       parameters to Julius. These option can be set at the command line, but
       it is recommended that you write them in a text file as a "jconf file",
       and specify it by "-C" option.

       Applications incorporating JuliusLib also use these options to set the
       parameters of core recognition engine. For example, a jconf file can be
       loaded to the enine by calling j_config_load_file_new() with the jconf
       file name as argument.

       Please note that relative paths in a jconf file should be relative to
       the jconf file itself, not the current working directory.

       Below are the details of all options, gathered by group.

   Julius application option
       These are application options of Julius, outside of JuliusLib. It
       contains parameters and switches for result output, character set
       conversion, log level, and module mode options. These option are
       specific to Julius, and cannot be used at applications using JuliusLib
       other than Julius.

        -outfile
          On file input, this option write the recognition result of each file
          to a separate file. The output file of an input file will be the
          same name but the suffix will be changed to ".out". (rev.4.0)

        -separatescore
          Output the language and acoustic scores separately.

        -callbackdebug
          Print the callback names at each call for debug. (rev.4.0)

        -charconv  from to
          Print with character set conversion.  from is the source character
          set used in the language model, and to is the target character set
          you want to get.

          On Linux, the arguments should be a code name. You can obtain the
          list of available code names by invoking the command "iconv --list".
          On Windows, the arguments should be a code name or codepage number.
          Code name should be one of "ansi", "mac", "oem", "utf-7", "utf-8",
          "sjis", "euc". Or you can specify any codepage number supported at
          your environment.

        -nocharconv
          Disable character conversion.

        -module  [port]
          Run Julius on "Server Module Mode". After startup, Julius waits for
          tcp/ip connection from client. Once connection is established,
          Julius start communication with the client to process incoming
          commands from the client, or to output recognition results, input
          trigger information and other system status to the client. The
          default port number is 10500.

        -record  dir
          Auto-save all input speech data into the specified directory. Each
          segmented inputs are recorded each by one. The file name of the
          recorded data is generated from system time when the input ends, in
          a style of YYYY.MMDD.HHMMSS.wav. File format is 16bit monoral WAV.
          Invalid for mfcfile input.

          With input rejection by -rejectshort, the rejected input will also
          be recorded even if they are rejected.

        -logfile  file
          Save all log output to a file instead of standard output. (Rev.4.0)

        -nolog
          Disable all log output. (Rev.4.0)

        -help
          Output help message and exit.

   Global options
       These are model-/search-dependent options relating audio input, sound
       detection, GMM, decoding algorithm, plugin facility, and others. Global
       options should be placed before any instance declaration (-AM, -LM, or
       -SR), or just after "-GLOBAL" option.

       Audio input
               -input
              {mic|rawfile|mfcfile|adinnet|stdin|netaudio|alsa|oss|esd}
                 Choose speech input source. Specify 'file' or 'rawfile' for
                 waveform file, 'htkparam' or 'mfcfile' for HTK parameter
                 file. On file input, users will be prompted to enter the file
                 name from stdin, or you can use -filelist option to specify
                 list of files to process.

                 'mic' is to get audio input from a default live microphone
                 device, and 'adinnet' means receiving waveform data via tcpip
                 network from an adinnet client. 'netaudio' is from
                 DatLink/NetAudio input, and 'stdin' means data input from
                 standard input.

                 For waveform file input, only WAV (no compression) and RAW
                 (noheader, 16bit, big endian) are supported by default. Other
                 format can be read when compiled with libsnd library. To see
                 what format is actually supported, see the help message using
                 option -help. For stdin input, only WAV and RAW is supported.
                 (default: mfcfile)

                 At Linux, you can choose API at run time by specifying alsa,
                 oss and esd.

               -chunk_size  samples
                 Audio fragment size in number of samples. (default: 1000)

               -filelist  filename
                 (With -input rawfile|mfcfile) perform recognition on all
                 files listed in the file. The file should contain input file
                 per line. Engine will end when all of the files are
                 processed.

               -notypecheck
                 By default, Julius checks the input parameter type whether it
                 matches the AM or not. This option will disable the check and
                 force engine to use the input vector as is.

               -48
                 Record input with 48kHz sampling, and down-sample it to 16kHz
                 on-the-fly. This option is valid for 16kHz model only. The
                 down-sampling routine was ported from sptk. (Rev. 4.0)

               -NA  devicename
                 Host name for DatLink server input (-input netaudio).

               -adport  port_number
                 With -input adinnet, specify adinnet port number to listen.
                 (default: 5530)

               -nostrip
                 Julius by default removes successive zero samples in input
                 speech data. This option inhibits the removal.

               -zmean ,  -nozmean
                 This option enables/disables DC offset removal of input
                 waveform. Offset will be estimated from the whole input. For
                 microphone / network input, zero mean of the first 48000
                 samples (3 seconds in 16kHz sampling) will be used for the
                 estimation. (default: disabled)

                 This option uses static offset for the channel. See also
                 -zmeansource for frame-wise offset removal.

       Speech detection by level and zero-cross
               -cutsilence ,  -nocutsilence
                 Turn on / off the speech detection by level and zero-cross.
                 Default is on for mic / adinnet input, and off for files.

