Minor changes, due to modification in transform/basis-fmllr-diag-gmm

git-svn-id: https://svn.code.sf.net/p/kaldi/code/trunk@1094 5e6a8d80-dfce-4ca6-a32a-6e07a63d50c8

src/gmmbin/gmm-est-basis-fmllr.cc

+// gmmbin/gmm-est-basis-fmllr.cc
+
+// Copyright 2012  Carnegie Mellon University (author: Yajie Miao)
+
+// 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>
+using std::string;
+#include <vector>
+using std::vector;
+
+#include "base/kaldi-common.h"
+#include "util/common-utils.h"
+#include "gmm/am-diag-gmm.h"
+#include "hmm/transition-model.h"
+#include "transform/fmllr-diag-gmm.h"
+#include "transform/basis-fmllr-diag-gmm.h"
+
+namespace kaldi {
+void AccumulateForUtterance(const Matrix<BaseFloat> &feats,
+                            const Posterior &post,
+                            const TransitionModel &trans_model,
+                            const AmDiagGmm &am_gmm,
+                            FmllrDiagGmmAccs *spk_stats) {
+  for (size_t i = 0; i < post.size(); i++) {
+    for (size_t j = 0; j < post[i].size(); j++) {
+      int32 pdf_id = trans_model.TransitionIdToPdf(post[i][j].first);
+      spk_stats->AccumulateForGmm(am_gmm.GetPdf(pdf_id),
+                                  feats.Row(i),
+                                  post[i][j].second);
+    }
+  }
+}
+
+
+}
+
+int main(int argc, char *argv[]) {
+  try {
+    typedef kaldi::int32 int32;
+    using namespace kaldi;
+    const char *usage =
+        "Perform basis fMLLR adaptation in testing stage, either per utterance or\n"
+        "for the supplied set of speakers (spk2utt option). Reads posterior to\n"
+        "accumulate fMLLR stats for each speaker/utterance. Writes to a table of\n"
+        "matrices.\n"
+        "Usage: gmm-est-basis-fmllr [options] <model-in> <basis-rspecifier> <feature-rspecifier> "
+        "<post-rspecifier> <transform-wspecifier>\n";
+
+    ParseOptions po(usage);
+    BasisFmllrOptions basis_fmllr_opts;
+    string spk2utt_rspecifier;
+    string weights_out_filename;
+
+    po.Register("spk2utt", &spk2utt_rspecifier, "Rspecifier for speaker to "
+                "utterance-list map");
+    po.Register("write-weights", &weights_out_filename, "File to write base "
+                    "weights to.");
+
+    basis_fmllr_opts.Register(&po);
+
+    po.Read(argc, argv);
+    if (po.NumArgs() != 5) {
+      po.PrintUsage();
+      exit(1);
+    }
+
+    string
+        model_rxfilename = po.GetArg(1),
+        basis_rspecifier = po.GetArg(2),
+        feature_rspecifier = po.GetArg(3),
+        post_rspecifier = po.GetArg(4),
+        trans_wspecifier = po.GetArg(5);
+
+    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);
+    }
+
+    BasisFmllrEstimate basis_est(am_gmm.Dim());
+    {
+      bool binary;
+      Input ki(basis_rspecifier, &binary);
+      basis_est.ReadBasis(ki.Stream(), binary, false);
+    }
+
+    RandomAccessPosteriorReader post_reader(post_rspecifier);
+
+    double tot_impr = 0.0, tot_t = 0.0;
+
+    BaseFloatMatrixWriter transform_writer(trans_wspecifier);
+    BaseFloatVectorWriter weights_writer;
+    if (!weights_out_filename.empty()) {
+      weights_writer.Open(weights_out_filename);
+    }
+
+    int32 num_done = 0, num_no_post = 0, num_other_error = 0;
+    if (spk2utt_rspecifier != "") {  // per-speaker adaptation
+      SequentialTokenVectorReader spk2utt_reader(spk2utt_rspecifier);
+      RandomAccessBaseFloatMatrixReader feature_reader(feature_rspecifier);
+
+      for (; !spk2utt_reader.Done(); spk2utt_reader.Next()) {
+        FmllrDiagGmmAccs spk_stats(am_gmm.Dim());
+        string spk = spk2utt_reader.Key();
+        const vector<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 << "Did not find features for utterance " << utt;
+            num_other_error++;
+            continue;
+          }
+          if (!post_reader.HasKey(utt)) {
+            KALDI_WARN << "Did not find posteriors for utterance " << utt;
