JP2020154178A - Information processing device, information processing method and information processing program - Google Patents

Abstract

To improve quality of a service for a user who cannot speak by estimating voice information indicating a voice feature of a target user from genome information of the user.SOLUTION: In an information processing device, an acquisition unit 30 acquires genome information and voice information of a teacher user and stores the same in a storage unit 4, a generation unit 31 generates a speaker model which outputs an index about a voice feature by machine learning with the voice information of the teacher user as a teacher and the genome information of the teacher user as an identity, an estimation unit 32 estimates voice information of a target user by inputting genome information of the target user acquired by the acquisition unit 30 to the speaker model, more specifically, the estimation unit 32 estimates a voice feature based on an index output from a speaker model as voice information, and a processing unit 34 generates voice based on the voice feature of the estimated voice information as voice of the target user.SELECTED DRAWING: Figure 3

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

Conventionally, an information processing device for identifying a speaker of input voice is known. In such an information processing device, a speaker model is generated by learning the characteristic parameters of the speaker's voice input in advance by machine learning, and the speaker is specified by inputting the voice into the speaker model and estimating the voice characteristics. (See, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2003-076390

However, since the prior art is a service limited to users who can emit voice, it cannot be said to be a useful service for users who cannot emit voice, such as an intubated person. Therefore, in the past, there was room for improvement in terms of improving the quality of service.

The present application has been made in view of the above, and an object of the present application is to provide an information processing device, an information processing method, and an information processing program capable of improving the quality of service.

The information processing apparatus according to the present application includes an acquisition unit and an estimation unit. The acquisition unit acquires the user's genomic information. The estimation unit estimates voice information indicating the voice characteristics of the user based on the genome information acquired by the acquisition unit.

According to one aspect of the embodiment, there is an effect that the quality of service can be improved.

FIG. 1 is a diagram showing an example of information processing according to an embodiment. FIG. 2 is a diagram showing a configuration of an information processing system according to an embodiment. FIG. 3 is a block diagram showing a configuration example of the information processing apparatus according to the embodiment. FIG. 4 is a diagram showing an example of user information. FIG. 5 is a diagram showing an example of model information. FIG. 6 is a flowchart showing a procedure of model generation processing executed by the information processing apparatus according to the embodiment. FIG. 7 is a flowchart showing a procedure of voice generation processing executed by the information processing apparatus according to the embodiment. FIG. 8 is a flowchart showing a procedure of registration processing of correct answer voice executed by the information processing apparatus according to the embodiment. FIG. 9 is a flowchart showing a procedure of authentication processing executed by the information processing apparatus according to the embodiment. FIG. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device according to the embodiment.

Hereinafter, the information processing apparatus, the information processing method, and the mode for implementing the information processing program according to the present application (hereinafter, referred to as “the embodiment”) will be described in detail with reference to the drawings. The information processing device, information processing method, and information processing program according to the present application are not limited by this embodiment. Further, in each of the following embodiments, the same parts are designated by the same reference numerals, and duplicate description is omitted.

First, an example of information processing realized by the information processing program according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram showing an example of information processing according to an embodiment. FIG. 1 describes, for example, a case where an information processing apparatus executes an information processing method for estimating voice information indicating voice characteristics of a user who cannot emit voice due to intubation (hereinafter referred to as a target user).

The target user may be a user who emits voice, and may be a user whose voice information is not registered in the information processing device. Further, in the information processing shown in FIG. 1, a story for estimating the voice information of the target user based on the genomic information and voice information of a user who can emit voice (hereinafter referred to as a teacher user) in advance. The model generation process that generates the person model is executed.

First, a series of processes up to the model generation process will be described. Specifically, as shown in FIG. 1, the teacher user first requests an analysis institution to analyze genetic analysis (S1). For example, the teacher user provides saliva, blood, etc. to the analysis institution at the time of requesting analysis.

Subsequently, the analysis institution performs genetic analysis using saliva, blood, etc. collected from the teacher user (S2). Then, the information processing apparatus according to the embodiment acquires the genomic information of the teacher user as a result of the genetic analysis from the analysis institution (S3).

