// onlinebin/online-gmm-decode-faster.cc
  
  // Copyright 2012 Cisco Systems (author: Matthias Paulik)
  
  //   Modifications to the original contribution by Cisco Systems made by:
  //   Vassil Panayotov
  
  // 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 "feat/feature-mfcc.h"
  #include "online/online-audio-source.h"
  #include "online/online-feat-input.h"
  #include "online/online-decodable.h"
  #include "online/online-faster-decoder.h"
  #include "online/onlinebin-util.h"
  
  
  int main(int argc, char *argv[]) {
  #ifndef KALDI_NO_PORTAUDIO
      try {
      using namespace kaldi;
      using namespace fst;
  
      typedef kaldi::int32 int32;
      typedef OnlineFeInput<Mfcc> FeInput;
  
      // Up to delta-delta derivative features are calculated (unless LDA is used)
      const int32 kDeltaOrder = 2;
      // Time out interval for the PortAudio source
      const int32 kTimeout = 500; // half second
      // Input sampling frequency is fixed to 16KHz
      const int32 kSampleFreq = 16000;
      // PortAudio's internal ring buffer size in bytes
      const int32 kPaRingSize = 32768;
      // Report interval for PortAudio buffer overflows in number of feat. batches
      const int32 kPaReportInt = 4;
  
      const char *usage =
          "Decode speech, using microphone input(PortAudio)
  
  "
          "Utterance segmentation is done on-the-fly.
  "
          "Feature splicing/LDA transform is used, if the optional(last) argument "
          "is given.
  "
          "Otherwise delta/delta-delta(2-nd order) features are produced.
  
  "
          "Usage: online-gmm-decode-faster [options] <model-in>"
          "<fst-in> <word-symbol-table> <silence-phones> [<lda-matrix-in>]
  
  "
          "Example: online-gmm-decode-faster --rt-min=0.3 --rt-max=0.5 "
          "--max-active=4000 --beam=12.0 --acoustic-scale=0.0769 "
          "model HCLG.fst words.txt '1:2:3:4:5' lda-matrix";
      ParseOptions po(usage);
      BaseFloat acoustic_scale = 0.1;
      int32 cmn_window = 600, min_cmn_window = 100;
      int32 right_context = 4, left_context = 4;
  
      kaldi::DeltaFeaturesOptions delta_opts;
      delta_opts.Register(&po);
      OnlineFasterDecoderOpts decoder_opts;
      OnlineFeatureMatrixOptions feature_reading_opts;
      decoder_opts.Register(&po, true);
      feature_reading_opts.Register(&po);
  
      po.Register("left-context", &left_context, "Number of frames of left context");
      po.Register("right-context", &right_context, "Number of frames of right context");
      po.Register("acoustic-scale", &acoustic_scale,
                  "Scaling factor for acoustic likelihoods");
      po.Register("cmn-window", &cmn_window,
          "Number of feat. vectors used in the running average CMN calculation");
      po.Register("min-cmn-window", &min_cmn_window,
                  "Minumum CMN window used at start of decoding (adds "
                  "latency only at start)");
  
      po.Read(argc, argv);
      if (po.NumArgs() != 4 && po.NumArgs() != 5) {
        po.PrintUsage();
        return 1;
      }
  
      std::string model_rxfilename = po.GetArg(1),
          fst_rxfilename = po.GetArg(2),
          word_syms_filename = po.GetArg(3),
          silence_phones_str = po.GetArg(4),
          lda_mat_rspecifier = po.GetOptArg(5);
  
      Matrix<BaseFloat> lda_transform;
      if (lda_mat_rspecifier != "") {
        bool binary_in;
        Input ki(lda_mat_rspecifier, &binary_in);
        lda_transform.Read(ki.Stream(), binary_in);
      }
  
      std::vector<int32> silence_phones;
      if (!SplitStringToIntegers(silence_phones_str, ":", false, &silence_phones))
          KALDI_ERR << "Invalid silence-phones string " << silence_phones_str;
      if (silence_phones.empty())
          KALDI_ERR << "No silence phones given!";
  
