Nippon Telegraph and Telephone Corporation

Taichi Katayama

Junji Tomita

Ryuichiro Higashinaka

Kyosuke Nishida

Ko Mitsuda

Nozomi Kobayashi

Ryo Ishii

Atsushi Otsuka

Kuniko Saito

Yuichiro Sekiguchi

Satoshi Mieda

A nonverbal information generation apparatus includes a nonverbal information generation unit that generates time-information-stamped nonverbal information that corresponds to time-information-stamped text feature quantities on the basis of the time-information-stamped text feature quantities and a learned nonverbal information generation model. The time-information-stamped text feature quantities are configured to include feature quantities that have been extracted from text and time information representing times assigned to predetermined units of the text. The nonverbal information is information for controlling an expression unit that expresses behavior that corresponds to the text.

Nonverbal information generation apparatus, nonverbal information generation model learning apparatus, methods, and programs

A FAQ maintenance support deviceincludes a question determining unitto extract determined question items determined as question items of a customer, from contents of an inquiry from the customer and a response to the customer; a query log extracting unitto extract search queries, which corresponds to the question items of the customer stored in a FAQ search system and have been determined such that all FAQ as search results for the search query are useless for the customer; and a maintenance question candidate extracting unitto perform clustering with elements of question items of FAQ registered in the FAQ search system, the determined question items, and the search queries, and based on the clustering result, extract a candidate question item of FAQ to be maintained, and thereby, maintenance such as addition and deletion of FAQ can be performed easily.

Faq consolidation assistance device, faq consolidation assistance method, and program

A nonverbal information generation apparatus includes a display unit that partitions text into predetermined units, displays the text partitioned into the predetermined units, and makes nonverbal information that represents information about behavior of a verbal output agent or nonverbal information that represents information about behavior of a receiver of verbal information of the verbal output agent that corresponds to the text when the verbal output agent outputs the verbal information visible in association with the predetermined units of the text.

Nonverbal information generation apparatus, 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

A nonverbal information generation apparatus includes a nonverbal information generation unit that generates time-information-stamped nonverbal information that corresponds to time-information-stamped text feature quantities and an expression unit that expresses the nonverbal information on the basis of the time-information-stamped text feature quantities and a learned nonverbal information generation model. The time-information-stamped text feature quantities are configured to include feature quantities that have been extracted from text and time information representing times assigned to predetermined units of the text. The nonverbal information is information for controlling the expression unit so as to express behavior corresponding to the text. The nonverbal information generation unit controls the expression unit so that the time-information-stamped nonverbal information is expressed from the expression unit in accordance with time information assigned to the nonverbal information, and controls the expression unit so that the text or voice corresponding to the text that corresponds to the time information is output.

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Tokyo, Japan

Taichi Katayama