diff --git a/README.md b/README.md
index 19901dff58598cdc2363b8040f2b7c3554d4f2b4..9a61ffac4254a439469646ccc880ff718de0420e 100644
--- a/README.md
+++ b/README.md
@@ -21,6 +21,7 @@ Readers interested in the high level design and experimental evaluation of these
## Prerequisites
- This library will re-use binaries and scripts from the [Kaldi](http://kaldi-asr.org) toolkit. So you should have Kaldi pre-installed on your system.
+ - Additionally you need to install [Kaldi helpers](local/kaldi-helpers)
- Speech datasets for training STT models, including:
- (small amount of) transcribed speech data. As demonstrated in the [COMPRISE D4.2 deliverable report](https://www.compriseh2020.eu/deliverables/), it could be an existing read speech corpus or a few hours of domain/application specific speech corpus.
- (more) un-transcribed speech data.
diff --git a/local/kaldi-helpers/README.md b/local/kaldi-helpers/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e800126ae5df2b3a01a35112f6a6f13c6bc3516c
--- /dev/null
+++ b/local/kaldi-helpers/README.md
@@ -0,0 +1,11 @@
+This directory shares some Kaldi helpers which are Kaldi .cc source code modified to achieve extended Kaldi binary functionalities.
+
+The avaiable Kaldi helpers and steps to compile them are listed below.
+
+**lattice-mbr-decode-wtimes**:
+- Download [lattice-mbr-decode-wtimes.cc](lattice-mbr-decode-wtimes.cc)
+- `cp lattice-mbr-decode-wtimes.cc <kaldi-dir>/src/latbin/`
+- Edit the '<kaldi-dir>/src/latbin/Makefile' to include 'lattice-mbr-decode-wtimes' in variable 'BINFILES'
+- `cd <kaldi-dir>/src/latbin/`
+- `make`
+
diff --git a/local/kaldi-helpers/lattice-mbr-decode-wtimes.cc b/local/kaldi-helpers/lattice-mbr-decode-wtimes.cc
new file mode 100755
index 0000000000000000000000000000000000000000..b13e773da3713caf9c3ce6ea60f75145b5eaac5a
--- /dev/null
+++ b/local/kaldi-helpers/lattice-mbr-decode-wtimes.cc
@@ -0,0 +1,141 @@
+// latbin/lattice-mbr-decode-wtimes.cc
+
+// Derived software, Copyright © 2020 INRIA (Imran Sheikh)
+// Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
+//
+// Based on Kaldi (latbin/lattice-mbr-decode.cc)
+
+// Copyright 2012 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 "util/common-utils.h"
+#include "lat/sausages.h"
+#include "hmm/posterior.h"
+
+int main(int argc, char *argv[]) {
+ try {
+ using namespace kaldi;
+ typedef kaldi::int32 int32;
+
+ const char *usage =
+ "Do Minimum Bayes Risk decoding (decoding that aims to minimize the \n"
+ "expected word error rate). Possible outputs include the 1-best path\n"
+ "(i.e. the word-sequence, as a sequence of ints per utterance), the\n"
+ "computed Bayes Risk for each utterance, and the sausage stats as\n"
+ "(for each utterance) std::vector<std::vector<std::pair<int32, float> > >\n"
+ "for which we use the same I/O routines as for posteriors (type Posterior).\n"
+ "times-wspecifier writes pairs of (start-time, end-time) in frames, for\n"
+ "each sausage position, or for each one-best entry if --one-best-times=true.\n"
+ "Note: use ark:/dev/null or the empty string for unwanted outputs.\n"
+ "Note: times will only be very meaningful if you first use lattice-word-align.\n"
+ "If you need ctm-format output, don't use this program but use lattice-to-ctm-conf\n"
+ "with --decode-mbr=true.\n"
+ "\n"
