Info on Phoneme Data Set

This data set was obtained from www-stat.stanford.edu/ElemStatLearn and was used as one of example sets in Hastie et al.: The elements of statistical learning. Following is the data provided with this data set.

These data arose from a collaboration between  Andreas Buja, Werner
Stuetzle and Martin Maechler, and we used as an illustration in the
paper on Penalized Discriminant Analysis by Hastie, Buja and
Tibshirani (1995), referenced in the text. 

The data were extracted from the TIMIT database (TIMIT
Acoustic-Phonetic Continuous Speech Corpus, NTIS, US Dept of Commerce)
which is a widely used resource for research in speech recognition.  A
dataset was formed by selecting five phonemes for
classification based on digitized speech from this database.  The
phonemes are transcribed as follows: "sh" as in "she", "dcl" as in
"dark", "iy" as the vowel in "she", "aa" as the vowel in "dark", and
"ao" as the first vowel in "water".  From continuous speech of 50 male
speakers, 4509 speech frames of 32 msec duration were selected,
approximately 2 examples of each phoneme from each speaker.  Each
speech frame is represented by 512 samples at a 16kHz sampling rate,
and each frame represents one of the above five phonemes.  The
breakdown of the 4509 speech frames into phoneme frequencies is as
follows:

  aa   ao dcl   iy  sh 
 695 1022 757 1163 872

From each speech frame, we computed a log-periodogram, which is one of
several widely used methods for casting speech data in a form suitable
for speech recognition.  Thus the data used in what follows consist of
4509 log-periodograms of length 256, with known class (phoneme)
memberships. 

The data contain 256 columns labelled "x.1" - "x.256", a response
column labelled "g", and a column labelled "speaker" identifying the
diffferent speakers.