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PROGRAM:

NAME


pocketsphinx_continuous - Run speech recognition in continuous listening mode

SYNOPSIS


pocketsphinx_continuous -hmm hmmdir -dict dictfile [ options ]...

DESCRIPTION


This program opens the audio device and waits for speech. When it detects an utterance,
it performs speech recognition on it.

-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
phoneme decoding with phonetic lm

-allphone_ci
Perform phoneme decoding with phonetic lm and context-independent units only

-alpha Preemphasis parameter

-argfile
file giving extra arguments.

-ascale
Inverse of acoustic model scale for confidence score calculation

-aw Inverse weight applied to acoustic scores.

-backtrace
Print results and backtraces to log file.

-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

-build_outdirs
Create missing subdirectories in output directory

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

-cepext
Input files extension (suffixed 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

-ctm output in CTM file format (may require post-sorting)

-debug level for debugging messages

-dict pronunciation dictionary (lexicon) input file

-dictcase
Dictionary is case sensitive (NOTE: case insensitivity applies to ASCII characters
only)

-dither
Add 1/2-bit noise

-doublebw
Use double bandwidth filters (same center freq)

-ds Frame GMM computation downsampling ratio

-fdict word pronunciation dictionary input file

-feat Feature stream type, depends on the acoustic model

-featparams
containing feature extraction parameters.

-fillprob
Filler word transition probability

-frate Frame rate

-fsg format finite state grammar file

-fsgctl
file listing FSG file to use for each utterance

-fsgdir
directory for FSG files

-fsgext
extension for FSG files (including leading dot)

-fsgusealtpron
Add alternate pronunciations to FSG

-fsgusefiller
Insert filler words at each state.

-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 fwdflat 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

-jsgf grammar file

-keyphrase
to spot

-kws file with keyphrases to spot, one per line

-kws_delay
Delay to wait for best detection score

-kws_plp
Phone loop probability for keyword spotting

-kws_threshold
Threshold for p(hyp)/p(alternatives) ratio

-latsize
Initial backpointer table size

-lda containing transformation matrix to be applied to features (single-stream features
only)

-ldadim
Dimensionality of output of feature transformation (0 to use entire matrix)

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

-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.

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