+ "Usage: lattice-mbr-decode [options] lattice-rspecifier "
+ "transcriptions-wspecifier [ bayes-risk-wspecifier "
+ "[ sausage-stats-wspecifier [ times-wspecifier] ] ] \n"
+ " e.g.: lattice-mbr-decode --acoustic-scale=0.1 ark:1.lats "
+ "'ark,t:|int2sym.pl -f 2- words.txt > text' ark:/dev/null ark:1.sau\n";
+
+ ParseOptions po(usage);
+ BaseFloat acoustic_scale = 1.0;
+ BaseFloat lm_scale = 1.0;
+ bool one_best_times = false;
+
+ std::string word_syms_filename;
+ po.Register("acoustic-scale", &acoustic_scale, "Scaling factor for "
+ "acoustic likelihoods");
+ po.Register("lm-scale", &lm_scale, "Scaling factor for language model "
+ "probabilities");
+ po.Register("word-symbol-table", &word_syms_filename, "Symbol table for "
+ "words [for debug output]");
+ po.Register("one-best-times", &one_best_times, "If true, output times "
+ "corresponding to one-best, not whole sausage.");
+
+ po.Read(argc, argv);
+
+ if (po.NumArgs() < 2 || po.NumArgs() > 5) {
+ po.PrintUsage();
+ exit(1);
+ }
+
+ std::string lats_rspecifier = po.GetArg(1),
+ trans_wspecifier = po.GetArg(2),
+ bayes_risk_wspecifier = po.GetOptArg(3),
+ sausage_stats_wspecifier = po.GetOptArg(4),
+ times_wspecifier = po.GetOptArg(5);
+
+ // Read as compact lattice.
+ SequentialCompactLatticeReader clat_reader(lats_rspecifier);
+
+ Int32VectorWriter trans_writer(trans_wspecifier);
+ BaseFloatWriter bayes_risk_writer(bayes_risk_wspecifier);
+ // Note: type Posterior = vector<vector<pair<int32,BaseFloat> > >
+ // happens to be the same as needed for the sausage stats.
+ PosteriorWriter sausage_stats_writer(sausage_stats_wspecifier);
+
+ BaseFloatPairVectorWriter times_writer(times_wspecifier);
+
+ fst::SymbolTable *word_syms = NULL;
+ if (word_syms_filename != "")
+ if (!(word_syms = fst::SymbolTable::ReadText(word_syms_filename)))
+ KALDI_ERR << "Could not read symbol table from file "
+ << word_syms_filename;
+
+ int32 n_done = 0, n_words = 0;
+ BaseFloat tot_bayes_risk = 0.0;
+
+ for (; !clat_reader.Done(); clat_reader.Next()) {
+ std::string key = clat_reader.Key();
+ CompactLattice clat = clat_reader.Value();
+ clat_reader.FreeCurrent();
+ fst::ScaleLattice(fst::LatticeScale(lm_scale, acoustic_scale), &clat);
+
+ MinimumBayesRisk mbr(clat);
+
+ if (trans_wspecifier != "")
+ trans_writer.Write(key, mbr.GetOneBest());
+ if (bayes_risk_wspecifier != "")
+ bayes_risk_writer.Write(key, mbr.GetBayesRisk());
+ if (sausage_stats_wspecifier != "")
+ sausage_stats_writer.Write(key, mbr.GetSausageStats());
+ if (times_wspecifier != ""){
+ //times_writer.Write(key, one_best_times ? mbr.GetOneBestTimes() :
+ // mbr.GetSausageTimes());
+ std::vector<std::vector<std::pair<BaseFloat, BaseFloat>>> wtimes = mbr.GetTimes();
+ for(int i=0;i<wtimes.size();i++){
+ KALDI_LOG<<key<<" "<<i<<" "<<wtimes[i].size();
+ times_writer.Write(key + "_" + std::to_string(i), wtimes[i]);
+ }
+ }
+ n_done++;
+ n_words += mbr.GetOneBest().size();
+ tot_bayes_risk += mbr.GetBayesRisk();
+ }
+
+ KALDI_LOG << "Done " << n_done << " lattices.";
+ KALDI_LOG << "Average Bayes Risk per sentence is "
+ << (tot_bayes_risk / n_done) << " and per word, "
+ << (tot_bayes_risk / n_words);
+
+ delete word_syms;
+ return (n_done != 0 ? 0 : 1);
+ } catch(const std::exception &e) {
+ std::cerr << e.what();
+ return -1;
+ }
+}