Abstract: Provided is to prevent a false determination due to an attachment condition of an apparatus that transmits and receives an acoustic signal, and perform accurate personal authentication. A personal authentication device includes: a personal authentication means that authenticates an individual by using first information at least including an acoustic characteristic calculated from an acoustic signal propagating through the head of the user, which is detected by an apparatus being attached on a head of a user for transmitting and receiving the acoustic signal, and a feature amount extracted from the acoustic characteristic; an attachment trouble rule storage means that stores an attachment trouble rule for detecting an attachment trouble with the apparatus; and an attachment trouble detection means that detects a trouble with an attachment state of the apparatus when the first information satisfies the attachment trouble rule.

Abstract: An authentication device is provided with: a plurality of attribute-dependent score calculation units each calculating an attribute-dependent score dependent on a prescribed attribute for input data; an attribute-independent score calculation unit for calculating an attribute-independent score independent of the attribute for the input data; an attribute estimation unit for performing attribute estimation for the input data; and a score integration unit for determining a score weight of each of a plurality of attribute-dependent scores and of the attribute-independent score using the result of the attribute estimation and calculating an output score using the attribute-dependent scores, the attribute-independent score, and the determined score weights.

Abstract: A neural network input unit 81 inputs a neural network in which a first network having a layer for inputting an anchor signal belonging to a predetermined class and a mixed signal including a target signal belonging to the class and a layer for outputting, as an estimation result, a reconstruction mask indicating a time-frequency domain in which the target signal is present in the mixed signal, and a second network having a layer for inputting the target signal extracted by applying the mixed signal to the reconstruction mask and a layer for outputting a result obtained by classifying the input target signal into a predetermined class are combined. A reconstruction mask estimation unit 82 applies the anchor signal and mixed signal to the first network to estimate the reconstruction mask of the class to which the anchor signal belongs.

Abstract: Provided is to prevent a false determination due to an attachment condition of an apparatus that transmits and receives an acoustic signal, and perform accurate personal authentication. A personal authentication device includes: a personal authentication means that authenticates an individual by using first information at least including an acoustic characteristic calculated from an acoustic signal propagating through the head of the user, which is detected by an apparatus being attached on a head of a user for transmitting and receiving the acoustic signal, and a feature amount extracted from the acoustic characteristic; an attachment trouble rule storage means that stores an attachment trouble rule for detecting an attachment trouble with the apparatus; and an attachment trouble detection means that detects a trouble with an attachment state of the apparatus when the first information satisfies the attachment trouble rule.

Abstract: A biometric authentication device is provided with: a replay unit for reproducing a sound; an ear authentication unit for acquiring a reverberation sound of the sound in an ear of a user to be authenticated, extracting an ear acoustic feature from the reverberation sound, and calculating an ear authentication score by comparing the extracted ear acoustic feature with an ear acoustic feature stored in advance; a voice authentication unit for extracting a talker feature from a voice of the user that has been input, and calculating a voice authentication score by comparing the extracted talker feature with a talker feature stored in advance; and an authentication integration unit for outputting an authentication integration result calculated based on the ear authentication score and the voice authentication score. After the sound is output into the ear, a recording unit inputs the voice of the user.

Abstract: A speaker subset selection means 81 selects speakers corresponding to an attribute from subset information of an entire speaker to determine a subset of a speech model from which test utterance is identified. A speaker identification means 82 identifies a speaker of the test utterance from a subset of the determined speech model based on features extracted from the test utterance.

Abstract: A biometric authentication device is provided with: a replay unit for reproducing a sound; an ear authentication unit for acquiring a reverberation sound of the sound in an ear of a user to be authenticated, extracting an ear acoustic feature from the reverberation sound, and calculating an ear authentication score by comparing the extracted ear acoustic feature with an ear acoustic feature stored in advance; a voice authentication unit for extracting a talker feature from a voice of the user that has been input, and calculating a voice authentication score by comparing the extracted talker feature with a talker feature stored in advance; and an authentication integration unit for outputting an authentication integration result calculated based on the ear authentication score and the voice authentication score. After the sound is output into the ear, a recording unit inputs the voice of the user.

Abstract: A biometric authentication device is provided with: a replay unit for reproducing a sound; an ear authentication unit for acquiring a reverberation sound of the sound in an ear of a user to be authenticated, extracting an ear acoustic feature from the reverberation sound, and calculating an ear authentication score by comparing the extracted ear acoustic feature with an ear acoustic feature stored in advance; a voice authentication unit for extracting a talker feature from a voice of the user that has been input, and calculating a voice authentication score by comparing the extracted talker feature with a talker feature stored in advance; and an authentication integration unit for outputting an authentication integration result calculated based on the ear authentication score and the voice authentication score. After the sound is output into the ear, a recording unit inputs the voice of the user.

Abstract: Provided is to prevent a false determination due to an attachment condition of an apparatus that transmits and receives an acoustic signal, and perform accurate personal authentication. A personal authentication device includes: a personal authentication means that authenticates an individual by using first information at least including an acoustic characteristic calculated from an acoustic signal propagating through the head of the user, which is detected by an apparatus being attached on a head of a user for transmitting and receiving the acoustic signal, and a feature amount extracted from the acoustic characteristic; an attachment trouble rule storage means that stores an attachment trouble rule for detecting an attachment trouble with the apparatus; and an attachment trouble detection means that detects a trouble with an attachment state of the apparatus when the first information satisfies the attachment trouble rule.

