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93 lines
2.2 KiB
93 lines
2.2 KiB
#include <iostream>
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#include "scorer.h"
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#include "lm/model.hh"
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#include "util/tokenize_piece.hh"
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#include "util/string_piece.hh"
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using namespace lm::ngram;
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Scorer::Scorer(float alpha, float beta, std::string lm_model_path) {
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this->_alpha = alpha;
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this->_beta = beta;
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this->_language_model = new Model(lm_model_path.c_str());
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}
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Scorer::~Scorer(){
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delete (Model *)this->_language_model;
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}
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/* Strip a input sentence
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* Parameters:
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* str: A reference to the objective string
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* ch: The character to prune
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* Return:
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* void
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*/
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inline void strip(std::string &str, char ch=' ') {
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if (str.size() == 0) return;
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int start = 0;
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int end = str.size()-1;
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for (int i=0; i<str.size(); i++){
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if (str[i] == ch) {
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start ++;
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} else {
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break;
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}
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}
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for (int i=str.size()-1; i>=0; i--) {
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if (str[i] == ch) {
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end --;
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} else {
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break;
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}
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}
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if (start == 0 && end == str.size()-1) return;
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if (start > end) {
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std::string emp_str;
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str = emp_str;
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} else {
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str = str.substr(start, end-start+1);
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}
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}
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int Scorer::word_count(std::string sentence) {
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strip(sentence);
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int cnt = 1;
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for (int i=0; i<sentence.size(); i++) {
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if (sentence[i] == ' ' && sentence[i-1] != ' ') {
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cnt ++;
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}
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}
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return cnt;
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}
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double Scorer::language_model_score(std::string sentence) {
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Model *model = (Model *)this->_language_model;
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State state, out_state;
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lm::FullScoreReturn ret;
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state = model->BeginSentenceState();
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for (util::TokenIter<util::SingleCharacter, true> it(sentence, ' '); it; ++it){
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lm::WordIndex vocab = model->GetVocabulary().Index(*it);
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ret = model->FullScore(state, vocab, out_state);
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state = out_state;
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}
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//log10 prob
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double log_prob = ret.prob;
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return log_prob;
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}
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void Scorer::reset_params(float alpha, float beta) {
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this->_alpha = alpha;
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this->_beta = beta;
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}
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double Scorer::get_score(std::string sentence) {
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double lm_score = language_model_score(sentence);
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int word_cnt = word_count(sentence);
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double final_score = pow(10, _alpha*lm_score) * pow(word_cnt, _beta);
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return final_score;
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}
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