Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.

Abstract: A biometric processor comprises: one or more inputs configured to receive first ear biometric data acquired in respect of a first ear of a user and second ear biometric data acquired in respect of a second ear of the user; a processing module configured to perform a biometric algorithm on the first ear biometric data and the second ear biometric data, based on a comparison of the first ear biometric data to a first stored ear biometric template for an authorised user and a comparison of the second ear biometric data to a second stored ear biometric template for the authorised user, to obtain respective first and second biometric scores; a fusion module configured to apply first and second weights to the respective first and second biometric scores to obtain first and second weighted biometric scores, and to combine at least the first and second weighted biometric scores to generate an overall biometric score, wherein the first and second weights are different to each other; and wherein a biometric result is b

Abstract: A method in a biometric authentication system, generating an acoustic stimulus for application to a user’s ear; receiving an audio signal representing a response of the user’s ear canal to the acoustic stimulus; adapting an ear canal response estimate of the user’s ear canal to the acoustic stimulus to reduce an error between the audio signal and the ear canal response estimate; calculating one or more quality metrics, the quality metrics comprising one or more of: an ear canal response estimate quality metric comprising one or more energy characteristics of the ear canal response estimate; an error quality metric derived from the error; an audio response quality metric comprising one or more statistical characteristics of the audio signal; and determining a validity of the audio signal for use in a biometric process based on the quality metrics.

Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.

Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.

Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.

Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.

Abstract: Embodiments described herein provide for automatically detecting whether an audio signal is a spoofed audio signal or a genuine audio signal. A spoof detection system can include an audio signal transforming front end and a classification back end. Both the front end and the back end can include neural networks that can be trained using the same set of labeled audio signals. The audio signal transforming front end can include a one or more neural networks for per-channel energy normalization transformation of the audio signal, and the back end can include a convolution neural network for classification into spoofed or genuine audio signal. In some embodiments, the transforming audio signal front end can include one or more neural networks for bandpass filtering of the audio signals, and the back end can include a residual neural network for audio signal classification into spoofed or genuine audio signal.

Abstract: A biometric processor comprises: one or more inputs configured to receive first ear biometric data acquired in respect of a first ear of a user and second ear biometric data acquired in respect of a second ear of the user; a processing module configured to perform a biometric algorithm on the first ear biometric data and the second ear biometric data, based on a comparison of the first ear biometric data to a first stored ear biometric template for an authorised user and a comparison of the second ear biometric data to a second stored ear biometric template for the authorised user, to obtain respective first and second biometric scores; a fusion module configured to apply first and second weights to the respective first and second biometric scores to obtain first and second weighted biometric scores, and to combine at least the first and second weighted biometric scores to generate an overall biometric score, wherein the first and second weights are different to each other; and wherein a biometric result is b

Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.

Abstract: In some examples, to mitigate interference of wireless communications, an electronic device that includes a first type wireless component and a second type wireless component receives values of parameters relating to wireless communication using the first type wireless component. The electronic device determines, using a model of a relationship between the parameters relating to wireless communication using the first type wireless component and at least one handover parameter relating to wireless communication using the second type wireless component, a value of the at least one handover parameter based on the received values of the parameters relating to wireless communication using the first type wireless component. It is determined whether the electronic device should be handed over from a first access point to a second access point based on the determined value of the at least one handover parameter.

Abstract: A method of controlling a wireless communication device to dynamically adapt and update roaming parameters stored in the device when operating in a wireless network. The method includes: determining a first roaming metric (M1) for a first wireless access point (AP) of the network when the device is in communication with the first AP; determining a second roaming metric (M2) for a second wireless AP of the network when the device has roamed to the second AP; and determining an adaptation value by subtracting M2 from M1. When the adaptation value is not zero, first roaming parameters associated with the first wireless AP are updated, based on the adaptation value and stored first roaming parameters associated with the first wireless AP and second roaming parameters associated with the second wireless AP are updated based on the adaptation value and stored second roaming parameters associated with the second wireless AP.

Abstract: Apparatus and method pertaining to the calculation of at least one value that represents, at least in part, wireless reception signal strength from the perspective of both a local wireless receiver and a remote receiver that receives wireless transmissions from a local wireless transmitter. By one approach the apparatus directly determines the wireless reception signal strength from the perspective of the local wireless receiver and indirectly determines the wireless reception signal strength from the perspective of the remote receiver.

Abstract: In some examples, to mitigate interference of wireless communications, an electronic device that includes a first type wireless component and a second type wireless component receives values of parameters relating to wireless communication using the first type wireless component. The electronic device determines, using a model of a relationship between the parameters relating to wireless communication using the first type wireless component and at least one handover parameter relating to wireless communication using the second type wireless component, a value of the at least one handover parameter based on the received values of the parameters relating to wireless communication using the first type wireless component. It is determined whether the electronic device should be handed over from a first access point to a second access point based on the determined value of the at least one handover parameter.

Abstract: Apparatus and method pertaining to the calculation of at least one value that represents, at least in part, wireless reception signal strength from the perspective of both a local wireless receiver and a remote receiver that receives wireless transmissions from a local wireless transmitter. By one approach the apparatus directly determines the wireless reception signal strength from the perspective of the local wireless receiver and indirectly determines the wireless reception signal strength from the perspective of the remote receiver.

Abstract: Apparatus and method pertaining to the calculation of at least one value that represents, at least in part, wireless reception signal strength from the perspective of both a local wireless receiver and a remote receiver that receives wireless transmissions from a local wireless transmitter. By one approach the apparatus directly determines the wireless reception signal strength from the perspective of the local wireless receiver and indirectly determines the wireless reception signal strength from the perspective of the remote receiver.

Abstract: An electronic device monitors a quality of a wireless connection between the electronic device and a first access point. Based on the monitoring and a collection of parameters relating to controlling handover between access points, a determination is made regarding whether the electronic device should be handed over to a second access point from the first access point, where the parameters differ for different combinations of the first access point and candidate destination access points for handover of the electronic device from the first access point.

Abstract: A method of controlling a wireless communication device to dynamically adapt and update roaming parameters stored in the device when operating in a wireless network. The method includes: determining a first roaming metric (M1) for a first wireless access point (AP) of the network when the device is in communication with the first AP; determining a second roaming metric (M2) for a second wireless AP of the network when the device has roamed to the second AP; and determining an adaptation value by subtracting M2 from M1. When the adaptation value is not zero, first roaming parameters associated with the first wireless AP are updated, based on the adaptation value and stored first roaming parameters associated with the first wireless AP and second roaming parameters associated with the second wireless AP are updated based on the adaptation value and stored second roaming parameters associated with the second wireless AP.

Abstract: An electronic device monitors a quality of a wireless connection between the electronic device and a first access point. Based on the monitoring and a collection of parameters relating to controlling handover between access points, a determination is made regarding whether the electronic device should be handed over to a second access point from the first access point, where the parameters differ for different combinations of the first access point and candidate destination access points for handover of the electronic device from the first access point.

Abstract: Apparatus and method pertaining to the calculation of at least one value that represents, at least in part, wireless reception signal strength from the perspective of both a local wireless receiver and a remote receiver that receives wireless transmissions from a local wireless transmitter. By one approach the apparatus directly determines the wireless reception signal strength from the perspective of the local wireless receiver and indirectly determines the wireless reception signal strength from the perspective of the remote receiver.