%SoundModelDS - Bayesean inference of HMM parameters from training data
%
% Y = SoundModelDS(TrainingDataListFile, nS, nB [,OPTIONAL ARGUMENTS...])
%
% INPUTS:
% TrainingDataList - filename of training data list: WAV file names (one per line).
%   nS - number of states in hidden Markov model [10]
%   nB - number of basis components to extract [10]
%
% The following variables are optional, and are specified using
% 'parameter' value pairs on the command line.
%
%    'hopSize'            'PT10N1000F'  - AudioSpectrumEnvelopeD hopSize
%    'loEdge'              62.5,        - AudioSpectrumEnvelopeD low Hz
%    'hiEdge'              16000,       - AudioSpectrumEnvelopeD high Hz
%    'octaveResolution'    '1/8'        - AudioSpectrumEnvelopeD resolution
%    'sequenceHopSize'     '',          - HMM data window hop [whole file]
%    'sequenceFrameLength' ''           - HMM data window length [whole file]
%    'outputFile'           ''          - Filename for Model output [stem+mp7.xml]
%    'soundName'            ''          - Model identifier name
%
% OUTPUTS: 
%
% outputFile.dat =  matlab struct Y.{T,S,M,C,X,maxenv,V,p}
%
%     T - state transition matrix
%     S - initial state probability vector
%     M - stacked means matrix (1 vector per row)
%     C - stacked inverse covariances
%     V - AudioSpectrumBasis vectors
% maxenv- scaling parameter for model decoding
%     p - training cycle likelihoods
%
% outputFile.mp7 = XML file containing MPEG-7 SoundModel description scheme
%
% Copyright (C) 1999-2002 Michael A. Casey, All Rights Reserved

LICENSE
      Permission to use, copy, modify and distribute this software and
      its documentation for educational, research and non-profit
      purposes, without fee, and without a written agreement is hereby
      granted, provided that the above copyright notice and the
      following three paragraphs appear in all copies.

      To request Permission to incorporate this software into
      commercial products contact MERL - Mitsubishi Electric Research
      Laboratories, 201 Broadway, Cambridge, MA 02139.

      IN NO EVENT SHALL MERL BE LIABLE TO ANY PARTY FOR DIRECT,
      INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
      INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE
      AND ITS DOCUMENTATION, EVEN IF MERL HAS BEEN ADVISED OF THE
      POSSIBILITY OF SUCH DAMAGES.

      MERL SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
      LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
      FITNESS FOR A PARTICULAR PURPOSE.  THE SOFTWARE PROVIDED
      HEREUNDER IS ON AN "AS IS" BASIS, AND MERL HAS NO OBLIGATIONS TO
      PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR
      MODIFICATIONS.