Merge pull request kaldi-asr#26 from david-ryan-snyder/xvector2

Xvector: Adding nnet3-xvector-scoring

src/xvector/xvector.cc

@@ -115,4 +115,16 @@ void ComputeXvectorObjfAndDeriv(
   (*tot_weight) = N;
 }
 
+BaseFloat SimilarityScore(const Vector<BaseFloat> &v,
+    const Vector<BaseFloat> &w, const SpMatrix<BaseFloat> &S,
+    BaseFloat b) {
+  KALDI_ASSERT(v.Dim() == w.Dim() && v.Dim() == S.NumRows());
+  Vector<BaseFloat> Sv(v.Dim());
+  Sv.AddSpVec(1.0, S, v, 0);
+  Vector<BaseFloat> Sw(w.Dim());
+  Sw.AddSpVec(1.0, S, w, 0);
+  BaseFloat L = VecVec(v, w) - VecVec(v, Sv) - VecVec(w, Sw) + b;
+  return L;
+}
+
 } // namespace kaldi

src/xvector/xvector.h

@@ -44,7 +44,7 @@ namespace kaldi {
   the objective function correctly.
   Let the log-odds L(v,w) [interpreted as log(p_same(v,w) / p_different(v,w))]
   be defined as:
-      L(v, w) = v' w -  v' S v - w' S w
+      L(v, w) = v' w -  v' S v - w' S w + b
   then p_same(v, w) = -log(1 + exp(-l(v, w)), and
   p_different(v, w) = 1 - p_same(v, w) = -log(1 + exp(-l(v, w)).
 
@@ -72,6 +72,23 @@ namespace kaldi {
     CuMatrixBase<BaseFloat> *scores_out,
     BaseFloat *tot_objf,
     BaseFloat *tot_weight);
+
+ /*
+ Compute the similarity score between two input xvectors. The score is
+ defined as:
+      L(v, w) = v' w -  v' S v - w' S w + b
+ @param [in] v  The first xvector.
+ @param [in] w  The second xvector.
+ @param [in] S  A symmetric matrix, usually a constant output of the
+ Nnet the xvectors came from.
+ @param [in] b  A scalar offset, usually a constant output of the Nnet
+ the xvectors came from.
+ @return  The score between vectors v and w.
+ */
+ BaseFloat SimilarityScore(const Vector<BaseFloat> &v,
+    const Vector<BaseFloat> &w, const SpMatrix<BaseFloat> &S,
+    BaseFloat b);
+
 }  // namespace kaldi
 
 #endif

src/xvectorbin/Makefile

@@ -8,7 +8,7 @@ LDLIBS += $(CUDA_LDLIBS)
 
 BINFILES = nnet3-xvector-get-egs nnet3-xvector-compute-prob \
            nnet3-xvector-show-progress nnet3-xvector-train \
-           nnet3-xvector-compute
+           nnet3-xvector-compute nnet3-xvector-scoring
 
