Nippon Telegraph and Telephone Corporation

Nozomi Kobayashi

Junji Tomita

Kyosuke Nishida

Ryuichiro Higashinaka

Taichi Katayama

Ryo Ishii

Kuniko Saito

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 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

It is an object to successfully absorb a difference in characteristics to be taken into consideration between languages and implement common named entity extraction in a processing system. A language characteristic extraction deviceincludes a language characteristic extraction unit that selects an abstract rule corresponding to a characteristic of a target language from among a collection of abstract rules common to a plurality of languages and sets, as a language-specific characteristic extraction rule, a concrete feature extraction method suited to the target language and a definition given as an output condition, defines, for each of a plurality of target languages, the language-specific characteristic extraction rule, and extracts a feature corresponding to a language of an input sentence from a morphological analysis result of the input sentence while referring to the language-specific characteristic extraction rule defined for the language and aimed at extracting a feature related to a representation or a part of speech included in the morphological analysis result and outputs the feature as a language characteristic extraction result.

Language characteristic extraction device, named entity extraction device, extraction method, and program

To make it possible to generate a response sentence with respect to an input speech sentence without preparing a large amount of data. A response-type determining unitdetermines, based on an analysis result of a speech sentence analyzed by a speech-content analyzing unit, a speech type indicating a type of the speech sentence and determines a response type with respect to the determined speech type based on the speech type and a type conversion rule prescribing, for each speech type, a rule for a response type with respect to a speech of the speech type. A response-sentence generating unitgenerates the response sentence based on the response type and a response sentence database.

Response sentence generation device, response sentence generation method, 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

Nozomi Kobayashi