Mitsubishi Electric Corporation

Yoichi Fujii

Jun Ishii

Keisuke Watanabe

Yusuke Koji

Yi Jing

A dialog management unit () selects a response template corresponding to a dialog state with a user and outputs a term symbol included in the response template to a comprehension level estimating unit (). The comprehension level estimating unit () outputs the user's comprehension level of the input term symbol to the dialog management unit (). A response generating unit () generates a response sentence on the basis of the response template selected by the dialog management unit (), adds an explanatory sentence to the response sentence depending on the user's comprehension level of the term input from the dialog management unit (), and outputs the response sentence.

Response generation device, dialog control system, and response generation method

A voice recognizergenerates plural voice recognition results from one input speech. For each of the voice recognition results, an intent understanding processorestimates an intent to thereby output one or more candidates of intent understanding results and scores of them. A weight calculatorcalculates standby weights using setting informationof a control target apparatus. An intent understanding correctorcorrects the scores of the candidates of intent understanding result, using the standby weights, to thereby calculate their final scores, and then selects one from among the candidates of intent understanding result, as an intent understanding result, on the basis of the final scores.

Device and method for understanding user intent

An intention estimation unit extractor that extracts one or more intention estimation units each of which is a unit on which an estimation of the intention is to be performed from an inputted language, an intention estimator that estimates a partial intention of a part which constructs each of the extracted intention estimation units, an intention co-occurrence weight calculator that calculates an intention co-occurrence weight based on a relationship between partial intentions, and an intention sequence estimator that generates an intention sequence corresponding to the inputted language by using one or more partial intentions, and generates an intention estimation result corresponding to the inputted language by using both a score showing a likelihood of the generated intention sequence and an intention co-occurrence weight which the intention co-occurrence weight calculator calculates for the partial intentions which construct the generated intention sequence are disposed.

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Tokyo, Japan

Yoichi Fujii