Nippon Telegraph and Telephone Corporation

Ko Mitsuda

Junji Tomita

Ryuichiro Higashinaka

Taichi Katayama

Atsushi Otsuka

Kuniko Saito

Yushi Aono

An expanded utterance that is used to output a more appropriate output utterance for an utterance can be generated. An utterance sentence expansion device includes an expansion unit that inserts, for an utterance that is an utterance to be expanded that includes a noun and is morphologically analyzed in advance, by using information of an expansion dictionary, which includes higher-level categories of the noun, one or more higher-level categories of the expansion dictionary corresponding to the noun included in the utterance into a position before the noun of the utterance to generate an expanded utterance.

Utterance sentence extension apparatus, utterance sentence generator apparatus, utterance sentence extension method, and program

A generation apparatusincludes: an argumentative scheme adding unitwhich adds an argumentative scheme with respect to pair data constituted by an input utterance and a counter utterancethat voices a negative opinion with respect to the input utterance and which generates argumentative scheme-added pair data; a generation model learning unitwhich learns a generation model for generating a counter utterance from an input utterance in consideration of the argumentative scheme by using the argumentative scheme-added pair dataas learning data and which generates a learned counter utterance generation model; and a counter utterance generating unitwhich acquires an input utterance of a user and a designated argumentative scheme and which outputs a counter utterance using the counter utterance generation model

Generating device, generating method, and program

To make it possible to generate dialogue data for generating a question sentence to deeply delve conversation at a low cost. For each of a plurality of pieces of data each including a set of a first utterance sentence that is a sentence uttered by a first user, a second utterance sentence that is a sentence uttered by a second user and is a response to the first utterance sentence, and a third utterance sentence that is a sentence uttered by the first user and is a response to the second utterance sentence, a dialogue data generation unitgenerates a set of the first utterance sentence of the data and the second utterance sentence of the data as dialogue data when the second utterance sentence of the data is a question sentence using an interrogative.

Dialogue data generation device, dialogue data generation method, and program

Acquisition of an utterance pair for expanding a set of utterance pairs for outputting an output utterance in response to receiving a given utterance is described. A keyword extraction unit is configured to compare a degree of characteristic of a word in expansion source utterance pair data and a degree of characteristics of a word in the given utterance data. The expansion source utterance pair data represents a set of expansion source utterance pairs including an input utterance and an output utterance for the input utterance. The present technology includes extracting, based on a comparison result, a keyword list including a keyword that is characteristic of the expansion source utterance pair data. An utterance pair extraction unit is configured to extract, based on the keyword list, an utterance pair from a set of given utterance pairs as an addition for expanding the set of utterance pairs.

Utterance pair acquisition apparatus, utterance pair acquisition method, and program

It is possible to ask an appropriate question for digging an utterance of the other party in depth. An interrogative search unit estimates an estimated used interrogative with a text, which is an utterance sentence, as an input, by using a predetermined rule or an estimator that has already learned, the estimated used interrogative being an interrogative related to the text. A candidate utterance sentence generation unit generates each of candidate utterance sentences for the utterance sentence with the text as an input through automatic utterance generation. Based on each of the candidate utterance sentences and an estimation result of the estimated used interrogative, a ranking unit ranks the candidate utterance sentenced, based on the scored.

Utterance generation device, method, and program

Provided are a dialogue device, a dialogue method, a data structure, and a program capable of realizing various dialogues while reducing the amount of description of a dialogue scenario. A knowledge transition unitdetermines a next type of knowledge based on: a knowledge basein which a relation label indicating each of relations between a plurality of types of knowledge is attached to knowledge about each of utterances to express the knowledge about the utterance; a user utterance; current knowledge; and a dialogue scenario including a basic scenario in which a transition method between the plurality of types of knowledge in the knowledge base is determined using the relation label, and an utterance generation unitgenerates a system utterance based on the next type of knowledge.

Dialog device, dialog method, data structure, and program

An argumentation structure can be automatically extended. A template creation unitcreates a template using a predetermined rewriting pattern by receiving, as an input, a proposition represented by each of nodes in an argumentation structure including the nodes respectively representing a main proposition of argumentation and a proposition that functions as an argument for another proposition. An additional proposition output unitcreates a proposition functioning as an argument for the input proposition using the created template and outputs the created proposition as a proposition represented by a node to be added to the argumentation structure.

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Tokyo, Japan

Ko Mitsuda