Systems and processes for operating an intelligent automated assistant are provided. In one example, a plurality of speech inputs is received from a first user. A voice model is obtained based on the plurality of speech inputs. A user input is received from the first user, the user input corresponding to a request to provide access to the voice model. The voice model is provided to a second electronic device.

Systems and processes for operating an intelligent automated assistant are provided. In one example, a plurality of speech inputs is received from a first user. A voice model is obtained based on the plurality of speech inputs. A user input is received from the first user, the user input corresponding to a request to provide access to the voice model. The voice model is provided to a second electronic device.

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.

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.

A system is provided to categorize voice prints during a voice authentication. The system includes a processor and a computer readable medium operably coupled thereto, to perform voice authentication operations which include receiving an enrollment of a user in the biometric authentication system, requesting a first voice print comprising a sample of a voice of the user, receiving the first voice print of the user during the enrollment, accessing a plurality of categorizations of the voice prints for the voice authentication, wherein each of the plurality of categorizations comprises a portion of the voice prints based on a plurality of similarity scores of distinct voice prints in the portion to a plurality of other voice prints, determining, using a hidden layer of a neural network, one of the plurality of categorizations for the first voice print, and encoding the first voice print with the one of the plurality of categorizations.

A system is provided to categorize voice prints during a voice authentication. The system includes a processor and a computer readable medium operably coupled thereto, to perform voice authentication operations which include receiving an enrollment of a user in the biometric authentication system, requesting a first voice print comprising a sample of a voice of the user, receiving the first voice print of the user during the enrollment, accessing a plurality of categorizations of the voice prints for the voice authentication, wherein each of the plurality of categorizations comprises a portion of the voice prints based on a plurality of similarity scores of distinct voice prints in the portion to a plurality of other voice prints, determining, using a hidden layer of a neural network, one of the plurality of categorizations for the first voice print, and encoding the first voice print with the one of the plurality of categorizations.

According to one embodiment, a system for creating a speaker model includes one or more processors. The processors change a part of network parameters from an input layer to a predetermined intermediate layer based on a plurality of patterns and inputs a piece of speech into each of neural networks so as to obtain a plurality of outputs from the intermediate layer. The part of network parameters of the each of the neural networks is changed based on one of the plurality of patterns. The processors create a speaker model with respect to one or more words detected from the speech based on the outputs.

Systems and methods provide voice activated authentication over time. A user can be registered with a voice authentication system based on a voiceprint profile of common words. This user voiceprint profile can be used in an ongoing secondary authentication as a hands-free head-mounted wearable device is used over time. Upon a user logging into a hands-free head-mounted wearable device voiceprints can be collected during a session. These collected voiceprints can be compared with a user voiceprint profile for a user authorized to operate the hands-free head-mounted wearable device. Such a comparison can include an analysis of frequency, duration, and amplitude for the voiceprints. When the voiceprints match, the login of the user can be maintained based on this secondary authentication using the voiceprints matched to the user voiceprint profile.

An AI control device, which identifies individual users from a plurality of users to receive input data, and is connectable to a server device that generates a trained model based on input data for each user, includes a control unit, and a communication unit connected to the server device. The control unit acquires input data, associates acquired input data and identifying information used to identify the user of the AI control device, and sends the data and information to the server device via the communication unit. The control unit uses the sent acquired input data to execute a trained model that is generated separately from trained models of other users by the server device, and that learns characteristics of acquired input data and detects input data having the same characteristics from unknown input data.

An AI control device, which identifies individual users from a plurality of users to receive input data, and is connectable to a server device that generates a trained model based on input data for each user, includes a control unit, and a communication unit connected to the server device. The control unit acquires input data, associates acquired input data and identifying information used to identify the user of the AI control device, and sends the data and information to the server device via the communication unit. The control unit uses the sent acquired input data to execute a trained model that is generated separately from trained models of other users by the server device, and that learns characteristics of acquired input data and detects input data having the same characteristics from unknown input data.