Nippon Telegraph and Telephone Corporation

Takuhiro Kaneko

Hirokazu Kameoka

Ko Tanaka

Kunio Kashino

Kaoru Hiramatsu

Nobukatsu Hojo

Yasunori Oishi

Aaron Valero Puche

A voice signal conversion model learning device includes: a generation unit configured to execute generation processing of generating a conversion destination voice signal on the basis of an input voice signal that is a voice signal of an input voice, conversion source attribute information that is information indicating an attribute of an input voice that is a voice represented by the input voice signal, and conversion destination attribute information indicating an attribute of a voice represented by the conversion destination voice signal that is a voice signal of a conversion destination of the input voice signal; and an identification unit configured to execute voice estimation processing of estimating whether or not a voice signal that is a processing target is a voice signal representing a vocal sound actually uttered by a person on the basis of the conversion source attribute information and the conversion destination attribute intonation, wherein the conversion destination voice signal is input to the identification unit, the processing target is a voice signal input to the identification unit, and the generation unit and the identification unit pertain learning on the basis of an estimation result of the voice estimation processing.

Audio signal conversion model learning apparatus, audio signal conversion apparatus, audio signal conversion model learning method and program

A voice conversion device is provided with a linguistic information extraction unit that extracts linguistic information corresponding to utterance content from a conversion source voice signal, an appearance feature extraction unit that extracts appearance features expressing features related to the look of a person's face from a captured image of the person, and a converted voice generation unit that generates a converted voice on a basis of the linguistic information and the appearance features.

Voice conversion apparatus, voice conversion learning apparatus, image generation apparatus, image generation learning apparatus, voice conversion method, voice conversion learning method, image generation method, image generation learning method, and computer program

A signal generation device includes a variable generation unit and a signal generation unit. The variable generation unit generates a plurality of latent variables corresponding to a plurality of features of a signal. The signal generation unit inputs, to at least one neural network learned in advance, a latent variable representing attributes obtained by converting a part of the plurality of latent variables by an attribute vector representing attributes of a signal to be generated and the other part of the plurality of latent variables representing an identity and generates the signal to be generated using the at least one neural network.

Signal generation device, signal generation learning device, method, and program

A conversion learning device includes: a source encoding unit that converts, by using a first machine learning model, a feature amount sequence of a source domain that is a characteristic of conversion-source content data, into a first internal representation vector sequence that is a matrix in which internal representation vectors at individual locations of the feature amount sequence of the source domain are arranged; a target encoding unit that converts, by using a second machine learning model, a feature amount sequence of a target domain that is a characteristic of conversion-target content data, into a second internal representation vector sequence that is a matrix in which internal representation vectors at individual locations of the feature amount sequence of the target domain are arranged; an attention matrix calculation unit that calculates, by using the first internal representation vector sequence and the second internal representation vector sequence, an attention matrix that is a matrix mapping the individual locations of the feature amount sequence of the source domain to the individual locations of the feature amount sequence of the target domain, and calculates a third internal representation vector sequence that is a product of an internal representation vector sequence calculated by linear conversion of the first internal representation vector sequence and the attention matrix; a target decoding unit that calculates, by using the third internal representation vector sequence, a feature amount sequence of a conversion domain that is used to convert the source domain into the conversion domain, by using a third machine learning model; and a learning execution unit that causes at least one of the target encoding unit and the target decoding unit to learn such that a distance between a submatrix of the feature amount sequence of the target domain and a submatrix of the feature amount sequence of the conversion domain becomes shorter.

Conversion learning apparatus, conversion learning method, conversion learning program and conversion apparatus

To be able to convert to a voice of the desired attribution. A learning unit learns a converter to minimize a value of a learning criterion of the converter, learns a voice identifier to minimize a value of a learning criterion of the voice identifier, and learns an attribution identifier to minimize a value of a learning criterion of the attribution identifier.

Voice conversion learning device, voice conversion device, method, and program

A signal retrieval device includes a modification unit and a signal retrieval unit. The modification unit modifies a value of an attribute of a target represented by an input signal or a stored signals stored in a signal storage unit or a value of an attribute relating to a signal generation source of the input signal to acquire a plurality of modified values of the attribute. The signal retrieval unit retrieves a stored signal of the stored signals similar to the input signal using the input signal or the stored signals in which the attribute is modified according to each of the plurality of modified values of the attribute acquired by the modification unit.

Signal retrieval device, method, and program

To be able to convert to a voice of the desired attribution. Learning an encoder for, on the basis of parallel data of a sound feature vector series in a conversion-source voice signal and a latent vector series in the conversion-source voice signal, and an attribution label indicating attribution of the conversion-source voice signal, estimating a latent vector series from input of a sound feature vector series and an attribution label, and a decoder for reconfiguring the sound feature vector series from input of the latent vector series and the attribution label.

Audio conversion learning device, audio conversion device, method, and program

The present invention relates to methods of converting a speech into another speech that sounds more natural. The method includes learning for a target conversion function and a target identifier according to an optimal condition in which the target conversion function and the target identifier compete with each other. The target conversion function converts source speech into target speech. The target identifier identifies whether the converted target speech follows the same distribution as actual target speech. The methods include learning for a source conversion function and a source identifier according to an optimal condition in which the source conversion function and the source identifier compete with each other. The source conversion function converts target speech into source speech, and the source identifier identifies whether the converted source speech follows the same distribution as actual source speech.

Device for learning speech conversion, and device, method, and program for converting speech

A signal output unit outputs an acquired signal. A signal accumulation unit accumulates signals. A signal attribute value display unit displays a value of an attribute related to an element constituting a target represented by the acquired signal or a signal generation source in a state in which an instruction for changing the value of the attribute is able to be received. A changed attribute value acquisition unit acquires a changed value of the attribute when the instruction for changing the value of the attribute is received. A signal retrieval unit retrieves, from the signals accumulated in the signal accumulation unit, a signal similar to a changed signal when the value of the attribute has been changed on the basis of the changed value of the attribute acquired by the changed attribute value acquisition unit.

Signal retrieval apparatus, method, and program

A signal output unit outputs an acquired signal. A signal attribute value display unit displays a value of an attribute related to an element constituting a target represented by the acquired signal or a signal generation source in a state in which a change instruction of the value of the attribute is able to be received. A changed attribute value acquisition unit acquires a changed value of the attribute when the change instruction of the value of the attribute is received. A change unit changes the value of the attribute for which the change instruction has been received on the basis of the changed value of the attribute acquired by the changed attribute value acquisition unit. A changed signal output unit outputs a changed signal in which the value of the attribute has been changed.

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Atsugi, Japan

Takuhiro Kaneko