The genomic information includes, for example, information on the health risk of the user, information on the constitution and physical characteristics of the user, and the like. The genomic information may include, for example, information related to the genetic code such as a user's base sequence or amino acid sequence.

The information processing device is not limited to acquiring genomic information from an analysis institution, but collects saliva or blood directly from the user, performs genetic analysis, acquires genomic information, or is already possessed by the user. Genome information may be obtained directly from the user without going through an analysis institution.

Subsequently, the information processing device according to the embodiment acquires voice information indicating the voice characteristics of the teacher user (S4). The voice information is information including an analysis result obtained by analyzing a voice input by a microphone or the like, for example, an acoustic feature such as a frequency characteristic of the voice and a language feature related to an arrangement of phonemes. The voice information may be the voice itself collected by a microphone or the like.

Although FIG. 1 shows a case where genome information and voice information are acquired from one teacher user, it is preferable to acquire genome information and voice information from a plurality of teacher users. As a result, the accuracy of the model generated by the model generation process in the subsequent stage can be improved.

Subsequently, the information processing apparatus according to the embodiment executes a model generation process using the acquired genomic information and voice information, and generates a model for estimating voice information (hereinafter, referred to as a speaker model). (S5).

Specifically, the information processing apparatus according to the embodiment is a model that generates a speaker model that outputs an index related to voice features by machine learning that uses the voice information of the teacher user as the teacher and the genomic information of the teacher user as the element. Execute the generation process.

Next, a series of processes for estimating the voice information of the target user will be described. Specifically, first, the target user requests an analysis institution to analyze the genetic analysis (S6). Subsequently, the analysis institution performs genetic analysis using saliva, blood, etc. collected from the target user (S7). Then, the information processing apparatus according to the embodiment acquires the genomic information of the target user as a result of the genetic analysis from the analysis institution (S8).

Subsequently, the information processing apparatus according to the embodiment executes an estimation process for estimating the voice information of the target user based on the genomic information of the target user (S9). Specifically, the information processing apparatus according to the embodiment inputs the acquired genomic information into the speaker model, and estimates the voice information of the target user based on the index output from the model.

The information processing device according to the embodiment can perform a voice generation process for generating (reproducing) the voice of the target user based on the estimated voice information, which will be described later.

Further, the information processing device according to the embodiment receives, for example, a voice input for a user who can emit a voice, and inputs the voice by collating the voice with the voice information estimated by the estimation process. It is possible to perform authentication processing for whether or not the user is the person himself / herself, and this point will also be described later.

As described above, the information processing apparatus according to the embodiment can provide a useful service for the target user who cannot emit the voice by estimating the voice information of the user based on the genomic information. Therefore, according to the information processing apparatus according to the embodiment, the quality of service can be improved.

Next, the system configuration of the information processing system according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram showing a configuration of an information processing system according to an embodiment.

As shown in FIG. 2, the information processing system S according to the embodiment includes an information processing device 1, a plurality of terminal devices 10-1 to 10-n, and an engine terminal 100. The information processing device 1, the plurality of terminal devices 10-1 to 10-n, and the engine terminal 100 are connected to each other via a network N so as to be able to communicate with each other by wire or wirelessly. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet. The terminal devices 10-1 to 10-n are operated by users U-1 to Un.

In the following, when each of the terminal devices 10-1 to 10-n is shown without distinction, it is described as the terminal device 10, and when each of the users U-1 to Un is shown without distinction, the user U It is described as. Further, the user U includes the teacher user and the target user described above.

The terminal device 10 is a terminal device of the user U, and is a smart device (communication terminal) such as a smartphone, a tablet terminal, a PDA (Personal Digital Assistant), or a personal computer. The terminal device 10 can execute a browser, various applications, and the like.

The terminal device 10 accesses the institutional terminal 100 from a browser or an application via the network N to request analysis of genetic analysis. Further, the terminal device 10 is provided with, for example, a microphone or the like, and can collect the voice emitted by the user U and transmit it as voice information to the information processing device 1.

The engine terminal 100 is a terminal device owned by an analysis institution that performs genetic analysis. The engine terminal 100 receives the analysis request of the user U from the terminal device 10 via the network N, and transmits the genomic information which is the result of the genetic analysis to the information processing device 1.