Abstract: A biometric authentication device is provided with: a replay unit for reproducing a sound; an ear authentication unit for acquiring a reverberation sound of the sound in an ear of a user to be authenticated, extracting an ear acoustic feature from the reverberation sound, and calculating an ear authentication score by comparing the extracted ear acoustic feature with an ear acoustic feature stored in advance; a voice authentication unit for extracting a talker feature from a voice of the user that has been input, and calculating a voice authentication score by comparing the extracted talker feature with a talker feature stored in advance; and an authentication integration unit for outputting an authentication integration result calculated based on the ear authentication score and the voice authentication score. After the sound is output into the ear, a recording unit inputs the voice of the user.

Abstract: Provided is a personal authentication device capable of simply securing security with little psychological and physical burden of a user to be authenticated.

Abstract: A feature vector having high class identification capability is generated. A signal processing system provided with: a first generation unit for generating a first feature vector on the basis of one of time-series voice data, meteorological data, sensor data, and text data, or on the basis of a feature quantity of one of these; a weight calculation unit for calculating a weight for the first feature vector; a statistical amount calculation unit for calculating a weighted average vector and a weighted high-order statistical vector of second or higher order using the first feature vector and the weight; and a second generation unit for generating a second feature vector using the weighted high-order statistical vector.

Abstract: This speech processing device is provided with: a contribution degree estimation means which calculates a contribution degree representing a quality of a segment of the speech signal; and a speaker feature calculation means which calculates a feature from the speech signal, for recognizing attribute information of the speech signal, using the contribution degree as a weight of the segment of the speech signal.

Abstract: A speech enhancement means 81 determines an enhancement mask generated based on a mask for speech enhancement, when a test utterance is input as speech data. A first hyper-parameter optimization means 82 determines, when the test utterance is input, a first hyper-parameter which is a hyper-parameter representing the degree to which the signal representing the test utterance is kept using the mask, and the first hyper-parameter which is set to take into account a downstream task that is processed using an enhanced test utterance. A mask generation means 83 generates an adaptive mask from the determined enhancement mask and the first hyper-parameter that enhances the test utterance for the downstream task. The mask generation means 83 generates the adaptive mask in which the first hyper-parameter is a power of the mask.

Abstract: Provided is a pattern recognition apparatus to provide classification robustness to any kind of domain variability. The pattern recognition apparatus 500 based on Neural Network (NN) includes: NN training unit 501 that trains an NN model to generate NN parameters, based on at least one first feature vector and at least one domain vector indicating one of subsets in a specific domain, wherein, the first feature vector is extracted from each of the subsets, the domain vector indicates an identifier corresponding to the each of the subsets; and NN verification unit 502 that verifies a pair of second feature vectors in the specific domain to output whether the pair indicates same individual or not, based on a target domain vector and the NN parameters.

Abstract: A spoofing detection apparatus 100 includes a multi-channel spectrogram creation unit 10 and an evaluation unit 40. The multi-channel spectrogram creation unit 10 extracts different type of spectrograms from speech data and integrates the different type of spectrograms to create a multi-channel spectrogram. The evaluation unit 40 evaluates the created multi-channel spectrogram by applying the created multi-channel spectrogram to a classifier constructed using labeled multi-channel spectrograms as training data and classifies it to either genuine or spoof.

Abstract: Learning means 81 generates a speaker embedding extracting neural network by learning a weighting factor so as to minimize a loss function indicating an error between a speaker label indicating a speaker of a voice signal and an output value output from an output layer, with respect to a neural network including an input layer that receives an input of the voice signal and the output layer that outputs the output value indicating a speaker of the voice signal. The speaker embedding extracting neural network includes a network that calculates a first accuracy from a feature in units of frames and calculates an average and a second accuracy of a posterior distribution from an average and an accuracy of a prior distribution and the feature and the first accuracy.

Abstract: The voice registration device 1X mainly includes a noise reproduction means 220X, a voice data acquisition means 200X, and a voice registration means 210X. The noise reproduction means 220X is configured to reproduce noise data during a time period in which voice input from a user is performed. The voice data acquisition means 200X is configured to acquire the voice data based on the voice input. The voice registration means 210X is configured to register the voice data or data generated based on the voice data as data to be used for verification relating to a voice of the user.

Abstract: A feature extraction unit (110) extracts, from input data based on an utterance of a person to be determined, a first feature of the input data using a discriminator that has performed machine learning using, as training data, voice data based on an utterance of the person to be determined in a normal state. An index value calculation unit (120) calculates an index value indicating the degree of similarity between the first feature of the input data and a second feature of the voice data based on the utterance of the person to be determined in the normal state. A state determination unit (130) determines whether the person to be determined is in the normal state or in an unusual state on the basis of the index value.

Abstract: Provided is a personal authentication device capable of simply securing security with little psychological and physical burden of a user to be authenticated.