SPHINX_FE(1)

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.