               -lv  thres
                 Level threshold for speech input detection. Values should be
                 in range from 0 to 32767. (default: 2000)

               -zc  thres
                 Zero crossing threshold per second. Only input that goes over
                 the level threshold (-lv) will be counted. (default: 60)

               -headmargin  msec
                 Silence margin at the start of speech segment in
                 milliseconds. (default: 300)

               -tailmargin  msec
                 Silence margin at the end of speech segment in milliseconds.
                 (default: 400)

       Input rejection
              Two simple front-end input rejection methods are implemented,
              based on input length and average power of detected segment. The
              rejection by average power is experimental, and can be enabled
              by --enable-power-reject on compilation. Valid for MFCC feature
              with power coefficient and real-time input only.

              For GMM-based input rejection see the GMM section below.

               -rejectshort  msec
                 Reject input shorter than specified milliseconds. Search will
                 be terminated and no result will be output.

               -powerthres  thres
                 Reject the inputted segment by its average energy. If the
                 average energy of the last recognized input is below the
                 threshold, Julius will reject the input. (Rev.4.0)

                 This option is valid when --enable-power-reject is specified
                 at compilation time.

       Gaussian mixture model / GMM-VAD
              GMM will be used for input rejection by accumulated score, or
              for front-end GMM-based VAD when --enable-gmm-vad is specified.

              NOTE: You should also set the proper MFCC parameters required
              for the GMM, specifying the acoustic parameters described in AM
              section -AM_GMM.

              When GMM-based VAD is enabled, the voice activity score will be
              calculated at each frame as front-end processing. The value will
              be computed as \[ \max_{m \in M_v} p(x|m) - \max_{m \in M_n}
              p(x|m) \] where $M_v$ is a set of voice GMM, and $M_n$ is a set
              of noise GMM whose names should be specified by -gmmreject. The
              activity score will be then averaged for the last N frames,
              where N is specified by -gmmmargin. Julius updates the averaged
              activity score at each frame, and detect speech up-trigger when
              the value gets higher than a value specified by -gmmup, and
              detecgt down-trigger when it gets lower than a value of
              -gmmdown.

               -gmm  hmmdefs_file
                 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 specified by -gmmreject. The GMM should be defined
                 as one-state HMMs.

               -gmmnum  number
                 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
                 accumulated 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.

               -gmmmargin  frames
                 (GMM_VAD) Head margin in frames. When a speech trigger
                 detected by GMM, recognition will start from current frame
                 minus this value. (Rev.4.0)

                 This option will be valid only if compiled with
                 --enable-gmm-vad.

               -gmmup  value
                 (GMM_VAD) Up trigger threshold of voice activity score.
                 (Rev.4.1)

                 This option will be valid only if compiled with
                 --enable-gmm-vad.

               -gmmdown  value
                 (GMM_VAD) Down trigger threshold of voice activity score.
                 (Rev.4.1)

                 This option will be valid only if compiled with
                 --enable-gmm-vad.

       Decoding option
              Real-time processing means concurrent processing of MFCC
              computation 1st pass decoding. By default, real-time processing
              on the pass is on for microphone / adinnet / netaudio input, and
              for others.

               -realtime ,  -norealtime
                 Explicitly switch on / off real-time (pipe-line) processing
                 on the first pass. The default is off for file input, and on
                 for microphone, adinnet and NetAudio input. This option
                 relates to the way CMN and energy normalization is performed:
                 if off, they will be done using average features of whole
                 input. If on, MAP-CMN and energy normalization to do
                 real-time processing.

       Misc. options
               -C  jconffile
                 Load a jconf file at here. The content of the jconffile will
                 be expanded at this point.

               -version
                 Print version information to standard error, and exit.

               -setting
                 Print engine setting information to standard error, and exit.

               -quiet
                 Output less log. For result, only the best word sequence will
                 be printed.

               -debug
                 (For debug) output enormous internal message and debug
                 information to log.

               -check  {wchmm|trellis|triphone}
                 For debug, enter interactive check mode.

               -plugindir  dirlist
                 Specify directory to load plugin. If several direcotries
                 exist, specify them by colon-separated list.

   Instance declaration for multi decoding
       The following arguments will create a new configuration set with
       default parameters, and switch current set to it. Jconf parameters
       specified after the option will be set into the current set.

       To do multi-model decoding, these argument should be specified at the
       first of each model / search instances with different names. Any
       options before the first instance definition will be IGNORED.

       When no instance definition is found (as older version of Julius), all
       the options are assigned to a default instance named _default.

       Please note that decoding with a single LM and multiple AMs is not
       fully supported. For example, you may want to construct the jconf file
       as following.
       This type of model sharing is not supported yet, since some part of LM
       processing depends on the assigned AM. Instead, you can get the same
       result by defining the same LMs for each AM, like this:

        -AM  name
          Create a new AM configuration set, and switch current to the new
          one. You should give a unique name. (Rev.4.0)

        -LM  name
          Create a new LM configuration set, and switch current to the new
          one. You should give a unique name. (Rev.4.0)

        -SR  name am_name lm_name
          Create a new search configuration set, and switch current to the new
          one. The specified AM and LM will be assigned to it. The am_name and
          lm_name can be either name or ID number. You should give a unique
          name. (Rev.4.0)

