NAME
sphinx_fe - Convert audio files to acoustic feature files
SYNOPSIS
sphinx_fe [ options ]...
DESCRIPTION
This program converts audio files (in either Microsoft WAV, NIST
Sphere, or raw format) to acoustic feature files for input to batch-
mode speech recognition. The resulting files are also useful for
various other things. A list of options follows:
-alpha Preemphasis parameter
-blocksize
Block size, used to limit the number of samples used at a time
when reading very large audio files
-c file for batch processing
-cep2spec
Input is cepstral files, output is log spectral files
-di directory, input file names are relative to this, if defined
-dither
Add 1/2-bit noise
-do directory, output files are relative to this
-doublebw
Use double bandwidth filters (same center freq)
-ei extension to be applied to all input files
-eo extension to be applied to all output files
-example
Shows example of how to use the tool
-fbtype
FB Type of mel_scale or log_linear
-feat SPHINX format - big endian
-frate Frame rate
-help Shows the usage of the tool
-i audio input file
-input_endian
Endianness of input data, big or little, ignored if NIST or MS
Wav
-lifter
Length of sin-curve for liftering, or 0 for no liftering.
-logspec
Write out logspectral files instead of cepstra
-lowerf
Lower edge of filters
-mach_endian
Endianness of machine, big or little
-mswav Defines input format as Microsoft Wav (RIFF)
-ncep Number of cep coefficients
-nchans
Number of channels of data (interlaced samples assumed)
-nfft Size of FFT
-nfilt Number of filter banks
-nist Defines input format as NIST sphere
-nskip a control file was specified, the number of utterances to skip
at the head of the file
-o cepstral output file
-raw Defines input format as raw binary data
-remove_dc
Remove DC offset from each frame
-round_filters
Round mel filter frequencies to DFT points
-runlen
a control file was specified, the number of utterances to
process (see -nskip too)
-samprate
Sampling rate
-seed Seed for random number generator; if less than zero, pick our
own
-smoothspec
Write out cepstral-smoothed logspectral files
-spec2cep
Input is log spectral files, output is cepstral files
-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
-verbose
Show input filenames
-warp_params
defining the warping function
-warp_type
Warping function type (or shape)
-whichchan
Channel to process
-wlen Hamming window length
Currently the only kind of features supported are MFCCs (mel-frequency
cepstral coefficients). There are numerous options which control the
properties of the output features. It is VERY important that you
document the specific set of flags used to create any given set of
feature files, since this information is NOT recorded in the files
themselves, and any mismatch between the parameters used to extract
features for recognition and those used to extract features for
training will cause recognition to fail.
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.
2007-08-27