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POCKETSPHINX_BATCH(1)					 POCKETSPHINX_BATCH(1)

NAME
       pocketsphinx_batch - Run speech recognition in batch mode

SYNOPSIS
       pocketsphinx_batch -hmm hmmdir -dict dictfile [ options ]...

DESCRIPTION
       Run  speech recognition over a list of utterances in batchmode.	A list
       of arguments follows:

       -adcdev
	      name for audio input (platform-specific)

       -adchdr
	      Size of audio file header in bytes (headers are ignored)

       -adcin Input is raw audio data

       -agc   Automatic gain  control  for  c0	('max',	 'emax',  'noise',  or
	      'none')

       -agcthresh
	      Initial threshold for automatic gain control

       -allphone
	      Do phoneme recognition

       -alpha Preemphasis parameter

       -backtrace
	      Print back trace of recognition results

       -beam  Beam  width  applied  to	every frame in Viterbi search (smaller
	      values mean wider beam)

       -bestpath
	      Run bestpath (Dijkstra) search over word lattice (3rd pass)

       -bestpathlw
	      Language model probability weight for bestpath search

       -cachesen
	      Cache senone scores from first pass search

       -cep2spec
	      Input is cepstral files, output is log spectral files

       -cepdir
	      files directory (prefixed to filespecs in control file)

       -cepext
	      Input files extension (prefixed to filespecs in control file)

       -ceplen
	      Number of components in the input feature vector

       -cmn   Cepstral	mean  normalization  scheme  ('current',  'prior',  or
	      'none')

       -cmninit
	      Initial  values (comma-separated) for cepstral mean when 'prior'
	      is used

       -compallsen
	      Compute all senone scores in every frame	(can  be  faster  when
	      there are many senones)

       -ctl   file listing utterances to be processed

       -ctlcount
	      No.  of  utterances  to  be processed (after skipping -ctloffset
	      entries)

       -ctlincr
	      Do every Nth line in the control file

       -ctloffset
	      No. of utterances at the beginning of -ctl file to be skipped

       -dict  pronunciation dictionary (lexicon) input file

       -dither
	      Add 1/2-bit noise

       -doublebw
	      Use double bandwidth filters (same center freq)

       -dsratio
	      Frame GMM computation downsampling ratio

       -fbtype
	      FB Type of mel_scale or log_linear

       -fdict word pronunciation dictionary input file

       -feat  Feature stream type, depends on the acoustic model

       -fillpen
	      Filler word transition penalty

       -frate Frame rate

       -fsg   state grammar

       -fsgbfs
	      Force backtrace from FSG final state

       -fsgctlfn
	      finite state grammar control file

       -fsgusealtpron
	      Use alternative pronunciations for FSG

       -fsgusefiller
	      (FSG Mode (Mode 2) only) Insert filler words at each state.

       -fwd3g Use trigrams in first pass search

       -fwdflat
	      Run forward flat-lexicon search over word lattice (2nd pass)

       -fwdflatbeam
	      Beam width applied to every frame in second-pass flat search

       -fwdflatefwid
	      Minimum number of end frames for a word to be searched  in  fwd‐
	      flat search

       -fwdflatlw
	      Language	model  probability  weight for flat lexicon (2nd pass)
	      decoding

       -fwdflatsfwin
	      Window of frames in lattice to search  for  successor  words  in
	      fwdflat search

       -fwdflatwbeam
	      Beam width applied to word exits in second-pass flat search

       -fwdtree
	      Run forward lexicon-tree search (1st pass)

       -hmm   containing acoustic model files.

       -hyp   output file name

       -hypseg
	      output with segmentation file name

       -input_endian
	      Endianness  of  input data, big or little, ignored if NIST or MS
	      Wav

       -kdmaxbbi
	      Maximum number of Gaussians per leaf node in kd-Trees

       -kdmaxdepth
	      Maximum depth of kd-Trees to use

       -kdtree
	      file for Gaussian selection

       -latsize
	      Lattice size

       -lifter
	      Length of sin-curve for liftering, or 0 for no liftering.

       -live  Get input from audio hardware

       -lm    trigram language model input file

       -lmctl a set of language model

       The -hmm and -dict arguments are always required.  Either -lm  or  -fsg
       is  required, depending on whether you are using a statistical language
       model or a finite-state grammar.	 To do batchmode recognition, you will
       need  to	 specify a control file, using -ctl This is a simple text file
       containing one entry per line.  Each entry is the name of an input file
       relative	 to  the -cepdir directory, and without the filename extension
       (which is given in the -cepext argument).

       If you are using acoustic feature files as input (see sphinx_fe(1)  for
       information  on	how to generate these), you can also specify a subpart
       of a file, using the following format:

	      FILENAME START-FRAME END-FRAME UTTERANCE-ID

AUTHOR
       Written by numerous people at CMU from 1994 onwards.  This manual  page
       by David Huggins-Daines <dhuggins@cs.cmu.edu>

COPYRIGHT
       Copyright © 1994-2007 Carnegie Mellon University.  See the file COPYING
       included with this package for more information.

SEE ALSO
       pocketsphinx_continuous(1), sphinx_fe(1).

				  2007-08-27		 POCKETSPHINX_BATCH(1)
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