        -AM_GMM
          When using GMM for front-end processing, you can specify
          GMM-specific acoustic parameters after this option. If you does not
          specify -AM_GMM with GMM, the GMM will share the same parameter
          vector as the last AM. The current AM will be switched to the GMM
          one, so be careful not to confuse with normal AM configurations.
          (Rev.4.0)

        -GLOBAL
          Start a global section. The global options should be placed before
          any instance declaration, or after this option on multiple model
          recognition. This can be used multiple times. (Rev.4.1)

        -nosectioncheck ,  -sectioncheck
          Disable / enable option location check in multi-model decoding. When
          enabled, the options between instance declaration is treated as
          "sections" and only the belonging option types can be written. For
          example, when an option -AM is specified, only the AM related option
          can be placed after the option until other declaration is found.
          Also, global options should be placed at top, before any instance
          declarataion. This is enabled by default. (Rev.4.1)

   Language model (-LM)
       This group contains options for model definition of each language model
       type. When using multiple LM, one instance can have only one LM.

       Only one type of LM can be specified for a LM configuration. If you
       want to use multi model, you should define them one as a new LM.

       N-gram
               -d  bingram_file
                 Use binary format N-gram. An ARPA N-gram file can be
                 converted to Julius binary format by mkbingram.

               -nlr  arpa_ngram_file
                 A forward, left-to-right N-gram language model in standard
                 ARPA format. When both a forward N-gram and backward N-gram
                 are specified, Julius uses this forward 2-gram for the 1st
                 pass, and the backward N-gram for the 2nd pass.

                 Since ARPA file often gets huge and requires a lot of time to
                 load, it may be better to convert the ARPA file to Julius
                 binary format by mkbingram. Note that if both forward and
                 backward N-gram is used for recognition, they together will
                 be converted to a single binary.

                 When only a forward N-gram is specified by this option and no
                 backward N-gram specified by -nrl, Julius performs
                 recognition with only the forward N-gram. The 1st pass will
                 use the 2-gram entry in the given N-gram, and The 2nd pass
                 will use the given N-gram, with converting forward
                 probabilities to backward probabilities by Bayes rule.
                 (Rev.4.0)

               -nrl  arpa_ngram_file
                 A backward, right-to-left N-gram language model in standard
                 ARPA format. When both a forward N-gram and backward N-gram
                 are specified, Julius uses the forward 2-gram for the 1st
                 pass, and this backward N-gram for the 2nd pass.

                 Since ARPA file often gets huge and requires a lot of time to
                 load, it may be better to convert the ARPA file to Julius
                 binary format by mkbingram. Note that if both forward and
                 backward N-gram is used for recognition, they together will
                 be converted to a single binary.

                 When only a backward N-gram is specified by this option and
                 no forward N-gram specified by -nlr, Julius performs
                 recognition with only the backward N-gram. The 1st pass will
                 use the forward 2-gram probability computed from the backward
                 2-gram using Bayes rule. The 2nd pass fully use the given
                 backward N-gram. (Rev.4.0)

               -v  dict_file
                 Word dictionary file.

               -silhead  word_string  -siltail  word_string
                 Silence word defined in the dictionary, for silences at the
                 beginning of sentence and end of sentence. (default: "<s>",
                 "</s>")

               -mapunk  word_string
                 Specify unknown word. Default is "<unk>" or "<UNK>". This
                 will be used to assign word probability on unknown words,
                 i.e. words in dictionary that are not in N-gram vocabulary.

               -iwspword
                 Add a word entry to the dictionary that should correspond to
                 inter-word pauses. This may improve recognition accuracy in
                 some language model that has no explicit inter-word pause
                 modeling. The word entry to be added can be changed by
                 -iwspentry.

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

               -sepnum  number
                 Number of high frequency words to be isolated from the
                 lexicon tree, to ease approximation error that may be caused
                 by the one-best approximation on 1st pass. (default: 150)

       Grammar
              Multiple grammars can be specified by repeating -gram and
              -gramlist. Note that this is unusual behavior from other options
              (in normal Julius option, last one will override previous ones).
              You can use -nogram to reset the grammars already specified
              before the point.

               -gram  gramprefix1[,gramprefix2[,gramprefix3,...]]
                 Comma-separated list of grammars to be used. the argument
                 should be a prefix of a grammar, i.e. if you have foo.dfa and
                 foo.dict, you should specify them with a single argument foo.
                 Multiple grammars can be specified at a time as a
                 comma-separated list.

               -gramlist  list_file
                 Specify a grammar list file that contains list of grammars to
                 be used. The list file should contain the prefixes of
                 grammars, each per line. A relative path in the list file
                 will be treated as relative to the file, not the current path
                 or configuration file.

               -dfa  dfa_file  -v  dict_file
                 An old way of specifying grammar files separately. This is
                 bogus, and should not be used any more.

               -nogram
                 Remove the current list of grammars already specified by
                 -gram, -gramlist, -dfa and -v.

       Isolated word
              Dictionary can be specified by using -w and -wlist. When you
              specify multiple times, all of them will be read at startup. You
              can use -nogram to reset the already specified dictionaries at
              that point.

