Abstract: An articulation abnormality detection method includes: calculating an acoustic feature from utterance data of a speaker; calculating, from the acoustic feature, a first speaker feature indicating a speaker characteristic of the utterance data by using a trained deep neural network (DNN); calculating a degree of similarity between a second speaker feature of the speaker and the first speaker feature, where the second speaker feature is a speaker feature obtained when the speaker articulated properly; and determining whether the speaker has an articulation abnormality, based on the degree of similarity.

Abstract: An utterer identification device executes: performing voice recognition from input utterance data; selecting, from among a plurality of registered utterance contents set in advance, a registered utterance content closest to a recognized utterance content indicated by a result of the voice recognition as a selected utterance content; selecting, from among a plurality of databases respectively associated with the registered utterance contents, a database associated with the selected utterance content; calculating a similarity between a feature quantity of the input utterance data and a feature quantity stored in the selected database; and identifying a certain utterer on the basis of the similarity, and outputting a result of the identification.

Abstract: A voice recognition device includes an estimation unit that compares a plurality of pieces of registration voice data stored in a database with input voice data uttered by a speaker who gets on a mobile body to estimate a registration command corresponding to the input command, a presentation unit that presents an estimation result, a second acquisition unit that acquires an error instruction indicating that the estimation result is an error, a determination unit that, in a case where the error instruction is acquired, determines a correct command corresponding to the input command based on an operation by the speaker, and a database management unit that stores the correct command and the input voice data in the database in association with each other

Abstract: A voice recognition device includes: a calculation unit that calculates a first feature amount that is a feature amount of input voice data acquired by a first acquisition unit; an estimation unit that estimates a driving situation of a mobile object on the basis of operation information acquired by a second acquisition unit; an extraction unit that extracts, from a feature amount database, a second feature amount corresponding to the driving situation; a recognition unit that recognizes an input command on the basis of similarity between the first feature amount and the second feature amount; and an output unit that outputs a recognition result.

Abstract: An aerosol quantity estimation method includes: determining whether a sound pressure level of a spoken voice of a speaker is higher than a predetermined sound pressure level; calculating an acoustic feature from speech data of the spoken voice of the speaker when the sound pressure level of the spoken voice is higher than the predetermined sound pressure level; calculating a first speaker feature from the acoustic feature by using a trained model, the first speaker feature representing a speaker characteristic of the speech data; calculating a similarity between the first speaker feature and a second speaker feature that is a speaker feature of the speaker when in a calm state; and estimating a quantity of aerosols generated by the speaker, the quantity of aerosols corresponding to the similarity.

Abstract: An action identification device acquires sound data from a microphone, calculates a feature amount of the sound data, determines whether or not a user is present in a space in which the microphone is installed, calculates a noise feature amount indicating a feature amount of noise based on the calculated feature amount and stores the calculated noise feature amount in a noise feature amount storage unit in a case where the user is not present in the space, subtracts the noise feature amount stored in the noise feature amount storage unit from the calculated feature amount to extract an action sound feature amount indicating a feature amount of an action sound generated by an action of the user in a case where the user is present in the space, and identifies an action of the user by using the action sound feature amount.

Abstract: A speaker identification apparatus that identifies a speaker of utterance data indicating a voice of an utterance subjected to identification includes: an emotion estimator that estimates, from an acoustic feature value calculated from the utterance data, an emotion contained in the voice of the utterance indicated by the utterance data, using a trained deep neural network (DNN); and a speaker identification processor that outputs, based on the acoustic feature value calculated from the utterance data, a score for identifying the speaker of the utterance data, using an estimation result of the emotion estimator.

Abstract: A cough detection device including: an acoustic feature extractor that extracts at least one acoustic feature from acoustic data output by a microphone array according to a sound received; a first identifier that performs identification of the sound based on the at least one acoustic feature to determine whether the sound is a cough sound; a direction estimator that estimates an arrival direction of the sound from the acoustic data; an image selector that selects, from first image data indicating an image obtained by capturing a scene in which the sound occurs, second image data indicating an area corresponding to the arrival direction estimated; and a second identifier that performs identification of the image based on the second image data to determine whether a coughing action is shown in the image.

Abstract: A cough detection device including: an acoustic feature extractor that extracts at least one acoustic feature from acoustic data output by a microphone array according to a sound received; a first identifier that performs identification of the sound based on the at least one acoustic feature to determine whether the sound is a cough sound; a direction estimator that estimates an arrival direction of the sound from the acoustic data; an image selector that selects, from first image data indicating an image obtained by capturing a scene in which the sound occurs, second image data indicating an area corresponding to the arrival direction estimated; and a second identifier that performs identification of the image based on the second image data to determine whether a coughing action is shown in the image.