A speech signal is received by a device comprising first and second transducers, and the first transducer comprises a microphone. A method comprises performing a first voice biometric process on speech contained in a first part of a signal received by the microphone, in order to determine whether the speech is the speech of an enrolled user. A first correlation is determined, between said first part of the signal received by the microphone and a corresponding part of the signal received by the second transducer. A second correlation is determined, between said second part of the signal received by the microphone and the corresponding part of the signal received by the second transducer. It is then determined whether the first correlation and the second correlation satisfy a predetermined condition. If it is determined that the speech contained in the first part of the received signal is the speech of an enrolled user and that the first correlation and the second correlation satisfy the predetermined condition, the received speech signal is authenticated.

Devices, systems and methods are disclosed for improving facial recognition and/or speaker recognition models by using results obtained from one model to assist in generating results from the other model. For example, a device may perform facial recognition for image data to identify users and may use the results of the facial recognition to assist in speaker recognition for corresponding audio data. Alternatively or additionally, the device may perform speaker recognition for audio data to identify users and may use the results of the speaker recognition to assist in facial recognition for corresponding image data. As a result, the device may identify users in video data that are not included in the facial recognition model and may identify users in audio data that are not included in the speaker recognition model. The facial recognition and/or speaker recognition models may be updated during run-time and/or offline using post-processed data.

Devices, systems and methods are disclosed for improving facial recognition and/or speaker recognition models by using results obtained from one model to assist in generating results from the other model. For example, a device may perform facial recognition for image data to identify users and may use the results of the facial recognition to assist in speaker recognition for corresponding audio data. Alternatively or additionally, the device may perform speaker recognition for audio data to identify users and may use the results of the speaker recognition to assist in facial recognition for corresponding image data. As a result, the device may identify users in video data that are not included in the facial recognition model and may identify users in audio data that are not included in the speaker recognition model. The facial recognition and/or speaker recognition models may be updated during run-time and/or offline using post-processed data.

Various implementations include approaches for authenticating user identity with audio-based verification. Certain approaches include: receiving a request to authenticate a user of an audio device; prompting the user of the audio device to speak a verification word or phrase in response to receiving the request; detecting an acoustic response at the audio device or a connected smart device; comparing the detected acoustic response with an acoustic signature of a known user associated with the audio device and the verification word or phrase, wherein the audio device is registered as an authentication device prior to receiving the request to authenticate the user of the audio device; and sending a confirmation response indicating the user of the audio device is the known user in response to the acoustic response corresponding with the acoustic signature and the verification word or phrase.

A method of detecting a replay attack on a voice biometrics system comprises: receiving an audio signal representing speech; detecting a magnetic field; determining if there is a correlation between the audio signal and the magnetic field; and if there is a correlation between the audio signal and the magnetic field, determining that the audio signal may result from a replay attack.

A method of detecting a replay attack on a voice biometrics system comprises: receiving an audio signal representing speech; detecting a magnetic field; determining if there is a correlation between the audio signal and the magnetic field; and if there is a correlation between the audio signal and the magnetic field, determining that the audio signal may result from a replay attack.

Embodiments of the invention relate to methods, apparatus and systems for biometric processes. The methods include updating stored ear model data for a user following successful authentication of the user. The ear model data may be acquired using a personal audio device that generates an acoustic stimulus and detects a measured response. The acquisition of the ear model data may be responsive to a determination that the personal audio device is inserted into or placed adjacent to the user's ear. The acquisition of the ear model data may also be responsive to the determination that the personal audio device has not been removed from or moved away from the user's ear.

Pairing two or more network devices in the same room or area is performed. Unique signature or speaker identification data of a user's voice is provided by the two or more network devices. The unique signature or speaker identification data provided by each of the two or more network devices is compared with one another and determined received at the same time. If unique signature or speaker identification data provided by each of the two or more network devices are the same and received at the same time, then pairing information is provided to the two more network devices to allow pairing.

Pairing two or more network devices in the same room or area is performed. Unique signature or speaker identification data of a user's voice is provided by the two or more network devices. The unique signature or speaker identification data provided by each of the two or more network devices is compared with one another and determined received at the same time. If unique signature or speaker identification data provided by each of the two or more network devices are the same and received at the same time, then pairing information is provided to the two more network devices to allow pairing.

A method for authenticating a user of an electronic device is disclosed. The method comprises: responsive to detection of a trigger event indicative of a user interaction with the electronic device, generating an audio probe signal to play through an audio transducer of the electronic device; receiving a first audio signal comprising a response of the user's ear to the audio probe signal; receiving a second audio signal comprising speech of the user; and applying an ear biometric algorithm to the first audio signal and a voice biometric algorithm to the second audio signal to authenticate the user as an authorised user.