               -w  dict_file
                 Word dictionary for isolated word recognition. File format is
                 the same as other LM. (Rev.4.0)

               -wlist  list_file
                 Specify a dictionary list file that contains list of
                 dictionaries to be used. The list file should contain the
                 file name of dictionaries, each per line. A relative path in
                 the list file will be treated as relative to the list file,
                 not the current path or configuration file. (Rev.4.0)

               -nogram
                 Remove the current list of dictionaries already specified by
                 -w and -wlist.

               -wsil  head_sil_model_name tail_sil_model_name sil_context_name
                 On isolated word recognition, silence models will be appended
                 to the head and tail of each word at recognition. This option
                 specifies the silence models to be appended.
                 sil_context_name is the name of the head sil model and tail
                 sil model as a context of word head phone and tail phone. For
                 example, if you specify -wsil silB silE sp, a word with phone
                 sequence b eh t will be translated as silB sp-b+eh b-eh+t
                 eh-t+sp silE. (Rev.4.0)

       User-defined LM
               -userlm
                 Declare to use user LM functions in the program. This option
                 should be specified if you use user-defined LM functions.
                 (Rev.4.0)

       Misc. LM options
               -forcedict
                 Skip error words in dictionary and force running.

   Acoustic model and feature analysis (-AM) (-AM_GMM)
       This section is about options for acoustic model, feature extraction,
       feature normalizations and spectral subtraction.

       After -AM name, an acoustic model and related specification should be
       written. You can use multiple AMs trained with different MFCC types.
       For GMM, the required parameter condition should be specified just as
       same as AMs after -AM_GMM.

       When using multiple AMs, the values of -smpPeriod, -smpFreq, -fsize and
       -fshift should be the same among all AMs.

       Acoustic HMM
               -h  hmmdef_file
                 Acoustic HMM definition file. It should be in HTK ascii
                 format, or Julius binary format. You can convert HTK ascii
                 format to Julius binary format using mkbinhmm.

               -hlist  hmmlist_file
                 HMMList file for phone mapping. This file provides mapping
                 between logical triphone names generated in the dictionary
                 and the defined HMM names in hmmdefs. This option should be
                 specified for context-dependent model.

               -tmix  number
                 Specify the number of top Gaussians to be calculated in a
                 mixture codebook. Small number will speed up the acoustic
                 computation, but AM accuracy may get worse with too small
                 value. See also -gprune. (default: 2)

               -spmodel  name
                 Specify HMM model name that corresponds to short-pause in an
                 utterance. The short-pause model name will be used in
                 recognition: short-pause skipping on grammar recognition,
                 word-end short-pause model insertion with -iwsp on N-gram, or
                 short-pause segmentation (-spsegment). (default: "sp")

               -multipath
                 Enable multi-path mode. To make decoding faster, Julius by
                 default impose a limit on HMM transitions that each model
                 should have only one transition from initial state and to end
                 state. On multi-path mode, Julius does extra handling on
                 inter-model transition to allows model-skipping transition
                 and multiple output/input transitions. Note that specifying
                 this option will make Julius a bit slower, and the larger
                 beam width may be required.

                 This function was a compilation-time option on Julius 3.x,
                 and now becomes a run-time option. By default (without this
                 option), Julius checks the transition type of specified HMMs,
                 and enable the multi-path mode if required. You can force
                 multi-path mode with this option. (rev.4.0)

               -gprune  {safe|heuristic|beam|none|default}
                 Set Gaussian pruning algorithm to use. For tied-mixture
                 model, Julius performs Gaussian pruning to reduce acoustic
                 computation, by calculating only the top N Gaussians in each
                 codebook at each frame. The default setting will be set
                 according to the model type and engine setting.  default will
                 force accepting the default setting. Set this to none to
                 disable pruning and perform full computation.  safe
                 guarantees the top N Gaussians to be computed.  heuristic and
                 beam do more aggressive computational cost reduction, but may
                 result in small loss of accuracy model (default: safe
                 (standard), beam (fast) for tied mixture model, none for non
                 tied-mixture model).

               -iwcd1  {max|avg|best number}
                 Select method to approximate inter-word triphone on the head
                 and tail of a word in the first pass.


                 max will apply the maximum likelihood of the same context
                 triphones.  avg will apply the average likelihood of the same
                 context triphones.  best number will apply the average of top
                 N-best likelihoods of the same context triphone.

                 Default is best 3 for use with N-gram, and avg for grammar
                 and word. When this AM is shared by LMs of both type, latter
                 one will be chosen.

               -iwsppenalty  float
                 Insertion penalty for word-end short pauses appended by
                 -iwsp.

               -gshmm  hmmdef_file
                 If this option is specified, Julius performs Gaussian Mixture
                 Selection for efficient decoding. The hmmdefs should be a
                 monophone model generated from an ordinary monophone HMM
                 model, using mkgshmm.

               -gsnum  number
                 On GMS, specify number of monophone states to compute
                 corresponding triphones in detail. (default: 24)

       Speech analysis
              Only MFCC feature extraction is supported in current Julius.
              Thus when recognizing a waveform input from file or microphone,
              AM must be trained by MFCC. The parameter condition should also
              be set as exactly the same as the training condition by the
              options below.

              When you give an input in HTK Parameter file, you can use any
              parameter type for AM. In this case Julius does not care about
              the type of input feature and AM, just read them as vector
              sequence and match them to the given AM. Julius only checks
              whether the parameter types are the same. If it does not work
              well, you can disable this checking by -notypecheck.

