1 files changed, 127 insertions, 0 deletions
diff --git a/dtrain/score.cc b/dtrain/score.cc
new file mode 100644
index 00000000..4cde638a
--- /dev/null
+++ b/dtrain/score.cc
@@ -0,0 +1,127 @@
+#include "score.h"
+
+namespace dtrain
+{
+
+
+/*
+ * bleu
+ *
+ * as in "BLEU: a Method for Automatic Evaluation
+ *        of Machine Translation"
+ * (Papineni et al. '02)
+ *
+ * NOTE: 0 if for one n \in {1..N} count is 0
+ */
+score_t
+BleuScorer::Bleu(NgramCounts& counts, const unsigned hyp_len, const unsigned ref_len)
+{
+  if (hyp_len == 0 || ref_len == 0) return 0;
+  unsigned M = N_;
+  if (ref_len < N_) M = ref_len;
+  score_t sum = 0;
+  for (unsigned i = 0; i < M; i++) {
+    if (counts.clipped[i] == 0 || counts.sum[i] == 0) return 0;
+    sum += w_[i] * log((score_t)counts.clipped[i]/counts.sum[i]);
+  }
+  return brevity_penaly(hyp_len, ref_len) * exp(sum);
+}
+
+score_t
+BleuScorer::Score(vector<WordID>& hyp, vector<WordID>& ref,
+                  const unsigned rank)
+{
+  unsigned hyp_len = hyp.size(), ref_len = ref.size();
+  if (hyp_len == 0 || ref_len == 0) return 0;
+  NgramCounts counts = make_ngram_counts(hyp, ref, N_);
+  return Bleu(counts, hyp_len, ref_len);
+}
+
+/*
+ * 'stupid' bleu
+ *
+ * as in "ORANGE: a Method for Evaluating
+ *        Automatic Evaluation Metrics
+ *        for Machine Translation"
+ * (Lin & Och '04)
+ *
+ * NOTE: 0 iff no 1gram match
+ */
+score_t
+StupidBleuScorer::Score(vector<WordID>& hyp, vector<WordID>& ref,
+                        const unsigned rank)
+{
+  unsigned hyp_len = hyp.size(), ref_len = ref.size();
+  if (hyp_len == 0 || ref_len == 0) return 0;
+  NgramCounts counts = make_ngram_counts(hyp, ref, N_);
+  unsigned M = N_;
+  if (ref_len < N_) M = ref_len;
+  score_t sum = 0, add = 0;
+  for (unsigned i = 0; i < M; i++) {
+    if (i == 1) add = 1;
+    sum += w_[i] * log(((score_t)counts.clipped[i] + add)/((counts.sum[i] + add)));
+  }
+  return  brevity_penaly(hyp_len, ref_len) * exp(sum);
+}
+
+/*
+ * smooth bleu
+ *
+ * as in "An End-to-End Discriminative Approach
+ *        to Machine Translation"
+ * (Liang et al. '06)
+ *
+ * NOTE: max is 0.9375
+ */
+score_t
+SmoothBleuScorer::Score(vector<WordID>& hyp, vector<WordID>& ref,
+                        const unsigned rank)
+{
+  unsigned hyp_len = hyp.size(), ref_len = ref.size();
+  if (hyp_len == 0 || ref_len == 0) return 0;
+  NgramCounts counts = make_ngram_counts(hyp, ref, N_);
+  score_t sum = 0;
+  unsigned j = 1;
+  for (unsigned i = 0; i < N_; i++) {
+    if (counts.clipped[i] == 0 || counts.sum[i] == 0) continue;
+    sum += exp((w_[i] * log((score_t)counts.clipped[i]/counts.sum[i])))/pow(2, N_-j+1);
+    j++;
+  }
+  return brevity_penaly(hyp_len, ref_len) * sum;
+}
+
+/*
+ * approx. bleu
+ *
+ * as in "Online Large-Margin Training of Syntactic
+ *        and Structural Translation Features"
+ * (Chiang et al. '08)
+ *
+ * NOTE: needs some code in dtrain.cc
+ */
+score_t
+ApproxBleuScorer::Score(vector<WordID>& hyp, vector<WordID>& ref,
+                        const unsigned rank)
+{
+  unsigned hyp_len = hyp.size(), ref_len = ref.size();
+  if (hyp_len == 0 || ref_len == 0) return 0;
+  NgramCounts counts = make_ngram_counts(hyp, ref, N_);
+  NgramCounts tmp(N_);
+  if (rank == 0) { // 'context of 1best translations'
+    glob_onebest_counts += counts;
+    glob_hyp_len += hyp_len;
+    glob_ref_len += ref_len;
+    hyp_len = glob_hyp_len;
+    ref_len = glob_ref_len;
+    tmp = glob_onebest_counts;
+  } else {
+    hyp_len = hyp.size();
+    ref_len = ref.size();
+    tmp = glob_onebest_counts + counts;
+  }
+  return 0.9 * Bleu(tmp, hyp_len, ref_len);
+}
+
+
+} // namespace
+