A learning apparatus includes: a speaker vector learning unit configured to learn a speaker vector extraction parameter λ based on one or more items of learning speech voice data in a speaker vector voice database; a non-speaker-individuality sound model learning unit configured to create a probability distribution model using a frequency component of one or more items of non-speaker-individuality sound data in a non-speaker-individuality sound database and calculate an internal parameter of the probability distribution model; and an age level estimation model learning unit configured to extract a speaker vector from voice data in an age level estimation model-learning voice database using the speaker vector extraction parameter λ, calculate a non-speaker-individuality sound likelihood vector from voice data in the age level estimation model-learning voice database using the internal parameters μ and Σ, and learn, with input of the speaker vector and the non-speaker-individuality sound likelihood vector, a parameter Ω of an age level estimation model that outputs an estimated value of an age level of a corresponding speaker.

A learning apparatus includes: a speaker vector learning unit configured to learn a speaker vector extraction parameter λ based on one or more items of learning speech voice data in a speaker vector voice database; a non-speaker-individuality sound model learning unit configured to create a probability distribution model using a frequency component of one or more items of non-speaker-individuality sound data in a non-speaker-individuality sound database and calculate an internal parameter of the probability distribution model; and an age level estimation model learning unit configured to extract a speaker vector from voice data in an age level estimation model-learning voice database using the speaker vector extraction parameter λ, calculate a non-speaker-individuality sound likelihood vector from voice data in the age level estimation model-learning voice database using the internal parameters μ and Σ, and learn, with input of the speaker vector and the non-speaker-individuality sound likelihood vector, a parameter Ω of an age level estimation model that outputs an estimated value of an age level of a corresponding speaker.

A speaker identification device acquires identification target voice data; acquires registered voice data; selects a first speaker identification model machine-learned using male voice data to identify a male speaker in a case where one of a sex of a speaker of the identification target voice data and a sex of a speaker of the registered voice data is male, and selects a second speaker identification model machine-learned using female voice data to identify a female speaker in a case where one of a sex of the speaker of the identification target voice data and a sex of the speaker of the registered voice data is female; and inputs a feature amount of the identification target voice data and a feature amount of the registered voice data to one of the selected first speaker identification model and second speaker identification model to identify the speaker of the identification target voice data.

A speaker identification device acquires identification target voice data; acquires registered voice data; selects a first speaker identification model machine-learned using male voice data to identify a male speaker in a case where one of a sex of a speaker of the identification target voice data and a sex of a speaker of the registered voice data is male, and selects a second speaker identification model machine-learned using female voice data to identify a female speaker in a case where one of a sex of the speaker of the identification target voice data and a sex of the speaker of the registered voice data is female; and inputs a feature amount of the identification target voice data and a feature amount of the registered voice data to one of the selected first speaker identification model and second speaker identification model to identify the speaker of the identification target voice data.

An electronic device is provided. The electronic device includes a microphone configured to receive an audio signal including a voice of a user, a sensor configured to detect a vibration signal generated by the user, at least one processor, and a memory configured to store an instruction executable by the processor. The at least one processor may be configured to determine a noise level included in the audio signal, calculate a verification score based on the noise level, the audio signal, and the vibration signal, and perform speaker verification for the user based on the verification score.

An electronic device is provided. The electronic device includes a microphone configured to receive an audio signal including a voice of a user, a sensor configured to detect a vibration signal generated by the user, at least one processor, and a memory configured to store an instruction executable by the processor. The at least one processor may be configured to determine a noise level included in the audio signal, calculate a verification score based on the noise level, the audio signal, and the vibration signal, and perform speaker verification for the user based on the verification score.

Smooth text communication is realized between users. An information processing apparatus according to the present disclosure includes a control unit configured to: determine speech generated by a first user on the basis of sensing information of at least one sensor apparatus sensing at least one of the first user and a second user communicating with the first user on the basis of the speech generation of the first user; and control information output to the first user on the basis of a result of the determination of the speech generation of the first user.

Smooth text communication is realized between users. An information processing apparatus according to the present disclosure includes a control unit configured to: determine speech generated by a first user on the basis of sensing information of at least one sensor apparatus sensing at least one of the first user and a second user communicating with the first user on the basis of the speech generation of the first user; and control information output to the first user on the basis of a result of the determination of the speech generation of the first user.

Implementations set forth herein relate to an automated assistant that can solicit other devices for data that can assist with user authentication. User authentication can be streamlined for certain requests by removing a requirement that all authentication be performed at a single device and/or by a single application. For instance, the automated assistant can rely on data from other devices, which can indicate a degree to which a user is predicted to be present at a location of an assistant-enabled device. The automated assistant can process this data to make a determination regarding whether the user should be authenticated in response to an assistant input and/or pre-emptively before the user provides an assistant input. In some implementations, the automated assistant can perform one or more factors of authentication and utilize the data to verify the user in lieu of performing one or more other factors of authentication.

Implementations set forth herein relate to an automated assistant that can solicit other devices for data that can assist with user authentication. User authentication can be streamlined for certain requests by removing a requirement that all authentication be performed at a single device and/or by a single application. For instance, the automated assistant can rely on data from other devices, which can indicate a degree to which a user is predicted to be present at a location of an assistant-enabled device. The automated assistant can process this data to make a determination regarding whether the user should be authenticated in response to an assistant input and/or pre-emptively before the user provides an assistant input. In some implementations, the automated assistant can perform one or more factors of authentication and utilize the data to verify the user in lieu of performing one or more other factors of authentication.