194 lines
4.6 KiB
Groff
194 lines
4.6 KiB
Groff
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.TH SPHINX_FE 1 "2007-08-27"
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.SH NAME
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sphinx_fe \- Convert audio files to acoustic feature files
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.SH SYNOPSIS
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.B sphinx_fe
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[\fI options \fR]...
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.SH DESCRIPTION
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.PP
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This program converts audio files (in either Microsoft WAV, NIST
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Sphere, or raw format) to acoustic feature files for input to
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batch-mode speech recognition. The resulting files are also useful
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for various other things. A list of options follows:
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.TP
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.B \-alpha
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Preemphasis parameter
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.TP
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.B \-argfile
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file (e.g. feat.params from an acoustic model) to read parameters from. This will override anything set in other command line arguments.
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.TP
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.B \-blocksize
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Number of samples to read at a time.
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.TP
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.B \-build_outdirs
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Create missing subdirectories in output directory
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.TP
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.B \-c
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file for batch processing
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.TP
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.B \-cep2spec
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Input is cepstral files, output is log spectral files
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.TP
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.B \-di
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directory, input file names are relative to this, if defined
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.TP
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.B \-dither
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Add 1/2-bit noise
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.TP
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.B \-do
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directory, output files are relative to this
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.TP
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.B \-doublebw
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Use double bandwidth filters (same center freq)
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.TP
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.B \-ei
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extension to be applied to all input files
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.TP
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.B \-eo
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extension to be applied to all output files
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.TP
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.B \-example
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Shows example of how to use the tool
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.TP
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.B \-frate
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Frame rate
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.TP
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.B \-help
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Shows the usage of the tool
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.TP
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.B \-i
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audio input file
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.TP
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.B \-input_endian
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Endianness of input data, big or little, ignored if NIST or MS Wav
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.TP
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.B \-lifter
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Length of sin-curve for liftering, or 0 for no liftering.
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.TP
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.B \-logspec
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Write out logspectral files instead of cepstra
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.TP
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.B \-lowerf
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Lower edge of filters
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.TP
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.B \-mach_endian
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Endianness of machine, big or little
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.TP
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.B \-mswav
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Defines input format as Microsoft Wav (RIFF)
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.TP
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.B \-ncep
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Number of cep coefficients
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.TP
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.B \-nchans
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Number of channels of data (interlaced samples assumed)
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.TP
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.B \-nfft
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Size of FFT
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.TP
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.B \-nfilt
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Number of filter banks
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.TP
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.B \-nist
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Defines input format as NIST sphere
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.TP
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.B \-npart
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Number of parts to run in (supersedes \fB\-nskip\fR and \fB\-runlen\fR if non-zero)
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.TP
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.B \-nskip
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If a control file was specified, the number of utterances to skip at the head of the file
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.TP
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.B \-o
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cepstral output file
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.TP
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.B \-ofmt
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Format of output files - one of sphinx, htk, text.
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.TP
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.B \-part
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Index of the part to run (supersedes \fB\-nskip\fR and \fB\-runlen\fR if non-zero)
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.TP
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.B \-raw
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Defines input format as raw binary data
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.TP
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.B \-remove_dc
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Remove DC offset from each frame
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.TP
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.B \-remove_noise
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Remove noise with spectral subtraction in mel-energies
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.TP
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.B \-remove_silence
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Enables VAD, removes silence frames from processing
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.TP
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.B \-round_filters
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Round mel filter frequencies to DFT points
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.TP
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.B \-runlen
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If a control file was specified, the number of utterances to process, or \fB\-1\fR for all
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.TP
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.B \-samprate
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Sampling rate
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.TP
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.B \-seed
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Seed for random number generator; if less than zero, pick our own
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.TP
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.B \-smoothspec
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Write out cepstral-smoothed logspectral files
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.TP
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.B \-spec2cep
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Input is log spectral files, output is cepstral files
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.TP
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.B \-sph2pipe
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Input is NIST sphere (possibly with Shorten), use sph2pipe to convert
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.TP
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.B \-transform
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Which type of transform to use to calculate cepstra (legacy, dct, or htk)
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.TP
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.B \-unit_area
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Normalize mel filters to unit area
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.TP
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.B \-upperf
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Upper edge of filters
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.TP
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.B \-vad_postspeech
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Num of silence frames to keep after from speech to silence.
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.TP
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.B \-vad_prespeech
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Num of speech frames to keep before silence to speech.
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.TP
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.B \-vad_startspeech
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Num of speech frames to trigger vad from silence to speech.
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.TP
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.B \-vad_threshold
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Threshold for decision between noise and silence frames. Log-ratio between signal level and noise level.
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.TP
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.B \-verbose
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Show input filenames
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.TP
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.B \-warp_params
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defining the warping function
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.TP
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.B \-warp_type
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Warping function type (or shape)
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.TP
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.B \-whichchan
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Channel to process (numbered from 1), or 0 to mix all channels
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.TP
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.B \-wlen
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Hamming window length
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.PP
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Currently the only kind of features supported are MFCCs (mel-frequency
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cepstral coefficients). There are numerous options which control the
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properties of the output features. It is \fBVERY\fR important that
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you document the specific set of flags used to create any given set of
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feature files, since this information is \fBNOT\fR recorded in the
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files themselves, and any mismatch between the parameters used to
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extract features for recognition and those used to extract features
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for training will cause recognition to fail.
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.SH AUTHOR
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Written by numerous people at CMU from 1994 onwards. This manual page
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by David Huggins-Daines <dhuggins@cs.cmu.edu>
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.SH COPYRIGHT
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Copyright \(co 1994-2007 Carnegie Mellon University. See the file
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\fICOPYING\fR included with this package for more information.
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.br
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