// online2bin/apply-cmvn-online.cc
  
  // Copyright      2014  Johns Hopkins University (author: Daniel Povey)
  
  // See ../../COPYING for clarification regarding multiple authors
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  //
  //  http://www.apache.org/licenses/LICENSE-2.0
  //
  // THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  // KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
  // WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
  // MERCHANTABLITY OR NON-INFRINGEMENT.
  // See the Apache 2 License for the specific language governing permissions and
  // limitations under the License.
  
  #include <string>
  #include <vector>
  #include "base/kaldi-common.h"
  #include "util/common-utils.h"
  #include "feat/online-feature.h"
  
  int main(int argc, char *argv[]) {
    try {
      typedef kaldi::int32 int32;
      using namespace kaldi;
      const char *usage =
          "Apply online cepstral mean (and possibly variance) computation online,
  "
          "using the same code as used for online decoding in the 'new' setup in
  "
          "online2/ and online2bin/.  If the --spk2utt option is used, it uses
  "
          "prior utterances from the same speaker to back off to at the utterance
  "
          "beginning.  See also apply-cmvn-sliding.
  "
          "
  "
          "Usage: apply-cmvn-online [options] <global-cmvn-stats> <feature-rspecifier> "
          "<feature-wspecifier>
  "
          "e.g. apply-cmvn-online 'matrix-sum scp:data/train/cmvn.scp -|' data/train/split8/1/feats.scp ark:-
  "
          "or: apply-cmvn-online --spk2utt=ark:data/train/split8/1/spk2utt 'matrix-sum scp:data/train/cmvn.scp -|' "
          " data/train/split8/1/feats.scp ark:-
  ";
      
      ParseOptions po(usage);
  
      OnlineCmvnOptions cmvn_opts;
      
      std::string spk2utt_rspecifier;
      po.Register("spk2utt", &spk2utt_rspecifier, "rspecifier for speaker to "
                  "utterance-list map");
      cmvn_opts.Register(&po);
      
      po.Read(argc, argv);
  
      if (po.NumArgs() != 3) {
        po.PrintUsage();
        exit(1);
      }
  
      std::string global_stats_rxfilename = po.GetArg(1),
          feature_rspecifier = po.GetArg(2),
          feature_wspecifier = po.GetArg(3);
  
      // global_cmvn_stats helps us initialize to online CMVN to
      // reasonable values at the beginning of the utterance.
      Matrix<double> global_cmvn_stats;
      ReadKaldiObject(global_stats_rxfilename, &global_cmvn_stats);
  
      
      
      BaseFloatMatrixWriter feature_writer(feature_wspecifier);
      int32 num_done = 0, num_err = 0;
      int64 tot_t = 0;
  
      if (spk2utt_rspecifier != "") {
        SequentialTokenVectorReader spk2utt_reader(spk2utt_rspecifier);
        RandomAccessBaseFloatMatrixReader feature_reader(feature_rspecifier);
  
        for (; !spk2utt_reader.Done(); spk2utt_reader.Next()) {
          OnlineCmvnState cmvn_state(global_cmvn_stats);
          const std::vector<std::string> &uttlist = spk2utt_reader.Value();
          for (size_t i = 0; i < uttlist.size(); i++) {
            std::string utt = uttlist[i];
            if (!feature_reader.HasKey(utt)) {
              KALDI_WARN << "No features for utterance " << utt;
              num_err++;
              continue;
            }
            const Matrix<BaseFloat> &feats = feature_reader.Value(utt);
            
            Matrix<BaseFloat> normalized_feats(feats.NumRows(), feats.NumCols(),
                                               kUndefined);
  
            OnlineMatrixFeature online_matrix(feats);
            OnlineCmvn online_cmvn(cmvn_opts,
                                   cmvn_state,
                                   &online_matrix);
  
            for (int32 t = 0; t < feats.NumRows(); t++) {
              SubVector<BaseFloat> row(normalized_feats, t);
              online_cmvn.GetFrame(t, &row);
            }
            online_cmvn.GetState(feats.NumRows() - 1, &cmvn_state);
            
            num_done++;
            tot_t += feats.NumRows();
            feature_writer.Write(utt, normalized_feats);
          }
        }
      } else {
        SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
        for (; !feature_reader.Done(); feature_reader.Next()) {
          std::string utt = feature_reader.Key();
          const Matrix<BaseFloat> &feats = feature_reader.Value();
          OnlineCmvnState cmvn_state(global_cmvn_stats);
  
          Matrix<BaseFloat> normalized_feats(feats.NumRows(), feats.NumCols(),
                                             kUndefined);
          OnlineMatrixFeature online_matrix(feats);
          OnlineCmvn online_cmvn(cmvn_opts,
                                 cmvn_state,
                                 &online_matrix);
  
          for (int32 t = 0; t < feats.NumRows(); t++) {
            SubVector<BaseFloat> row(normalized_feats, t);
            online_cmvn.GetFrame(t, &row);
          }
          num_done++;
          tot_t += feats.NumRows();
          feature_writer.Write(utt, normalized_feats);
          
          num_done++;
        }
      }
      
      KALDI_LOG << "Applied online CMVN to " << num_done << " files, or "
                << tot_t << " frames.";
      return (num_done != 0 ? 0 : 1);
    } catch(const std::exception &e) {
      std::cerr << e.what();
      return -1;
    }
  }