The NICO toolkit was developed for automatic
speech recognition problems and therefore special commands are available
for speech input and output. The set of tools available is not a full tool-kit
for speech processing but it is enough to start experimenting. It's possible
to extract filterbank features (mel or bark scaled), compute cepstrum features
and velocity and acceleration coefficients. A tool for creating targets
for phoneme clasifiers from phonetic label files and a simple label file
editor are also available.
In phonetic classification expreriments,
you have an output group of N output units -- one unit for each phoneme.
The output unit with the highest activation at each time point is the network's
The phonetic targets are typically specified
in "label files" -- file formats that are not directly supported by NICO
streams. This is text files with basically one phoneme per row. Start and
end times for the phonemes are also given. See the reference section File
formats for more details.
Creating phonetic target files
The command Lab2Targ
converts label files to a file format that can be read by a stream in a
network. This is the syntax for Lab2Targ:
USAGE: Lab2Targ [options] LabelListFile InputSize InputFile
"LabelListFile" is a list of the phonemes
to discriminate, so the number of target values per frame is equal to the
number of rows in "LabelListFile" . The program also needs to know the
number of samples for each utterance, therefore you need to give the datafile
of one arbitrary other stream of the network (for example an input stream)
and the size of this stream. That's the arguments "InputSize" and "InputFile".
Following the general convention of the toolkit, all data files for the
same utterance have the same basename so the filename of the created target
file is constructed from "InputFile". The directories and extensions of
the input file, label file and outputted target file can be specified with
various options (see the manual page for Lab2Targ).
can read severeal different label file formats and write different target
file formats. File formats are described in more detail in the Reference
Creating input feature files
Input features are computed with the Barkfib
USAGE: Barkfib [options] audiofile
Barkfib cen extract: mel, bark or linearly
spaced filterbank features and do some standard preprocessing, such as
pre-emphasis. It also computes cepstrum features from the filterbank and
the energy coefficient on demand. Melfib can read several different audio
file formats, see the File
formats section for details. The created datafiles gets the same base
names as the audio files, but the file extension and output directory can
be specified by command switches. See the manual page for Barkfib
for more details.
The command MakeCep
can be used to create a cepstrum representation from the filterbank input.
This is done by adding a layer of hidden linear units to the network and
connect them with the appropriate weights. Similarly, MakeDiff
creates a group of units computing the first order derivative of another
group by adding a new hidden layer and connect it to the old lauer with
time-delay and look-ahead connections. Thus, by combining MakeCep and MakeDiff,
the popular cepstrum + velocity and acceleration can be created.
In the Speech
Example we put all the pieces discussed above together in a phonetic