              In Julius, the parameter kind and qualifiers (as TARGETKIND in
              HTK) and the number of cepstral parameters (NUMCEPS) will be set
              automatically from the content of the AM header, so you need not
              specify them by options.

              Other parameters should be set exactly the same as training
              condition. You can also give a HTK Config file which you used to
              train AM to Julius by -htkconf. When this option is applied,
              Julius will parse the Config file and set appropriate parameter.

              You can further embed those analysis parameter settings to a
              binary HMM file using mkbinhmm.

              If options specified in several ways, they will be evaluated in
              the order below. The AM embedded parameter will be loaded first
              if any. Then, the HTK config file given by -htkconf will be
              parsed. If a value already set by AM embedded value, HTK config
              will override them. At last, the direct options will be loaded,
              which will override settings loaded before. Note that, when the
              same options are specified several times, later will override
              previous, except that -htkconf will be evaluated first as
              described above.

               -smpPeriod  period
                 Sampling period of input speech, in unit of 100 nanoseconds.
                 Sampling rate can also be specified by -smpFreq. Please note
                 that the input frequency should be set equal to the training
                 conditions of AM. (default: 625, corresponds to 16,000Hz)

                 This option corresponds to the HTK Option SOURCERATE. The
                 same value can be given to this option.

                 When using multiple AM, this value should be the same among
                 all AMs.

               -smpFreq  Hz
                 Set sampling frequency of input speech in Hz. Sampling rate
                 can also be specified using -smpPeriod. Please note that this
                 frequency should be set equal to the training conditions of
                 AM. (default: 16,000)

                 When using multiple AM, this value should be the same among
                 all AMs.

               -fsize  sample_num
                 Window size in number of samples. (default: 400)

                 This option corresponds to the HTK Option WINDOWSIZE, but
                 value should be in samples (HTK value / smpPeriod).

                 When using multiple AM, this value should be the same among
                 all AMs.

               -fshift  sample_num
                 Frame shift in number of samples. (default: 160)

                 This option corresponds to the HTK Option TARGETRATE, but
                 value should be in samples (HTK value / smpPeriod).

                 When using multiple AM, this value should be the same among
                 all AMs.

               -preemph  float
                 Pre-emphasis coefficient. (default: 0.97)

                 This option corresponds to the HTK Option PREEMCOEF. The same
                 value can be given to this option.

               -fbank  num
                 Number of filterbank channels. (default: 24)

                 This option corresponds to the HTK Option NUMCHANS. The same
                 value can be given to this option. Be aware that the default
                 value not the same as in HTK (22).

               -ceplif  num
                 Cepstral liftering coefficient. (default: 22)

                 This option corresponds to the HTK Option CEPLIFTER. The same
                 value can be given to this option.

               -rawe ,  -norawe
                 Enable/disable using raw energy before pre-emphasis (default:
                 disabled)

                 This option corresponds to the HTK Option RAWENERGY. Be aware
                 that the default value differs from HTK (enabled at HTK,
                 disabled at Julius).

               -enormal ,  -noenormal
                 Enable/disable normalizing log energy. On live input, this
                 normalization will be approximated from the average of last
                 input. (default: disabled)

                 This option corresponds to the HTK Option ENORMALISE. Be
                 aware that the default value differs from HTK (enabled at
                 HTK, disabled at Julius).

               -escale  float_scale
                 Scaling factor of log energy when normalizing log energy.
                 (default: 1.0)

                 This option corresponds to the HTK Option ESCALE. Be aware
                 that the default value differs from HTK (0.1).

               -silfloor  float
                 Energy silence floor in dB when normalizing log energy.
                 (default: 50.0)

                 This option corresponds to the HTK Option SILFLOOR.

               -delwin  frame
                 Delta window size in number of frames. (default: 2)

                 This option corresponds to the HTK Option DELTAWINDOW. The
                 same value can be given to this option.

               -accwin  frame
                 Acceleration window size in number of frames. (default: 2)

                 This option corresponds to the HTK Option ACCWINDOW. The same
                 value can be given to this option.

               -hifreq  Hz
                 Enable band-limiting for MFCC filterbank computation: set
                 upper frequency cut-off. Value of -1 will disable it.
                 (default: -1)

                 This option corresponds to the HTK Option HIFREQ. The same
                 value can be given to this option.

               -lofreq  Hz
                 Enable band-limiting for MFCC filterbank computation: set
                 lower frequency cut-off. Value of -1 will disable it.
                 (default: -1)

                 This option corresponds to the HTK Option LOFREQ. The same
                 value can be given to this option.

               -zmeanframe ,  -nozmeanframe
                 With speech input, this option enables/disables frame-wise DC
                 offset removal. This corresponds to HTK configuration
                 ZMEANSOURCE. This cannot be used together with -zmean.
                 (default: disabled)

               -usepower
                 Use power instead of magnitude on filterbank analysis.
                 (default: disabled)

       Normalization
              Julius can perform cepstral mean normalization (CMN) for inputs.
              CMN will be activated when the given AM was trained with CMN
              (i.e. has "_Z" qualifier in the header).