Although FIG. 2 shows a case where the terminal device 10 and the information processing device 1 are separately configured, for example, the terminal device 10 and the information processing device 1 are integrally configured, and each process of the information processing device 1 is performed. The terminal device 10 may execute.

Next, the configuration of the information processing apparatus 1 according to the embodiment will be described with reference to FIG. FIG. 3 is a block diagram showing a configuration example of the information processing device 1 according to the embodiment.

As shown in FIG. 3, the information processing device 1 includes a communication unit 2, a control unit 3, and a storage unit 4.

The communication unit 2 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 2 is connected to the network N by wire or wirelessly, and transmits / receives information to / from the terminal device 10 and the engine terminal 100 via the network N.

The storage unit 4 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. As shown in FIG. 3, the storage unit 4 stores the user information 40 and the model information 41.

The user information 40 includes user information which is information of the user U. FIG. 4 is a diagram showing an example of user information. User information is generated, for example, when genomic information or voice information is acquired.

As shown in FIG. 4, the user information includes items such as "user ID", "attribute", "genome information", and "voice information".

The "user ID" is identification information that identifies the user U. The "attribute" is information about the attribute of the user U, and includes, for example, a demographic attribute and a psychographic attribute. The "genome information" is, for example, information on the gene of the user U extracted by collecting saliva of the user U, for example, information on the health risk of the user U, and information on the constitution and physical characteristics of the user U. , Information on the genetic code such as the base sequence and amino acid sequence of user U is included. The genomic information may include genomic information generated by another laboratory. The "voice information" is voice information indicating the voice characteristics of the user U, and includes, for example, an analysis result obtained by analyzing the input voice of the user U and the input voice itself.

Next, the model information 41 is information about the speaker model generated by the generation unit 31 described later. FIG. 5 is a diagram showing an example of model information. As shown in FIG. 5, the model information includes items such as "model ID" and "model information".

The "model ID" is identification information that identifies the speaker model. "Model information" indicates model information for outputting an index indicating a voice feature. In the model information 41, the speaker model identified by the model ID may be classified by, for example, gender, nationality, age, or the like, or may be one speaker model. That is, the model information 41 includes one or a plurality of speaker models.

The control unit 3 is a controller, and for example, various programs stored in a storage device inside the information processing device 1 by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like store RAM in a work area. It is realized by executing as. Further, the control unit 3 is, for example, a controller, and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

The control unit 3 includes an acquisition unit 30, a generation unit 31, an estimation unit 32, a reception unit 33, and a processing unit 34.

The acquisition unit 30 acquires various information of the user U. The acquisition unit 30 acquires, for example, genomic information and voice information. In addition, the acquisition unit 30 acquires attribute information and the like, which are user information related to the user U who has acquired the genome information and the voice information. The acquisition unit 30 stores the acquired genome information, voice information, attribute information, and the like as user information 40 in the storage unit 4.

The generation unit 31 generates a machine learning model based on the genomic information and voice information of the user U (teacher user) acquired by the acquisition unit 30. Specifically, the generation unit 31 generates a speaker model that outputs an index related to voice features by machine learning using the voice information of the teacher user as a teacher and the genomic information of the teacher user as a feature.

For example, when a neural network is used as machine learning, the generation unit 31 learns each weight in the neural network based on genomic information and voice information.

More specifically, the generation unit 31 uses a regression model in which the voice information of the teacher user is used as the objective variable (teacher) and the genomic information and each feature information extracted from the user information are used as explanatory variables (features) as the learning model. You can ask.

The feature information extracted from the genomic information includes, for example, information on the shape of the voice organ of the user U, information on the frequency characteristics of the voice of the user U, information on the physique and constitution of the user U, and the like. In addition, the feature information extracted from the user information includes information on attributes such as the birthplace of the user U, the past residence, the period of residence, the age, and the gender.

Further, the index output from the speaker model includes, for example, a score indicating the frequency characteristic of the voice, a score indicating the intonation of the voice, a score indicating the strength of the voice, a score indicating the arrangement of phonemes, and the like. The generation unit 31 may generate a speaker model for each of the above scores, or may generate one speaker model that outputs a total score of all the scores.