      TransitionModel trans_model;
      AmDiagGmm am_gmm;
      {
          bool binary;
          Input ki(model_rxfilename, &binary);
          trans_model.Read(ki.Stream(), binary);
          am_gmm.Read(ki.Stream(), binary);
      }
  
      fst::SymbolTable *word_syms = NULL;
      if (!(word_syms = fst::SymbolTable::ReadText(word_syms_filename)))
          KALDI_ERR << "Could not read symbol table from file "
                      << word_syms_filename;
  
      fst::Fst<fst::StdArc> *decode_fst = ReadDecodeGraph(fst_rxfilename);
  
      // We are not properly registering/exposing MFCC and frame extraction options,
      // because there are parts of the online decoding code, where some of these
      // options are hardwired(ToDo: we should fix this at some point)
      MfccOptions mfcc_opts;
      mfcc_opts.use_energy = false;
      int32 frame_length = mfcc_opts.frame_opts.frame_length_ms = 25;
      int32 frame_shift = mfcc_opts.frame_opts.frame_shift_ms = 10;
  
      int32 window_size = right_context + left_context + 1;
      decoder_opts.batch_size = std::max(decoder_opts.batch_size, window_size);
      OnlineFasterDecoder decoder(*decode_fst, decoder_opts,
                                  silence_phones, trans_model);
      VectorFst<LatticeArc> out_fst;
      OnlinePaSource au_src(kTimeout, kSampleFreq, kPaRingSize, kPaReportInt);
      Mfcc mfcc(mfcc_opts);
      FeInput fe_input(&au_src, &mfcc,
                       frame_length * (kSampleFreq / 1000),
                       frame_shift * (kSampleFreq / 1000));
      OnlineCmnInput cmn_input(&fe_input, cmn_window, min_cmn_window);
      OnlineFeatInputItf *feat_transform = 0;
      if (lda_mat_rspecifier != "") {
        feat_transform = new OnlineLdaInput(
                                 &cmn_input, lda_transform,
                                 left_context, right_context);
      } else {
        DeltaFeaturesOptions opts;
        opts.order = kDeltaOrder;
        feat_transform = new OnlineDeltaInput(opts, &cmn_input);
      }
  
      // feature_reading_opts contains number of retries, batch size.
      OnlineFeatureMatrix feature_matrix(feature_reading_opts,
                                         feat_transform);
  
      OnlineDecodableDiagGmmScaled decodable(am_gmm, trans_model, acoustic_scale,
                                             &feature_matrix);
      bool partial_res = false;
      decoder.InitDecoding();
      while (1) {
        OnlineFasterDecoder::DecodeState dstate = decoder.Decode(&decodable);
        if (dstate & (decoder.kEndFeats | decoder.kEndUtt)) {
          std::vector<int32> word_ids;
          decoder.FinishTraceBack(&out_fst);
          fst::GetLinearSymbolSequence(out_fst,
                                       static_cast<vector<int32> *>(0),
                                       &word_ids,
                                       static_cast<LatticeArc::Weight*>(0));
          PrintPartialResult(word_ids, word_syms, partial_res || word_ids.size());
          partial_res = false;
          if (dstate == decoder.kEndFeats) {
            if (au_src.TimedOut())
              KALDI_WARN << "PortAudio time out detected!";
            KALDI_LOG << "No more features available from PortAudio!";
            break;
          }
        } else {
          std::vector<int32> word_ids;
          if (decoder.PartialTraceback(&out_fst)) {
            fst::GetLinearSymbolSequence(out_fst,
                                         static_cast<vector<int32> *>(0),
                                         &word_ids,
                                         static_cast<LatticeArc::Weight*>(0));
            PrintPartialResult(word_ids, word_syms, false);
            if (!partial_res)
              partial_res = (word_ids.size() > 0);
          }
        }
      }
  
      delete feat_transform;
      delete word_syms;
      delete decode_fst;
      return 0;
    } catch(const std::exception& e) {
      std::cerr << e.what();
      return -1;
    }
  #endif
  }  // main()