// tree/build-tree.h // Copyright 2009-2011 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. #ifndef KALDI_TREE_BUILD_TREE_H_ #define KALDI_TREE_BUILD_TREE_H_ // The file build-tree.h contains outer-level routines used in tree-building // and related tasks, that are directly called by the command-line tools. #include "tree/build-tree-utils.h" #include "tree/context-dep.h" namespace kaldi { /// \defgroup tree_group_top Top-level tree-building functions /// See \ref tree_internals for context. /// \ingroup tree_group /// @{ // Note, in tree_group_top we also include AccumulateTreeStats, in // ../hmm/tree-accu.h (it has some extra dependencies so we didn't // want to include it here). /** * BuildTree is the normal way to build a set of decision trees. * The sets "phone_sets" dictate how we set up the roots of the decision trees. * each set of phones phone_sets[i] has shared decision-tree roots, and if * the corresponding variable share_roots[i] is true, the root will be shared * for the different HMM-positions in the phone. All phones in "phone_sets" * should be in the stats (use FixUnseenPhones to ensure this). * if for any i, do_split[i] is false, we will not do any tree splitting for * phones in that set. * @param qopts [in] Questions options class, contains questions for each key * (e.g. each phone position) * @param phone_sets [in] Each element of phone_sets is a set of phones whose * roots are shared together (prior to decision-tree splitting). * @param phone2num_pdf_classes [in] A map from phones to the number of * \ref pdf_class "pdf-classes" * in the phone (this info is derived from the HmmTopology object) * @param share_roots [in] A vector the same size as phone_sets; says for each * phone set whether the root should be shared among all the * pdf-classes or not. * @param do_split [in] A vector the same size as phone_sets; says for each * phone set whether decision-tree splitting should be done * (generally true for non-silence phones). * @param stats [in] The statistics used in tree-building. * @param thresh [in] Threshold used in decision-tree splitting (e.g. 1000), * or you may use 0 in which case max_leaves becomes the * constraint. * @param max_leaves [in] Maximum number of leaves it will create; set this * to a large number if you want to just specify "thresh". * @param cluster_thresh [in] Threshold for clustering leaves after decision-tree * splitting (only within each phone-set); leaves will be combined * if log-likelihood change is less than this. A value about equal * to "thresh" is suitable * if thresh != 0; otherwise, zero will mean no clustering is done, * or a negative value (e.g. -1) sets it to the smallest likelihood * change seen during the splitting algorithm; this typically causes * about a 20% reduction in the number of leaves. * @param P [in] The central position of the phone context window, e.g. 1 for a * triphone system. * @return Returns a pointer to an EventMap object that is the tree. */ EventMap *BuildTree(Questions &qopts, const std::vector > &phone_sets, const std::vector &phone2num_pdf_classes, const std::vector &share_roots, const std::vector &do_split, const BuildTreeStatsType &stats, BaseFloat thresh, int32 max_leaves, BaseFloat cluster_thresh, // typically == thresh. If negative, use smallest split. int32 P); /** * * BuildTreeTwoLevel builds a two-level tree, useful for example in building tied mixture * systems with multiple codebooks. It first builds a small tree by splitting to * "max_leaves_first". It then splits at the leaves of "max_leaves_first" (think of this * as creating multiple little trees at the leaves of the first tree), until the total * number of leaves reaches "max_leaves_second". It then outputs the second tree, along * with a mapping from the leaf-ids of the second tree to the leaf-ids of the first tree. * Note that the interface is similar to BuildTree, and in fact it calls BuildTree * internally. * * The sets "phone_sets" dictate how we set up the roots of the decision trees. * each set of phones phone_sets[i] has shared decision-tree roots, and if * the corresponding variable share_roots[i] is true, the root will be shared * for the different HMM-positions in the phone. All phones in "phone_sets" * should be in the stats (use FixUnseenPhones to ensure this). * if for any i, do_split[i] is false, we will not do any tree splitting for * phones in that set. * * @param qopts [in] Questions options class, contains questions for each key * (e.g. each phone position) * @param phone_sets [in] Each element of phone_sets is a set of phones whose * roots are shared together (prior to decision-tree splitting). * @param phone2num_pdf_classes [in] A map from phones to the number of * \ref pdf_class "pdf-classes" * in the phone (this info is derived from the HmmTopology object) * @param share_roots [in] A vector the same size as phone_sets; says for each * phone set whether the root should be shared among all the * pdf-classes or not. * @param do_split [in] A vector the same size as phone_sets; says for each * phone set whether decision-tree splitting should be done * (generally true for non-silence phones). * @param stats [in] The statistics used in tree-building. * @param max_leaves_first [in] Maximum number of leaves it will create in first * level of decision tree. * @param max_leaves_second [in] Maximum number of leaves it will create in second * level of decision tree. Must be > max_leaves_first. * @param cluster_leaves [in] Boolean value; if true, we post-cluster the leaves produced * in the second level of decision-tree split; if false, we don't. * The threshold for post-clustering is the log-like change of the last * decision-tree split; this typically causes about a 20% reduction in * the number of leaves. * @param P [in] The central position of the phone context window, e.g. 1 for a * triphone system. * @param leaf_map [out] Will be set to be a mapping from the leaves of the * "big" tree to the leaves of the "little" tree, which you can * view as cluster centers. * @return Returns a pointer to an EventMap object that is the (big) tree. */ EventMap *BuildTreeTwoLevel(Questions &qopts, const std::vector > &phone_sets, const std::vector &phone2num_pdf_classes, const std::vector &share_roots, const std::vector &do_split, const BuildTreeStatsType &stats, int32 max_leaves_first, int32 max_leaves_second, bool cluster_leaves, int32 P, std::vector *leaf_map); /// GenRandStats generates random statistics of the form used by BuildTree. /// It tries to do so in such a way that they mimic "real" stats. The event keys /// and their corresponding values are: /// - key == -1 == kPdfClass -> pdf-class, generally corresponds to /// zero-based position in HMM (0, 1, 2 .. hmm_lengths[phone]-1) /// - key == 0 -> phone-id of left-most context phone. /// - key == 1 -> phone-id of one-from-left-most context phone. /// - key == P-1 -> phone-id of central phone. /// - key == N-1 -> phone-id of right-most context phone. /// GenRandStats is useful only for testing but it serves to document the format of /// stats used by BuildTreeDefault. /// if is_ctx_dep[phone] is set to false, GenRandStats will not define the keys for /// other than the P-1'th phone. /// @param dim [in] dimension of features. /// @param num_stats [in] approximate number of separate phones-in-context wanted. /// @param N [in] context-size (typically 3) /// @param P [in] central-phone position in zero-based numbering (typically 1) /// @param phone_ids [in] integer ids of phones /// @param hmm_lengths [in] lengths of hmm for phone, indexed by phone. /// @param is_ctx_dep [in] boolean array indexed by phone, saying whether each phone /// is context dependent. /// @param ensure_all_phones_covered [in] Boolean argument: if true, GenRandStats /// ensures that every phone is seen at least once in the central position (P). /// @param stats_out [out] The statistics that this routine outputs. void GenRandStats(int32 dim, int32 num_stats, int32 N, int32 P, const std::vector &phone_ids, const std::vector &hmm_lengths, const std::vector &is_ctx_dep, bool ensure_all_phones_covered, BuildTreeStatsType *stats_out); /// included here because it's used in some tree-building /// calling code. Reads an OpenFst symbl table, /// discards the symbols and outputs the integers void ReadSymbolTableAsIntegers(std::string filename, bool include_eps, std::vector *syms); /** * Outputs sets of phones that are reasonable for questions * to ask in the tree-building algorithm. These are obtained by tree * clustering of the phones; for each node in the tree, all the leaves * accessible from that node form one of the sets of phones. * @param stats [in] The statistics as used for normal tree-building. * @param phone_sets_in [in] All the phones, pre-partitioned into sets. * The output sets will be various unions of these sets. These sets * will normally correspond to "real phones", in cases where the phones * have stress and position markings. * @param all_pdf_classes_in [in] All the \ref pdf_class "pdf-classes" * that we consider for clustering. In the normal case this is the singleton * set {1}, which means that we only consider the central hmm-position * of the standard 3-state HMM, for clustering purposes. * @param P [in] The central position in the phone context window; normally * 1 for triphone system.s * @param questions_out [out] The questions (sets of phones) are output to here. **/ void AutomaticallyObtainQuestions(BuildTreeStatsType &stats, const std::vector > &phone_sets_in, const std::vector &all_pdf_classes_in, int32 P, std::vector > *questions_out); /// This function clusters the phones (or some initially specified sets of phones) /// into sets of phones, using a k-means algorithm. Useful, for example, in building /// simple models for purposes of adaptation. void KMeansClusterPhones(BuildTreeStatsType &stats, const std::vector > &phone_sets_in, const std::vector &all_pdf_classes_in, int32 P, int32 num_classes, std::vector > *sets_out); /// Reads the roots file (throws on error). Format is lines like: /// "shared split 1 2 3 4", /// "not-shared not-split 5", /// and so on. The numbers are indexes of phones. void ReadRootsFile(std::istream &is, std::vector > *phone_sets, std::vector *is_shared_root, std::vector *is_split_root); /// @} }// end namespace kaldi #endif