+            num_no_post++;
+            continue;
+          }
+          const Matrix<BaseFloat> &feats = feature_reader.Value(utt);
+          const Posterior &post = post_reader.Value(utt);
+          if (static_cast<int32>(post.size()) != feats.NumRows()) {
+            KALDI_WARN << "Posterior vector has wrong size " << (post.size())
+                       << " vs. " << (feats.NumRows());
+            num_other_error++;
+            continue;
+          }
+
+          AccumulateForUtterance(feats, post, trans_model, am_gmm, &spk_stats);
+          num_done++;
+        }  // end looping over all utterances of the current speaker
+
+        double impr, spk_tot_t;
+        {
+          // Compute the transform and write it out.
+          Matrix<BaseFloat> transform(am_gmm.Dim(), am_gmm.Dim() + 1);
+          transform.SetUnit();
+          Vector<BaseFloat> weights(am_gmm.Dim() * (am_gmm.Dim() + 1)); // size will be adjusted
+          impr = basis_est.BasisFmllrCoefficients(spk_stats, &transform,
+        		             &weights, basis_fmllr_opts);
+          spk_tot_t = spk_stats.beta_;
+          transform_writer.Write(spk, transform);
+          // Optionally write out the base weights
+          if (!weights_out_filename.empty() && weights.Dim() > 0)
+        	  weights_writer.Write(spk, weights);
+        }
+
+        KALDI_LOG << "For speaker " << spk << ", auxf-impr from Basis fMLLR is "
+                  << (impr / spk_tot_t) << ", over " << spk_tot_t << " frames.";
+        tot_impr += impr;
+        tot_t += spk_tot_t;
+      }  // end looping over speakers
+    } else {  // per-utterance adaptation
+      SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
+      for (; !feature_reader.Done(); feature_reader.Next()) {
+        string utt = feature_reader.Key();
+        if (!post_reader.HasKey(utt)) {
+          KALDI_WARN << "Did not find posts for utterance " << utt;
+          num_no_post++;
+          continue;
+        }
+        const Matrix<BaseFloat> &feats = feature_reader.Value();
+        const Posterior &post = post_reader.Value(utt);
+
+        if (static_cast<int32>(post.size()) != feats.NumRows()) {
+          KALDI_WARN << "Posterior has wrong size " << (post.size())
+                     << " vs. " << (feats.NumRows());
+          num_other_error++;
+          continue;
+        }
+
+        FmllrDiagGmmAccs spk_stats(am_gmm.Dim());
+        AccumulateForUtterance(feats, post, trans_model, am_gmm, &spk_stats);
+        num_done++;
+
+        BaseFloat impr, utt_tot_t;
+        {  // Compute the transform and write it out.
+          Matrix<BaseFloat> transform(am_gmm.Dim(), am_gmm.Dim()+1);
+          transform.SetUnit();
+          Vector<BaseFloat> weights(am_gmm.Dim() * (am_gmm.Dim() + 1)); // size will be adjusted
+          impr = basis_est.BasisFmllrCoefficients(spk_stats, &transform,
+                  		             &weights, basis_fmllr_opts);
+          utt_tot_t = spk_stats.beta_;
+          transform_writer.Write(utt, transform);
+          // Optionally write out the base weights
+          if (!weights_out_filename.empty() && weights.Dim() > 0)
+            weights_writer.Write(utt, weights);
+        }
+        KALDI_LOG << "For utterance " << utt << ", auxf-impr from Basis fMLLR is "
+                  << (impr / utt_tot_t) << ", over " << utt_tot_t << " frames.";
+        tot_impr += impr;
+        tot_t += utt_tot_t;
+      }  // end looping over all the utterances
+    }
+
+    KALDI_LOG << "Done " << num_done << " files, " << num_no_post
+              << " with no posts, " << num_other_error << " with other errors.";
+    KALDI_LOG << "Overall fMLLR auxf-impr per frame is "
+              << (tot_impr / tot_t) << " over " << tot_t << " frames.";
+    return (num_done != 0 ? 0 : 1);
+  } catch(const std::exception& e) {
+    std::cerr << e.what();
+    return -1;
+  }
+}
+