The machine learning learning model used by the generation unit 31 is not limited to the neural network, and for example, another machine learning learning model such as SVM (Support Vector Machine) may be used.

In addition, the generation unit 31 can also generate a speaker model by using a technique of deep learning. For example, the generation unit 31 can generate a speaker model by appropriately using various deep learning techniques such as DNN (Deep Neural Network), RNN (Recurrent Neural Network), and CNN (Convolutional Neural Network).

In addition, the generation unit 31 updates the speaker model after the speaker model is generated. Specifically, the generation unit 31 acquires the voice information of a predetermined user U (user U capable of emitting voice) estimated by the estimation unit 32 described later using the speaker model, and the acquisition unit 30. The speaker model is updated based on the collation result with the voice information of the user U.

For example, the generation unit 31 updates each weight in the neural network. Specifically, the generation unit 31 sets each weight in the neural network so that the similarity between the voice information estimated by the estimation unit 32 and the voice information acquired by the acquisition unit 30 is equal to or higher than a predetermined threshold value. Update.

The estimation unit 32 estimates voice information indicating the voice characteristics of the user U based on the genomic information acquired by the acquisition unit 30. Specifically, the estimation unit 32 inputs the genomic information of the user U (for example, the target user) acquired by the acquisition unit 30 into the speaker model, and estimates the voice information of the user U. More specifically, the estimation unit 32 estimates the voice features based on the index output from the speaker model as voice information.

The reception unit 33 receives voice input for the processing unit 34, which will be described later, to perform an authentication process. For example, the reception unit 33 receives the voice of the user U collected through the microphone of the terminal device 10 as a voice input.

The processing unit 34 executes various processes based on the voice information estimated by the estimation unit 32. For example, the processing unit 34 performs a voice generation process for generating the voice of the user U based on the voice information estimated by the estimation unit 32. Specifically, the processing unit 34 generates a voice based on the voice characteristics of the estimated voice information as the voice of the user U.

In addition, the processing unit 34 can also perform voice authentication processing using the voice information estimated by the estimation unit 32. Specifically, the processing unit 34 authenticates that the user U is the person himself / herself by collating the voice information of the user U estimated by the estimation unit 32 with the voice received by the reception unit 33. Perform processing.

More specifically, the processing unit 34 first stores the voice based on the voice information estimated by the estimation unit 32 in the storage unit 4 as the correct voice (for example, "voice information" of the user information 40).

Then, the processing unit 34 performs an authentication process as to whether or not the user U is the user U, based on the comparison result between the voice input received by the reception unit 33 at the time of user U authentication and the correct answer voice stored in the storage unit 4. Do. That is, the processing unit 34 generates voice information based on the speaker model as correct voice in the authentication process.

Alternatively, the processing unit 34 may generate voice information based on the speaker model as voice input in the authentication process. Specifically, the processing unit 34 first stores the voice input received by the reception unit 33 in the storage unit 4 as a correct answer voice.

Then, the processing unit 34 acquires the genomic information at the time of authentication of the user U, and based on the comparison result between the voice based on the voice information estimated based on the genome information and the correct voice stored in the storage unit 4, the processing unit 34 obtains the genomic information. Authentication processing may be performed to determine whether or not the user U is the person himself / herself.

Next, the procedure of the process executed by the information processing apparatus 1 according to the embodiment will be described with reference to FIGS. 6 to 9. First, the processing procedure of the model generation processing will be described with reference to FIG.

FIG. 6 is a flowchart showing a procedure of model generation processing executed by the information processing apparatus 1 according to the embodiment. As shown in FIG. 6, the acquisition unit 30 acquires the genomic information of the teacher user (S101).

Subsequently, the acquisition unit 30 acquires the voice information of the teacher user (S102). In FIG. 6, the processing procedures of S101 and S102 may be interchanged.

Subsequently, the generation unit 31 generates a speaker model that outputs an index related to the voice feature by machine learning using the voice information of the teacher user as the teacher and the genomic information of the teacher user as the feature (S103).

Subsequently, the generation unit 31 stores the generated speaker model as model information 41 in the storage unit 4 (S104), and ends the process.

Next, the processing procedure of the voice generation processing will be described with reference to FIG. 7. FIG. 7 is a flowchart showing a procedure of voice generation processing executed by the information processing device 1 according to the embodiment.

