📄 tr_mod_hmm_0.cc
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// file: tr_mod_hmm_0.cc//// isip include files//#include "train_model.h"#include "train_model_constants.h"// method: get_output_prob_cc//// arguments:// int_4 state : (input) the state index for which probability is reqd// float_8* data : (input) the acoustic data feature vector// int_4 frame : (input) the current frame index// int_4& max_mix : (output) the index of the highest mixture corresponding// to the current input state//// return: float_8 giving the output probability for the given observation//// this methods returns float_8 giving the observation probability for// the specified state//float_8 Train_Model::get_output_prob_cc(int_4 state_a, float_8* data_a, int_4 frame_a, int_4& max_mix_a) { // dummy variables // float_8 score = (float_8)0; // evaluate if appropriate // if ((state_a > (int_4)0) && (state_a < num_states_d)) { score = states_d[state_a]->eval_score_cc(data_a, frame_a, max_mix_a); } // return the output probability // return score;}
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