Abstract: 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.

Abstract: 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 unit 117 determines, based on an analysis result of a speech sentence analyzed by a speech-content analyzing unit 112, 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 unit 119 generates the response sentence based on the response type and a response sentence database.

Abstract: To enable accurate estimation of a dialogue act type taking utterance subject into account. A feature value extraction unit 130 extracts feature values including an utterance subject feature value which is a feature value related to an utterance subject of an utterance sentence for each of a first utterance sentence and a second utterance sentence, the second utterance sentence being an utterance sentence preceding the first utterance sentence, including at least the utterance sentence immediately preceding the first utterance sentence. A dialogue act estimation unit 260 estimates a dialogue act type of the first utterance sentence using the aggregate feature value generated by aggregating the extracted feature values for each of the first utterance sentence and the second utterance sentence and a previously learned dialogue act estimation model for estimating the dialogue act type indicating a kind of dialogue act taking into account the utterance subject of an utterance sentence.

Abstract: 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 unit 110 generates 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.

Abstract: 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.

Abstract: 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 unit 117 determines, based on an analysis result of a speech sentence analyzed by a speech-content analyzing unit 112, 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 unit 119 generates the response sentence based on the response type and a response sentence database.