// gmmbin/gmm-make-regtree.cc // Copyright 2009-2011 Saarland University; Microsoft Corporation // 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/kaldi-io.h" #include "util/text-utils.h" #include "gmm/mle-am-diag-gmm.h" #include "tree/context-dep.h" #include "hmm/transition-model.h" #include "transform/regression-tree.h" int main(int argc, char *argv[]) { try { typedef kaldi::int32 int32; typedef kaldi::BaseFloat BaseFloat; const char *usage = "Build regression class tree.\n" "Usage: gmm-make-regtree [options] \n" "E.g.: gmm-make-regtree --silphones=1:2:3 --state-occs=1.occs 1.mdl 1.regtree\n" " [Note: state-occs come from --write-occs option of gmm-est]\n"; std::string occs_in_filename; std::string sil_phones_str; bool binary_write = true; int32 max_leaves = 1; kaldi::ParseOptions po(usage); po.Register("state-occs", &occs_in_filename, "File containing state occupancies (use --write-occs in gmm-est)"); po.Register("sil-phones", &sil_phones_str, "Colon-separated list of integer ids of silence phones, e.g. 1:2:3; if used, create top-level speech/sil split (only one reg-class for silence)."); po.Register("binary", &binary_write, "Write output in binary mode"); po.Register("max-leaves", &max_leaves, "Maximum number of leaves in regression tree."); po.Read(argc, argv); if (po.NumArgs() != 2) { po.PrintUsage(); exit(1); } std::string model_in_filename = po.GetArg(1), tree_out_filename = po.GetArg(2); kaldi::AmDiagGmm am_gmm; kaldi::TransitionModel trans_model; { bool binary_read; kaldi::Input ki(model_in_filename, &binary_read); trans_model.Read(ki.Stream(), binary_read); am_gmm.Read(ki.Stream(), binary_read); } kaldi::Vector state_occs; if (occs_in_filename != "") { bool binary_read; kaldi::Input ki(occs_in_filename, &binary_read); state_occs.Read(ki.Stream(), binary_read); } else { KALDI_LOG << "--state-occs option not provided so using constant occupancies."; state_occs.Resize(am_gmm.NumPdfs()); state_occs.Set(1.0); } std::vector sil_pdfs; if (sil_phones_str != "") { std::vector sil_phones; if (!kaldi::SplitStringToIntegers(sil_phones_str, ":", false, &sil_phones)) KALDI_ERR << "invalid sil-phones option " << sil_phones_str; std::sort(sil_phones.begin(), sil_phones.end()); bool ans = GetPdfsForPhones(trans_model, sil_phones, &sil_pdfs); if (!ans) KALDI_WARN << "Pdfs associated with silence phones are not only " "associated with silence phones: your speech-silence split " "may not be meaningful."; } kaldi::RegressionTree regtree; regtree.BuildTree(state_occs, sil_pdfs, am_gmm, max_leaves); // Write out the regression tree { kaldi::Output ko(tree_out_filename, binary_write); regtree.Write(ko.Stream(), binary_write); } KALDI_LOG << "Written regression tree to " << tree_out_filename; } catch(const std::exception &e) { std::cerr << e.what() << '\n'; return -1; } }