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Diffstat (limited to 'kaldi_io/src/kaldi/util/edit-distance-inl.h')
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1 files changed, 0 insertions, 189 deletions
diff --git a/kaldi_io/src/kaldi/util/edit-distance-inl.h b/kaldi_io/src/kaldi/util/edit-distance-inl.h deleted file mode 100644 index ebbfb71..0000000 --- a/kaldi_io/src/kaldi/util/edit-distance-inl.h +++ /dev/null @@ -1,189 +0,0 @@ -// util/edit-distance-inl.h - -// Copyright 2009-2011 Microsoft Corporation; Haihua Xu; Yanmin Qian - -// 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_UTIL_EDIT_DISTANCE_INL_H_ -#define KALDI_UTIL_EDIT_DISTANCE_INL_H_ -#include "util/stl-utils.h" - - -namespace kaldi { - -template<class T> -int32 LevenshteinEditDistance(const std::vector<T> &a, - const std::vector<T> &b) { - // Algorithm: - // write A and B for the sequences, with elements a_0 .. - // let |A| = M and |B| = N be the lengths, and have - // elements a_0 ... a_{M-1} and b_0 ... b_{N-1}. - // We are computing the recursion - // E(m, n) = min( E(m-1, n-1) + (1-delta(a_{m-1}, b_{n-1})), - // E(m-1, n), - // E(m, n-1) ). - // where E(m, n) is defined for m = 0..M and n = 0..N and out-of- - // bounds quantities are considered to be infinity (i.e. the - // recursion does not visit them). - - // We do this computation using a vector e of size N+1. - // The outer iterations range over m = 0..M. - - int M = a.size(), N = b.size(); - std::vector<int32> e(N+1); - std::vector<int32> e_tmp(N+1); - // initialize e. - for (size_t i = 0; i < e.size(); i++) - e[i] = i; - for (int32 m = 1; m <= M; m++) { - // computing E(m, .) from E(m-1, .) - // handle special case n = 0: - e_tmp[0] = e[0] + 1; - - for (int32 n = 1; n <= N; n++) { - int32 term1 = e[n-1] + (a[m-1] == b[n-1] ? 0 : 1); - int32 term2 = e[n] + 1; - int32 term3 = e_tmp[n-1] + 1; - e_tmp[n] = std::min(term1, std::min(term2, term3)); - } - e = e_tmp; - } - return e.back(); -} -// -struct error_stats{ - int32 ins_num; - int32 del_num; - int32 sub_num; - int32 total_cost; // minimum total cost to the current alignment. -}; -// Note that both hyp and ref should not contain noise word in -// the following implementation. - -template<class T> -int32 LevenshteinEditDistance(const std::vector<T> &ref, - const std::vector<T> &hyp, - int32 *ins, int32 *del, int32 *sub) { - // temp sequence to remember error type and stats. - std::vector<error_stats> e(ref.size()+1); - std::vector<error_stats> cur_e(ref.size()+1); - // initialize the first hypothesis aligned to the reference at each - // position:[hyp_index =0][ref_index] - for (size_t i =0; i < e.size(); i ++) { - e[i].ins_num = 0; - e[i].sub_num = 0; - e[i].del_num = i; - e[i].total_cost = i; - } - - // for other alignments - for (size_t hyp_index = 1; hyp_index <= hyp.size(); hyp_index ++) { - cur_e[0] = e[0]; - cur_e[0].ins_num ++; - cur_e[0].total_cost ++; - for (size_t ref_index = 1; ref_index <= ref.size(); ref_index ++) { - - int32 ins_err = e[ref_index].total_cost + 1; - int32 del_err = cur_e[ref_index-1].total_cost + 1; - int32 sub_err = e[ref_index-1].total_cost; - if (hyp[hyp_index-1] != ref[ref_index-1]) - sub_err ++; - - if (sub_err < ins_err && sub_err < del_err) { - cur_e[ref_index] =e[ref_index-1]; - if (hyp[hyp_index-1] != ref[ref_index-1]) - cur_e[ref_index].sub_num ++; // substitution error should be increased - cur_e[ref_index].total_cost = sub_err; - }else if (del_err < ins_err ) { - cur_e[ref_index] = cur_e[ref_index-1]; - cur_e[ref_index].total_cost = del_err; - cur_e[ref_index].del_num ++; // deletion number is increased. - }else{ - cur_e[ref_index] = e[ref_index]; - cur_e[ref_index].total_cost = ins_err; - cur_e[ref_index].ins_num ++; // insertion number is increased. - } - } - e = cur_e; // alternate for the next recursion. - } - size_t ref_index = e.size()-1; - *ins = e[ref_index].ins_num, *del = e[ref_index].del_num, *sub = e[ref_index].sub_num; - return e[ref_index].total_cost; -} - -template<class T> -int32 LevenshteinAlignment(const std::vector<T> &a, - const std::vector<T> &b, - T eps_symbol, - std::vector<std::pair<T, T> > *output) { - // Check inputs: - { - KALDI_ASSERT(output != NULL); - for (size_t i = 0; i < a.size(); i++) KALDI_ASSERT(a[i] != eps_symbol); - for (size_t i = 0; i < b.size(); i++) KALDI_ASSERT(b[i] != eps_symbol); - } - output->clear(); - // This is very memory-inefficiently implemented using a vector of vectors. - size_t M = a.size(), N = b.size(); - size_t m, n; - std::vector<std::vector<int32> > e(M+1); - for (m = 0; m <=M; m++) e[m].resize(N+1); - for (n = 0; n <= N; n++) - e[0][n] = n; - for (m = 1; m <= M; m++) { - e[m][0] = e[m-1][0] + 1; - for (n = 1; n <= N; n++) { - int32 sub_or_ok = e[m-1][n-1] + (a[m-1] == b[n-1] ? 0 : 1); - int32 del = e[m-1][n] + 1; // assumes a == ref, b == hyp. - int32 ins = e[m][n-1] + 1; - e[m][n] = std::min(sub_or_ok, std::min(del, ins)); - } - } - // get time-reversed output first: trace back. - m = M; n = N; - while (m != 0 || n != 0) { - size_t last_m, last_n; - if (m == 0) { last_m = m; last_n = n-1; } - else if (n == 0) { last_m = m-1; last_n = n; } - else { - int32 sub_or_ok = e[m-1][n-1] + (a[m-1] == b[n-1] ? 0 : 1); - int32 del = e[m-1][n] + 1; // assumes a == ref, b == hyp. - int32 ins = e[m][n-1] + 1; - if (sub_or_ok <= std::min(del, ins)) { // choose sub_or_ok if all else equal. - last_m = m-1; last_n = n-1; - } else { - if (del <= ins) { // choose del over ins if equal. - last_m = m-1; last_n = n; - } else { - last_m = m; last_n = n-1; - } - } - } - T a_sym, b_sym; - a_sym = (last_m == m ? eps_symbol : a[last_m]); - b_sym = (last_n == n ? eps_symbol : b[last_n]); - output->push_back(std::make_pair(a_sym, b_sym)); - m = last_m; - n = last_n; - } - ReverseVector(output); - return e[M][N]; -} - - -} // end namespace kaldi - -#endif // KALDI_UTIL_EDIT_DISTANCE_INL_H_ |