As shown in FIG. 7, first, the acquisition unit 30 acquires the genome information of the target user (S201).

Subsequently, the estimation unit 32 inputs genomic information into the speaker model and outputs an index indicating voice characteristics (S202).

Subsequently, the estimation unit 32 estimates the voice information based on the output index (S203).

Subsequently, the processing unit 34 executes a voice generation process for generating the voice of the target user based on the estimated voice information (S204), and ends the process.

Next, the processing procedure of the authentication process will be described with reference to FIGS. 8 and 9. FIG. 8 is a flowchart showing a procedure of registration processing of correct answer voice executed by the information processing device 1 according to the embodiment. FIG. 9 is a flowchart showing a procedure of the authentication process executed by the information processing apparatus 1 according to the embodiment.

As shown in FIG. 8, the acquisition unit 30 acquires the genome information of the user U to be authenticated (S301).

Subsequently, the estimation unit 32 inputs genomic information into the speaker model and outputs an index indicating voice characteristics (S302).

Subsequently, the estimation unit 32 estimates the voice information based on the output index (S303).

Subsequently, the estimation unit 32 stores the estimated voice information (or voice based on the voice information) in the storage unit 4 as the correct voice (S304), and ends the process.

Next, as shown in FIG. 9, in the authentication process, the reception unit 33 determines whether or not the voice input of the user U, which is the target of the authentication process, has been accepted (S401). If the reception unit 33 does not accept the voice input of the user U (S401: No), the reception unit 33 repeatedly executes S401 until the voice input is received.

Subsequently, the processing unit 34 collates the voice received by the reception unit 33 with the correct answer voice stored in the storage unit 4 (S402).

As a result of the collation, the processing unit 34 determines whether or not the similarity between the voice received by the reception unit 33 and the correct answer voice is equal to or higher than a predetermined threshold value (S403).

Subsequently, when the similarity is equal to or higher than a predetermined threshold value (S403: Yes), the processing unit 34 determines that the user U is the user (S404), and ends the process.

On the other hand, when the similarity is less than a predetermined threshold value (S403: No), the processing unit 34 determines that the user is not the user U (S405), and ends the processing.

Further, the information processing apparatus 1 according to the above-described embodiment is realized by, for example, a computer 200 having a configuration as shown in FIG. FIG. 10 is a hardware configuration diagram showing an example of a computer 200 that realizes the function of the information processing device 1 according to the embodiment. The computer 200 has a CPU 201, a RAM 202, a ROM 203, an HDD 204, a communication interface (I / F) 205, an input / output interface (I / F) 206, and a media interface (I / F) 207.

The CPU 201 operates based on the program stored in the ROM 203 or the HDD 204, and controls each part. The ROM 203 stores a boot program executed by the CPU 201 when the computer 200 is started, a program that depends on the hardware of the computer 200, and the like.

The HDD 204 stores a program executed by the CPU 201, data used by the program, and the like. The communication interface 205 receives data from another device via the network N and sends it to the CPU 201, and transmits the data generated by the CPU 201 to the other device via the network N.

The CPU 201 controls an output device such as a display or a printer and an input device such as a keyboard or a mouse via the input / output interface 206. The CPU 201 acquires data from the input device via the input / output interface 206. Further, the CPU 201 outputs the generated data to the output device via the input / output interface 206.

The media interface 207 reads the program or data stored in the recording medium 208 and provides it to the CPU 201 via the RAM 202. The CPU 201 loads the program from the recording medium 208 onto the RAM 202 via the media interface 207, and executes the loaded program. The recording medium 208 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable Disk), a magneto-optical recording medium such as MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. And so on.

For example, when the computer 200 functions as the information processing device 1 according to the embodiment, the CPU 201 of the computer 200 realizes the function of the control unit 3 by executing the program loaded on the RAM 202. Further, the data in the storage unit 4 is stored in the HDD 204. The CPU 201 of the computer 200 reads and executes these programs from the recording medium 208, but as another example, these programs may be acquired from another device via the network N.

