POCKETSPHINX(1)

NAME
pocketsphinx - Run speech recognition on audio data

SYNOPSIS
pocketsphinx [ options... ] [ live | single | help | soxflags ] INPUTS...

DESCRIPTION

The ‘pocketsphinx’ command-line program reads single-channel 16-bit PCM audio one or more input files (or ‘-’ to read from standard input), and attempts to recognize speech in it using the default acoustic and language model. The input files can be raw audio, WAV, or NIST Sphere files, though some of these may not be recognized properly. It accepts a large number of options which you probably don't care about, and a command which defaults to ‘live’. The commands are as follows:

help
    Print a long list of those options you don't care about.

config
    Dump configuration as JSON to standard output (can be loaded with the ‘-config’ option).

live
    Detect speech segments in input files, run recognition on them (using those options you don't care about), and write the results to standard output in line-delimited JSON. I realize this isn't the prettiest format, but it sure beats XML. Each line contains a JSON object with these fields, which have short names to make the lines more readable:

    "b": Start time in seconds, from the beginning of the stream

    "d": Duration in seconds

    "p": Estimated probability of the recognition result, i.e. a number between 0 and 1 which may be used as a confidence score

    "t": Full text of recognition result

    "w": List of segments (usually words), each of which in turn contains the ‘b’, ‘d’, ‘p’, and ‘t’ fields, for start, end, probability, and the text of the word. In the future we may also support hierarchical results in which case ‘w’ could be present.

single
    Recognize the input as a single utterance, and write a JSON object in the same format described above.

align
    Align a single input file (or ‘-’ for standard input) to a word sequence, and write a JSON object in the same format described above. The first positional argument is the input, and all subsequent ones are concatenated to make the text, to avoid surprises if you forget to quote it. You are responsible for normalizing the text to remove punctuation, uppercase, centipedes, etc. For example:
            pocketsphinx align goforward.wav "go forward ten meters"
    By default, only word-level alignment is done. To get phone alignments, pass `-phone_align yes` in the flags, e.g.:
            pocketsphinx -phone_align yes align audio.wav $text
    This will make not particularly readable output, but you can use jq (https://stedolan.github.io/jq/) to clean it up. For example, you can get just the word names and start times like this:
            pocketsphinx align audio.wav $text | jq '.w[]|[.t,.b]'
    Or you could get the phone names and durations like this:
            pocketsphinx -phone_align yes align audio.wav $text | jq '.w[]|.w[]|[.t,.d]'
    There are many, many other possibilities, of course.

help
    Print a usage and help text with a list of possible arguments.

soxflags
    Return arguments to ‘sox’ which will create the appropriate input format. Note that because the ‘sox’ command-line is slightly quirky these must always come after the filename or ‘-d’ (which tells ‘sox’ to read from the microphone). You can run live recognition like this:
            sox -d $(pocketsphinx soxflags) | pocketsphinx -
    or decode from a file named "audio.mp3" like this:
            sox audio.mp3 $(pocketsphinx soxflags) | pocketsphinx -

By default only errors are printed to standard error, but if you want more information you can pass ‘-loglevel INFO’. Partial results are not printed, maybe they will be in the future, but don't hold your breath. Force-alignment is likely to be supported soon, however.

OPTIONS

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

-agcthresh
    Initial threshold for automatic gain control

-allphone
    phoneme decoding with phonetic lm (given here)

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

-alpha
    Preemphasis parameter

-ascale
    Inverse of acoustic model scale for confidence score calculation

-aw Inverse weight applied to acoustic scores.

-backtrace
    Print results and backtraces to log.

-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

-ceplen
    Number of components in the input feature vector

-cmn
    Cepstral mean normalization scheme ('live', 'batch', or 'none')

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

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

-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

-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.

-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 keyphrase 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

-lmname
    language model in -lmctl to use by default

-logbase
    Base in which all log-likelihoods calculated

-logfn
    to write log messages in

-loglevel
    Minimum level of log messages (DEBUG, INFO, WARN, ERROR)

-logspec
    Write out logspectral files instead of cepstra

-lowerf
    Lower edge of filters

-lpbeam
    Beam width applied to last phone in words

-lponlybeam
    Beam width applied to last phone in single-phone words

-lw Language model probability weight

-maxhmmpf
    Maximum number of active HMMs to maintain at each frame (or -1 for no pruning)

-maxwpf
    Maximum number of distinct word exits at each frame (or -1 for no pruning)

-mdef
    definition input file

-mean
    gaussian means input file

-mfclogdir
    to log feature files to

-min_endfr
    Nodes ignored in lattice construction if they persist for fewer than N frames

-mixw
    mixture weights input file (uncompressed)

-mixwfloor
    Senone mixture weights floor (applied to data from -mixw file)

-mllr
    transformation to apply to means and variances

-mmap
    Use memory-mapped I/O (if possible) for model files

-ncep
    Number of cep coefficients

-nfft
    Size of FFT, or 0 to set automatically (recommended)

-nfilt
    Number of filter banks

-nwpen
    New word transition penalty

-pbeam
    Beam width applied to phone transitions

-pip
    Phone insertion penalty

-pl_beam
    Beam width applied to phone loop search for lookahead

-pl_pbeam
    Beam width applied to phone loop transitions for lookahead

-pl_pip
    Phone insertion penalty for phone loop

-pl_weight
    Weight for phoneme lookahead penalties

-pl_window
    Phoneme lookahead window size, in frames

-rawlogdir
    to log raw audio files to

-remove_dc
    Remove DC offset from each frame

-remove_noise
    Remove noise using spectral subtraction

-round_filters
    Round mel filter frequencies to DFT points

-samprate
    Sampling rate

-seed
    Seed for random number generator; if less than zero, pick our own

-sendump
    dump (compressed mixture weights) input file

-senlogdir
    to log senone score files to

-senmgau
    to codebook mapping input file (usually not needed)

-silprob
    Silence word transition probability

-smoothspec
    Write out cepstral-smoothed logspectral files

-svspec
    specification (e.g., 24,0-11/25,12-23/26-38 or 0-12/13-25/26-38)

-tmat
    state transition matrix input file

-tmatfloor
    HMM state transition probability floor (applied to -tmat file)

-topn
    Maximum number of top Gaussians to use in scoring.

-topn_beam
    Beam width used to determine top-N Gaussians (or a list, per-feature)

-toprule
    rule for JSGF (first public rule is default)

-transform
    Which type of transform to use to calculate cepstra (legacy, dct, or htk)

-unit_area
    Normalize mel filters to unit area

-upperf
    Upper edge of filters

-uw Unigram weight

-var
    gaussian variances input file

-varfloor
    Mixture gaussian variance floor (applied to data from -var file)

-varnorm
    Variance normalize each utterance (only if CMN == current)

-verbose
    Show input filenames

-warp_params
    defining the warping function

-warp_type
    Warping function type (or shape)

-wbeam
    Beam width applied to word exits

-wip
    Word insertion penalty

-wlen
    Hamming window length

AUTHOR
Written by numerous people at CMU from 1994 onwards. This manual page by David Huggins-Daines <dhdaines@gmail.com>

COPYRIGHT
Copyright © 1994-2016 Carnegie Mellon University. See the file LICENSE included with this package for more information.

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