              The cepstral mean will be estimated in different way according
              to the input type. On file input, the mean will be computed from
              the whole input. On live input such as microphone and network
              input, the ceptral mean of the input is unknown at the start. So
              MAP-CMN will be used. On MAP-CMN, an initial mean vector will be
              applied at the beginning, and the mean vector will be smeared to
              the mean of the incrementing input vector as input goes. Options
              below can control the behavior of MAP-CMN.

               -cvn
                 Enable cepstral variance normalization. At file input, the
                 variance of whole input will be calculated and then applied.
                 At live microphone input, variance of the last input will be
                 applied. CVN is only supported for an audio input.

               -vtln  alpha lowcut hicut
                 Do frequency warping, typically for a vocal tract length
                 normalization (VTLN). Arguments are warping factor, high
                 frequency cut-off and low freq. cut-off. They correspond to
                 HTK Config values, WARPFREQ, WARPHCUTOFF and WARPLCUTOFF.

               -cmnload  file
                 Load initial cepstral mean vector from file on startup. The
                 file should be one saved by -cmnsave. Loading an initial
                 cepstral mean enables Julius to better recognize the first
                 utterance on a real-time input. When used together with
                 -cmnnoupdate, this initial value will be used for all input.

               -cmnsave  file
                 Save the calculated cepstral mean vector into file. The
                 parameters will be saved at each input end. If the output
                 file already exists, it will be overridden.

               -cmnupdate   -cmnnoupdate
                 Control whether to update the cepstral mean at each input on
                 real-time input. Disabling this and specifying -cmnload will
                 make engine to always use the loaded static initial cepstral
                 mean.

               -cmnmapweight  float
                 Specify the weight of initial cepstral mean for MAP-CMN.
                 Specify larger value to retain the initial cepstral mean for
                 a longer period, and smaller value to make the cepstral mean
                 rely more on the current input. (default: 100.0)

       Front-end processing
              Julius can perform spectral subtraction to reduce some
              stationary noise from audio input. Though it is not a powerful
              method, but it may work on some situation. Julius has two ways
              to estimate noise spectrum. One way is to assume that the first
              short segment of an speech input is noise segment, and estimate
              the noise spectrum as the average of the segment. Another way is
              to calculate average spectrum from noise-only input using other
              tool mkss, and load it in Julius. The former one is popular for
              speech file input, and latter should be used in live input. The
              options below will switch / control the behavior.

               -sscalc
                 Perform spectral subtraction using head part of each file as
                 silence part. The head part length should be specified by
                 -sscalclen. Valid only for file input. Conflict with -ssload.

               -sscalclen  msec
                 With -sscalc, specify the length of head silence for noise
                 spectrum estimation in milliseconds. (default: 300)

               -ssload  file
                 Perform spectral subtraction for speech input using
                 pre-estimated noise spectrum loaded from file. The noise
                 spectrum file can be made by mkss. Valid for all speech
                 input. Conflict with -sscalc.

               -ssalpha  float
                 Alpha coefficient of spectral subtraction for -sscalc and
                 -ssload. Noise will be subtracted stronger as this value gets
                 larger, but distortion of the resulting signal also becomes
                 remarkable. (default: 2.0)

               -ssfloor  float
                 Flooring coefficient of spectral subtraction. The spectral
                 power that goes below zero after subtraction will be
                 substituted by the source signal with this coefficient
                 multiplied. (default: 0.5)

       Misc. AM options
               -htkconf  file
                 Parse the given HTK Config file, and set corresponding
                 parameters to Julius. When using this option, the default
                 parameter values are switched from Julius defaults to HTK
                 defaults.

   Recognition process and search (-SR)
       This section contains options for search parameters on the 1st / 2nd
       pass such as beam width and LM weights, configurations for short-pause
       segmentation, switches for word lattice output and confusion network
       output, forced alignments, and other options relating recognition
       process and result output.

       Default values for beam width and LM weights will change according to
       compile-time setup of JuliusLib , AM model type, and LM size. Please
       see the startup log for the actual values.

       1st pass parameters
               -lmp  weight penalty
                 (N-gram) Language model weights and word insertion penalties
                 for the first pass.

               -penalty1  penalty
                 (Grammar) word insertion penalty for the first pass.
                 (default: 0.0)

               -b  width
                 Beam width in number of HMM nodes for rank beaming on the
                 first pass. This value defines search width on the 1st pass,
                 and has dominant 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 will
                 grow in proportion to the width.

                 The default value is dependent on acoustic model type: 400
                 (monophone), 800 (triphone), or 1000 (triphone, setup=v2.1)

               -nlimit  num
                 Upper limit of token per node. This option is valid when
                 --enable-wpair and --enable-wpair-nlimit are enabled at
                 compilation time.

               -progout
                 Enable progressive output of the partial results on the first
                 pass.

               -proginterval  msec
                 Set the time interval for -progout in milliseconds. (default:
                 300)

       2nd pass parameters
               -lmp2  weight penalty
                 (N-gram) Language model weights and word insertion penalties
                 for the second pass.