 OBJFILES =
 

src/xvectorbin/nnet3-xvector-scoring.cc

@@ -0,0 +1,150 @@
+// xvectorbin/nnet3-xvector-scoring.cc
+
+// Copyright 2013  Daniel Povey
+//           2016  David Snyder
+
+// 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 "base/kaldi-common.h"
+#include "util/common-utils.h"
+#include "nnet3/nnet-utils.h"
+#include "xvector/xvector.h"
+
+
+int main(int argc, char *argv[]) {
+  using namespace kaldi;
+    using namespace kaldi::nnet3;
+  typedef kaldi::int32 int32;
+  typedef kaldi::int64 int64;
+  try {
+    const char *usage =
+        "Computes scores between pairs of xvectors.\n"
+        "The 'trials-file' has lines of the form\n"
+        "<key1> <key2>\n"
+        "and the output will have the form\n"
+        "<key1> <key2> [<score>]\n"
+        "(if either key could not be found, the score field in the output\n"
+        "will be absent, and this program will print a warning)\n"
+        "\n"
+        "Usage:  nnet3-xvector-scoring [options] <raw-nnet-in> "
+        "<trials-in> <xvector1-rspecifier> <xvector2-rspecifier> "
+        "<scores-out>\n"
+        "e.g.: \n"
+        "  nnet3-xvector-scoring nnet.final trials ark:spk_xvectors.scp "
+        "ark:test_xvectors.scp trials.scored\n"
+        "See also: ivector-plda-scoring and ivector-compute-dot-products\n";
+
+    ParseOptions po(usage);
+
+    po.Read(argc, argv);
+
+    if (po.NumArgs() != 5) {
+      po.PrintUsage();
+      exit(1);
+    }
+
+    std::string nnet_rxfilename = po.GetArg(1),
+        trials_rxfilename = po.GetArg(2),
+        xvector1_rspecifier = po.GetArg(3),
+        xvector2_rspecifier = po.GetArg(4),
+        scores_wxfilename = po.GetArg(5);
+
+
+    int64 num_done = 0, num_err = 0;
+    Nnet nnet;
+    ReadKaldiObject(nnet_rxfilename, &nnet);
+    // We need to ensure that the Nnet has outputs called 's' and 'b'
+    // and that 'b' is a scalar and 's' can be interpreted as a symmetric
+    // matrix.
+    int32 s_index = nnet.GetNodeIndex("s"),
+          b_index = nnet.GetNodeIndex("b");
+    if (s_index == -1 || b_index == -1)
+      KALDI_ERR << "The input Nnet cannot be used for xvector scoring"
+                << "because it has no output called 's' or 'b'.";
+    if (!nnet.IsOutputNode(s_index) || !nnet.IsOutputNode(b_index))
+      KALDI_ERR << "The nodes 's' and 'b' must be output nodes.";
+
+    int32 s_dim = nnet.OutputDim("s"),
+          b_dim = nnet.OutputDim("b");
+    if (b_dim != 1)
+      KALDI_ERR << "The output 'b' is a scalar offset.  Input Nnet has an"
+                << "output called 'b' but it has a dimension of " << b_dim;
+    int32 d = (0.5) * (1 + sqrt(1 + 8 * s_dim)) - 1;
+    if (((d + 1) * d) / 2 != s_dim)
+      KALDI_ERR << "Output 's' cannot be interpretedas a symmetric matrix.";
+    Vector<BaseFloat> s_vec(s_dim);
+    Vector<BaseFloat> b_vec(1);
+    GetConstantOutput(nnet, "s", &s_vec);
+    GetConstantOutput(nnet, "b", &b_vec);
+    SpMatrix<BaseFloat> S(d);
+    S.CopyFromVec(s_vec);
+    BaseFloat b = b_vec(0);
+
+    RandomAccessBaseFloatVectorReader xvector1_reader(xvector1_rspecifier);
+    RandomAccessBaseFloatVectorReader xvector2_reader(xvector2_rspecifier);
+
+    Input ki(trials_rxfilename);
+
+    bool binary = false;
+    Output ko(scores_wxfilename, binary);
+    double sum = 0.0, sumsq = 0.0;
+
+    std::string line;
+    while (std::getline(ki.Stream(), line)) {
+      std::vector<std::string> fields;
+      SplitStringToVector(line, " \t\n\r", true, &fields);
+      if (fields.size() != 2) {
+        KALDI_ERR << "Bad line " << (num_done + num_err) << " in input "
+                  << "(expected two fields: key1 key2): " << line;
+      }
+      std::string key1 = fields[0], key2 = fields[1];
+      if (!xvector1_reader.HasKey(key1)) {
+        KALDI_WARN << "Key " << key1 << " not present in 1st table of xvectors.";
+        num_err++;
+        continue;
+      }
+      if (!xvector2_reader.HasKey(key2)) {
+        KALDI_WARN << "Key " << key2 << " not present in 2nd table of xvectors.";
+        num_err++;
+        continue;
+      }
+      const Vector<BaseFloat> &xvector1 = xvector1_reader.Value(key1),
+          &xvector2 = xvector2_reader.Value(key2);
+      // The following will crash if the dimensions differ, but
+      // they would likely also differ for all the xvectors so it's probably
+      // best to just crash.
+      BaseFloat score = SimilarityScore(xvector1, xvector2, S, b);
+      sum += score;
+      sumsq += score * score;
+      num_done++;
+      ko.Stream() << key1 << ' ' << key2 << ' ' << score << std::endl;
+    }
+
+    if (num_done != 0) {
+      BaseFloat mean = sum / num_done, scatter = sumsq / num_done,
+          variance = scatter - mean * mean, stddev = sqrt(variance);
+      KALDI_LOG << "Mean score was " << mean << ", standard deviation was "
+                << stddev;
+    }
+    KALDI_LOG << "Processed " << num_done << " trials " << num_err
+              << " had errors.";
+    return (num_done != 0 ? 0 : 1);
+  } catch(const std::exception &e) {
+    std::cerr << e.what();
+    return -1;
+  }
+}