1. Title of Database: ISOLET (Isolated Letter Speech Recognition)
2. Sources:
   (a) Creators: Ron Cole and Mark Fanty
       Department of Computer Science and Engineering,
       Oregon Graduate Institute, Beaverton, OR 97006.
       cole@cse.ogi.edu, fanty@cse.ogi.edu
   (b) Donor: Tom Dietterich
       Department of Computer Science
       Oregon State University, Corvallis, OR 97331
       tgd@cs.orst.edu
   (c) September 12, 1994

3. Past Usage:
   (a) Fanty, M., Cole, R. (1991).  Spoken letter recognition.  In
       Lippman, R. P., Moody, J., and Touretzky, D. S. (Eds).
       Advances in Neural Information Processing Systems 3.  San
       Mateo, CA: Morgan Kaufmann.

       Goal: Predict which letter-name was spoken--a simple
       classification task.  95.9% correct classification using
       the OPT backpropagation implementation.  Training on
       isolet1+2+3+4, testing on isolet5.  Network architecture: 56
       hidden units, 26 output units (one-per-class).

   (b) Dietterich, T. G., Bakiri, G. (1991)  Error-correcting
       output codes: A general method for improving multiclass
       inductive learning programs.  Proceedings of the Ninth
       National Conference on Artificial Intelligence (AAAI-91),
       Anaheim, CA: AAAI Press.

       Goal: same as above. 95.83% correct using OPT
       backpropagation.  (Architecture: 78 hidden units, 26 output
       units, one-per-class).
       96.73% correct using a 30-bit error-correcting output code with
       OPT (Architecture: 156 hidden units, 30 output units).

   (c) Dietterich, T. G., Bakiri, G. (1994) Solving Multiclass
       Learning Problems via Error-Correcting Output Codes.
       Submitted.  Available as URL
       ftp://ftp.cs.orst.edu/pub/tgd/papers/tr-ecoc.ps.gz

       Supporting data not published in that paper:

        Algorithm and configuration      errors    %error  %correct
        Opt 30-bit ECOC                     51       3.27     96.73
        Opt 62-bit ECOC                     63       4.04     95.96
        Opt OPC                             65       4.17     95.83
        C4.5 107-bit ECOC soft pruned      103       6.61     93.39
        C4.5 92-bit ECOC soft pruned       107       6.86     93.14
        C4.5 45-bit ECOC soft pruned       109       6.99     93.01
        C4.5 107-bit ECOC soft raw         116       7.44     92.56
        C4.5 92-bit ECOC soft raw          118       7.57     92.43
        C4.5 107-bit ECOC hard pruned      126       8.08     91.91
        C4.5 92-bit ECOC hard pruned       127       8.15     91.85
        C4.5 62-bit ECOC soft pruned       131       8.40     91.60
        C4.5 30-bit ECOC soft pruned       134       8.60     91.40
        C4.5 62-bit ECOC soft raw          134       8.60     91.40
        C4.5 77-bit ECOC hard pruned       138       8.85     91.15
        C4.5 45-bit ECOC soft raw          145       9.30     90.70
        C4.5 62-bit ECOC hard pruned       164       9.88     90.12
        C4.5 45-bit ECOC hard pruned       155       9.94     90.06
        C4.5 30-bit ECOC soft raw          175      11.23     88.77
        C4.5 30-bit ECOC hard pruned       185      11.87     88.13
        C4.5 multiclass soft pruned        239      15.33     84.67
        C4.5 multiclass soft raw           248      15.91     84.09
        C4.5 multiclass hard pruned        254      16.29     83.71
        C4.5 15-bit ECOC soft pruned       259      16.61     83.39
        C4.5 multiclass hard raw           264      16.93     83.07
        C4.5 OPC soft pruned               296      18.99     81.01
        C4.5 15-bit ECOC soft raw          321      20.59     79.41
        C4.5 107-bit ECOC hard raw         334      21.42     78.58
        C4.5 92-bit ECOC hard raw          349      22.39     77.61
        C4.5 OPC soft raw                  379      24.31     75.69
        C4.5 15-bit ECOC hard pruned       383      24.57     75.43
        C4.5 77-bit ECOC hard raw          424      27.20     72.80
        C4.5 OPC hard pruned               437      28.03     71.97
        C4.5 62-bit ECOC hard raw          463      29.70     70.30
        C4.5 OPC hard raw                  519      33.29     66.71
        C4.5 45-bit ECOC hard raw          568      36.43     63.57
        C4.5 30-bit ECOC hard raw          617      43.04     56.96
        C4.5 15-bit ECOC hard raw          991      63.57     36.43

        Legend:  OPT = conjugate-gradient implementation of backprop.
        C4.5 = Quinlan's C4.5 system, Release 1.
        OPC = one-per-class representation
        ECOC = error-correcting output code
        raw = unpruned decision trees
        pruned = pruned decision trees (CF=0.25)
        hard = default trees
        soft = trees with softened thresholds.
        multiclass = one tree to do all 26-way classifications.

4. Relevant Information Paragraph:
     This data set was generated as follows.
     150 subjects spoke the name of each letter of the alphabet twice.
     Hence, we have 52 training examples from each speaker.
     The speakers are grouped into sets of 30 speakers each, and are
     referred to as isolet1, isolet2, isolet3, isolet4, and isolet5.
     The data appears in isolet1+2+3+4.data in sequential order, first
     the speakers from isolet1, then isolet2, and so on.  The test
     set, isolet5, is a separate file.

     You will note that 3 examples are missing.  I believe they were
     dropped due to difficulties in recording.

     I believe this is a good domain for a noisy, perceptual task.  It
     is also a very good domain for testing the scaling abilities of
     algorithms. For example, C4.5 on this domain is slower than
     backpropagation!

     I have formatted the data for C4.5 and provided a C4.5-style
     names file as well.

5. Number of Instances
     isolet1+2+3+4.data.Z:  6238
     isolet5.data.Z:        1559

6. Number of Attributes       617 plus 1 for the class
     All attributes are continuous, real-valued attributes scaled into the
     range -1.0 to 1.0.  

7. For Each Attribute: (please give both acronym and full name if both exist)
     The features are described in the paper by Cole and Fanty cited
     above.  The features include spectral coefficients; contour
     features, sonorant features, pre-sonorant features, and
     post-sonorant features.  Exact order of appearance of the
     features is not known.

8. Missing Attribute Values: none

9. Class Distribution:
     Class       isolet1+2+3+4:    isolet5:
       1  A         240               60
       2  B         240               60
       3  C         240               60
       4  D         240               60
       5  E         240               60
       6  F         238               60
       7  G         240               60
       8  H         240               60
       9  I         240               60
      10  J         240               60
      11  K         240               60
      12  L         240               60
      13  M         240               59
      14  N         240               60
      15  O         240               60
      16  P         240               60
      17  Q         240               60
      18  R         240               60
      19  S         240               60
      20  T         240               60
      21  U         240               60
      22  V         240               60
      23  W         240               60
      24  X         240               60
      25  Y         240               60
      26  Z         240               60

