DIALOGUE LEARNING APPARATUS, DIALOGUE ANALYZER, DIALOGUE LEARNING METHOD, DIALOGUE ANALYSIS METHOD, AND PROGRAM

摘要

PROBLEM TO BE SOLVED: To dispense with data formed by previously labeling satisfaction for every dialogue action; and to evaluate the satisfaction for every dialogue action in the dialogue.

SOLUTION: A dialogue learning apparatus learns hidden Markov models M1, ..., MKhaving such a state as outputting dialogue actions of a speaker for every evaluation phase. Alternatively, the dialogue learning apparatus may learn a hidden Markov model M0having such a state as outputting the dialogue actions of the speaker from all dialogues. All the states of the hidden Markov models (M0,) M1, ..., MKare connected together to create a hidden Markov model MC. Likelihood may be improved by repeating the learning. A dialogue analyzer of the present invention obtains an evaluation value of each dialogue action by estimating from which evaluation value state of the hidden Markov model MCthe dialogue action is output using the hidden Markov model MC, and estimates the evaluation value of the dialogue.

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