As described above, the information processing apparatus 1 according to the embodiment includes an acquisition unit 30 and an estimation unit 32. The acquisition unit 30 acquires the genome information of the user U. The estimation unit 32 estimates voice information indicating the voice characteristics of the user U based on the genomic information acquired by the acquisition unit 30.

As a result, the quality of service can be improved.

In addition, the information processing device 1 according to the above-described embodiment further includes a processing unit 34. The processing unit 34 performs a voice generation process for generating the voice of the user U based on the voice information of the user U estimated by the estimation unit 32.

As a result, for example, the voice of the user U who does not make a voice due to intubation or the like can be reproduced, so that a useful service for such a user U can be provided.

Further, the information processing device 1 according to the above-described embodiment further includes a reception unit 33 and a processing unit 34. The reception unit 33 receives the voice input of the user U. The processing unit 34 performs an authentication process for authenticating the user U by collating the voice information of the user U estimated by the estimation unit 32 with the voice received by the reception unit 33.

As a result, the authentication accuracy of the user U can be improved.

In addition, the information processing device 1 according to the above-described embodiment further includes a generation unit 31. The generation unit 31 generates a model that outputs an index related to the voice feature by machine learning using the voice information of the teacher user as a teacher and the genomic information of the teacher user as a feature. The estimation unit 32 inputs the genomic information acquired by the acquisition unit 30 into the model and estimates the voice information of the user U.

Thereby, the estimation accuracy of the voice information of the user U can be improved.

Further, in the information processing device 1 according to the above-described embodiment, the acquisition unit 30 acquires the voice information of the user U. The generation unit 31 updates the model based on the collation result of the voice information estimated by the estimation unit 32 and the voice information acquired by the acquisition unit 30.

As a result, the accuracy of the index output from the speaker model can be improved, so that the estimation accuracy of the voice information by the estimation unit 32 can be improved.

Although some of the embodiments of the present application have been described in detail with reference to the drawings, these are examples, and various modifications are made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure column of the invention. It is possible to carry out the present invention in other improved forms.

Further, among the processes described in the above-described embodiment, all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed can be performed. All or part of it can be done automatically by a known method. In addition, the processing procedure, specific name, and information including various data and parameters shown in the above document and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of the device is functionally or physically distributed / physically in arbitrary units according to various loads and usage conditions. It can be integrated and configured.

In addition, the processes described in the above-described embodiments can be appropriately combined as long as the processing contents do not contradict each other.

In addition, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the estimation unit 32 can be read as an estimation means or an estimation circuit.

1 Information processing device 2 Communication unit 3 Control unit 4 Storage unit 10 Terminal equipment 30 Acquisition unit 31 Generation unit 32 Estimate unit 33 Reception unit 34 Processing unit 100 Engine terminal U user

Claims (7)

The acquisition department that acquires the user's genome information,
An information processing device including an estimation unit that estimates voice information indicating the voice characteristics of the user based on the genome information acquired by the acquisition unit. The information processing apparatus according to claim 1, further comprising a processing unit that performs a voice generation process for generating a voice of the user based on the voice information of the user estimated by the estimation unit. The reception unit that accepts the user's voice input and
It is characterized by further including a processing unit that performs an authentication process for authenticating the user by collating the voice information of the user estimated by the estimation unit with the voice received by the reception unit. The information processing device according to claim 1 or 2. It further includes a generator that generates a model that outputs an index related to voice features by machine learning that uses the voice information of the teacher user as a teacher and the genomic information of the teacher user as a feature.
The estimation unit
The information processing apparatus according to any one of claims 1 to 3, wherein the user's genomic information acquired by the acquisition unit is input to the model to estimate the user's voice information. The acquisition unit
Further acquisition of the user's voice information
The generator
The information processing apparatus according to claim 4, wherein the model is updated based on a collation result of the voice information estimated by the estimation unit and the voice information acquired by the acquisition unit. Information processing method executed by a computer
The acquisition process to acquire the user's genome information and
An information processing method including an estimation step of estimating voice information indicating a voice feature of the user based on the genome information acquired by the acquisition step. The acquisition procedure for acquiring the user's genome information and
An information processing program characterized in that a computer executes an estimation procedure for estimating voice information indicating the voice characteristics of the user based on the genome information acquired by the acquisition procedure.

Images