               -penalty2  penalty
                 (Grammar) word insertion penalty for the second pass.
                 (default: 0.0)

               -b2  width
                 Envelope beam width (number of hypothesis) at the second
                 pass. If the count of word expansion at a certain hypothesis
                 length reaches this limit while search, shorter hypotheses
                 are not expanded further. This prevents search to fall in
                 breadth-first-like situation stacking on the same position,
                 and improve search failure mostly for large vocabulary
                 condition. (default: 30)

               -sb  float
                 Score envelope width for enveloped scoring. When calculating
                 hypothesis score for each generated hypothesis, its trellis
                 expansion and Viterbi operation will be pruned in the middle
                 of the speech if score on a frame goes under the width.
                 Giving small value makes the second pass faster, but
                 computation error may occur. (default: 80.0)

               -s  num
                 Stack size, i.e. the maximum number of hypothesis that can be
                 stored on the stack during the search. A larger value may
                 give more stable results, but increases the amount of memory
                 required. (default: 500)

               -m  count
                 Number of expanded hypotheses required to discontinue the
                 search. If the number of expanded hypotheses is greater then
                 this threshold then, the search is discontinued at that
                 point. The larger this value is, The longer Julius gets to
                 give up search. (default: 2000)

               -n  num
                 The number of candidates Julius tries to find. The search
                 continues till this number of sentence hypotheses have been
                 found. The obtained sentence hypotheses are sorted by score,
                 and final result is displayed in the order (see also the
                 -output). The possibility that the optimum hypothesis is
                 correctly found increases as this value gets increased, but
                 the processing time also becomes longer. The default value
                 depends on the engine setup on compilation time: 10
                 (standard) or 1 (fast or v2.1)

               -output  num
                 The top N sentence hypothesis to be output at the end of
                 search. Use with -n (default: 1)

               -lookuprange  frame
                 Set the number of frames before and after to look up next
                 word hypotheses in the word trellis on the second pass. This
                 prevents the omission of short words, but with a large value,
                 the number of expanded hypotheses increases and system
                 becomes slow. (default: 5)

               -looktrellis
                 (Grammar) Expand only the words survived on the first pass
                 instead of expanding all the words predicted by grammar. This
                 option makes second pass decoding faster especially for large
                 vocabulary condition, but may increase deletion error of
                 short words. (default: disabled)

       Short-pause segmentation / decoder-VAD
              When compiled with --enable-decoder-vad, the short-pause
              segmentation will be extended to support decoder-based VAD.

               -spsegment
                 Enable short-pause segmentation mode. Input will be segmented
                 when a short pause word (word with only silence model in
                 pronunciation) gets the highest likelihood at certain
                 successive frames on the first pass. When detected segment
                 end, Julius stop the 1st pass at the point, perform 2nd pass,
                 and continue with next segment. The word context will be
                 considered among segments. (Rev.4.0)

                 When compiled with --enable-decoder-vad, this option enables
                 decoder-based VAD, to skip long silence.

               -spdur  frame
                 Short pause duration length to detect end of input segment,
                 in number of frames. (default: 10)

               -pausemodels  string
                 A comma-separated list of pause model names to be used at
                 short-pause segmentation. The word whose pronunciation
                 consists of only the pause models will be treated as "pause
                 word" and used for pause detection. If not specified, name of
                 -spmodel, -silhead and -siltail will be used. (Rev.4.0)

               -spmargin  frame
                 Back step margin at trigger up for decoder-based VAD. When
                 speech up-trigger found by decoder-VAD, Julius will rewind
                 the input parameter by this value, and start recognition at
                 the point. (Rev.4.0)

                 This option will be valid only if compiled with
                 --enable-decoder-vad.

               -spdelay  frame
                 Trigger decision delay frame at trigger up for decoder-based
                 VAD. (Rev.4.0)

                 This option will be valid only if compiled with
                 --enable-decoder-vad.

       Word lattice / confusion network output
               -lattice ,  -nolattice
                 Enable / disable generation of word graph. Search algorithm
                 also has changed to optimize for better word graph
                 generation, so the sentence result may not be the same as
                 normal N-best recognition. (Rev.4.0)

               -confnet ,  -noconfnet
                 Enable / disable generation of confusion network. Enabling
                 this will also activates -lattice internally. (Rev.4.0)

               -graphrange  frame
                 Merge same words at neighbor position at graph generation. If
                 the beginning time and ending time of two word candidates of
                 the same word is within the specified range, they will be
                 merged. The default is 0 (allow merging same words on exactly
                 the same location) and specifying larger value will result in
                 smaller graph output. Setting this value to -1 will disable
                 merging, in that case same words on the same location of
                 different scores will be left as they are. (default: 0)

               -graphcut  depth
                 Cut the resulting graph by its word depth at post-processing
                 stage. The depth value is the number of words to be allowed
                 at a frame. Setting to -1 disables this feature. (default:
                 80)

               -graphboundloop  count
                 Limit the number of boundary adjustment loop at
                 post-processing stage. This parameter prevents Julius from
                 blocking by infinite adjustment loop by short word
                 oscillation. (default: 20)

               -graphsearchdelay ,  -nographsearchdelay
                 When this option is enabled, Julius modifies its graph
                 generation algorithm on the 2nd pass not to terminate search
                 by graph merging, until the first sentence candidate is
                 found. This option may improve graph accuracy, especially
                 when you are going to generate a huge word graph by setting
                 broad search. Namely, it may result in better graph accuracy
                 when you set wide beams on both 1st pass -b and 2nd pass -b2,
                 and large number for -n. (default: disabled)

       Multi-gram / multi-dic recognition
               -multigramout ,  -nomultigramout
                 On grammar recognition using multiple grammars, Julius will
                 output only the best result among all grammars. Enabling this
                 option will make Julius to output result for each grammar.
                 (default: disabled)

       Forced alignment
               -walign
                 Do viterbi alignment per word units for the recognition
                 result. The word boundary frames and the average acoustic
                 scores per frame will be calculated.

               -palign
                 Do viterbi alignment per phone units for the recognition
                 result. The phone boundary frames and the average acoustic
                 scores per frame will be calculated.

               -salign
                 Do viterbi alignment per state for the recognition result.
                 The state boundary frames and the average acoustic scores per
                 frame will be calculated.

       Misc. search options
               -inactive
                 Start this recognition process instance with inactive state.
                 (Rev.4.0)

               -1pass
                 Perform only the first pass.

               -fallback1pass
                 When 2nd pass fails, Julius finish the recognition with no
                 result. This option tell Julius to output the 1st pass result
                 as a final result when the 2nd pass fails. Note that some
                 score output (confidence etc.) may not be useful. This was
                 the default behavior of Julius-3.x.

               -no_ccd ,  -force_ccd
                 Explicitly switch phone context handling at search. Normally
                 Julius determines whether the using AM is a context-dependent
                 model or not from the model names, i.e., whether the names
                 contain character + and -. This option will override the
                 automatic detection.

               -cmalpha  float
                 Smoothing parameter for confidence scoring. (default: 0.05)

               -iwsp
                 (Multi-path mode only) Enable inter-word context-free short
                 pause insertion. This option appends a skippable short pause
                 model for every word end. The short-pause model can be
                 specified by -spmodel.

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

               -demo
                 Equivalent to -progout -quiet.

ENVIRONMENT VARIABLES
        ALSADEV
          (using mic input with alsa device) specify a capture device name. If
          not specified, "default" will be used.

        AUDIODEV
          (using mic input with oss device) specify a capture device path. If
          not specified, "/dev/dsp" will be used.

        LATENCY_MSEC
          Try to set input latency of microphone input in milliseconds.
          Smaller value will shorten latency but sometimes make process
          unstable. Default value will depend on the running OS.

EXAMPLES
       For examples of system usage, refer to the tutorial section in the
       Julius documents.

NOTICE
       Note about jconf files: relative paths in a jconf file are interpreted
       as relative to the jconf file itself, not to the current directory.

SEE ALSO
       julian(1), jcontrol(1), adinrec(1), adintool(1), mkbingram(1),
       mkbinhmm(1), mkgsmm(1), wav2mfcc(1), mkss(1)

       http://julius.sourceforge.jp/en/

DIAGNOSTICS
       Julius normally will return the exit status 0. If an error occurs,
       Julius exits abnormally with exit status 1. If an input file cannot be
       found or cannot be loaded for some reason then Julius will skip
       processing for that file.

BUGS
       There are some restrictions to the type and size of the models Julius
       can use. For a detailed explanation refer to the Julius documentation.
       For bug-reports, inquires and comments please contact julius-info at
       lists.sourceforge.jp.

COPYRIGHT
       Copyright (c) 1991-2008 Kawahara Lab., Kyoto University

       Copyright (c) 1997-2000 Information-technology Promotion Agency, Japan

       Copyright (c) 2000-2008 Shikano Lab., Nara Institute of Science and
       Technology

       Copyright (c) 2005-2008 Julius project team, Nagoya Institute of
       Technology

AUTHORS
       Rev.1.0 (1998/02/20)
          Designed by Tatsuya KAWAHARA and Akinobu LEE (Kyoto University)

          Development by Akinobu LEE (Kyoto University)

       Rev.1.1 (1998/04/14), Rev.1.2 (1998/10/31), Rev.2.0 (1999/02/20),
       Rev.2.1 (1999/04/20), Rev.2.2 (1999/10/04), Rev.3.0 (2000/02/14),
       Rev.3.1 (2000/05/11)
          Development of above versions by Akinobu LEE (Kyoto University)

       Rev.3.2 (2001/08/15), Rev.3.3 (2002/09/11), Rev.3.4 (2003/10/01),
       Rev.3.4.1 (2004/02/25), Rev.3.4.2 (2004/04/30)
          Development of above versions by Akinobu LEE (Nara Institute of
          Science and Technology)

       Rev.3.5 (2005/11/11), Rev.3.5.1 (2006/03/31), Rev.3.5.2 (2006/07/31),
       Rev.3.5.3 (2006/12/29), Rev.4.0 (2007/12/19), Rev.4.1 (2008/10/03)
          Development of above versions by Akinobu LEE (Nagoya Institute of
          Technology)

THANKS TO
       From rev.3.2, Julius is released by the "Information Processing
       Society, Continuous Speech Consortium".

       The Windows DLL version was developed and released by Hideki BANNO
       (Nagoya University).

       The Windows Microsoft Speech API compatible version was developed by
       Takashi SUMIYOSHI (Kyoto University).



                                  02/11/2009                         JULIUS(1)
