Abstract:
A device includes a memory and a processor. The memory is configured to store a threshold. The processor is configured to authenticate a user based on authentication data. The processor is also configured to, in response to determining that the user is authenticated, generate a correlation score indicating a correlation between a first signal received from a first sensor and a second signal received from a second sensor. The processor is also configured to determine liveness of the user based on a comparison of the correlation score and the threshold.
Abstract:
A method for verifying at least one sound sample to be used in generating a sound detection model in an electronic device includes receiving a first sound sample; extracting a first acoustic feature from the first sound sample; receiving a second sound sample; extracting a second acoustic feature from the second sound sample; and determining whether the second acoustic feature is similar to the first acoustic feature.
Abstract:
A method for activating a voice assistant function in a mobile device is disclosed. The method includes receiving an input sound stream by a sound sensor and determining a context of the mobile device. The method may determine the context based on the input sound stream. For determining the context, the method may also obtain data indicative of the context of the mobile device from at least one of an acceleration sensor, a location sensor, an illumination sensor, a proximity sensor, a clock unit, and a calendar unit in the mobile device. In this method, a threshold for activating the voice assistant function is adjusted based on the context. The method detects a target keyword from the input sound stream based on the adjusted threshold. If the target keyword is detected, the method activates the voice assistant function.
Abstract:
A method for controlling voice activation by a target keyword in a mobile device is disclosed. The method includes receiving an input sound stream. When the input sound stream indicates speech, the voice activation unit is activated to detect the target keyword and at least one sound feature is extracted from the input sound stream. Further, the method includes deactivating the voice activation unit when the at least one sound feature indicates a non-target keyword.
Abstract:
Various arrangements for detecting a type of sound, such as speech, are presented. A plurality of audio snippets may be sampled. A period of time may elapse between consecutive audio snippets. A hypothetical test may be performed using the sampled plurality of audio snippets. Such a hypothetical test may include weighting one or more hypothetical values greater than one or more other hypothetical values. Each hypothetical value may correspond to an audio snippet of the plurality of audio snippets. The hypothetical test may further include using at least the greater weighted one or more hypothetical values to determine whether at least one audio snippet of the plurality of audio snippets comprises the type of sound.
Abstract:
A method for activating a voice assistant function in a mobile device is disclosed. The method includes receiving an input sound stream by a sound sensor and determining a context of the mobile device. The method may determine the context based on the input sound stream. For determining the context, the method may also obtain data indicative of the context of the mobile device from at least one of an acceleration sensor, a location sensor, an illumination sensor, a proximity sensor, a clock unit, and a calendar unit in the mobile device. In this method, a threshold for activating the voice assistant function is adjusted based on the context. The method detects a target keyword from the input sound stream based on the adjusted threshold. If the target keyword is detected, the method activates the voice assistant function.
Abstract:
A method for controlling an application in a mobile device is disclosed. The method includes receiving environmental information, inferring an environmental context from the environmental information, and controlling activation of the application based on a set of reference models associated with the inferred environmental context. In addition, the method may include receiving a sound input, extracting a sound feature from the sound input, transmitting the sound feature to a server configured to group a plurality of mobile devices into at least one similar context group, and receiving, from the server, information on a leader device or a non-leader device and the at least one similar context group.
Abstract:
A method, which is performed in a first electronic device, for authorizing access to a second electronic device is disclosed. The method may include establishing communication between the first electronic device and the second electronic device. The method may also obtain data indicative of a motion of at least one of the first and second electronic devices in response to a movement of the at least one of the first and second electronic devices. Based on the data, a control signal authorizing access to the second electronic device is generated, and transmitted to the second electronic device.
Abstract:
A method of detecting a target keyword from an input sound for activating a function in a mobile device is disclosed. In this method sound features are extracted from the input stream and statistics are generated (340) including the mean value and the variance of a particular sound feature. Based on the statistics the method adaptively skips the normalisation of a sound feature when the difference between the present value and the previous value is not significant, this has the effect of lowering the process load. In detail a first plurality of sound features is received in a buffer (330), and a second plurality of sound features is received in the buffer 330). While receiving each of the second plurality of sound features in the buffer, a first number of the sound features are processed from the buffer. The first number of the sound features includes two or more sound features. Further, the method includes determining a keyword score (360) for each of the processed sound features and detecting the input sound as the target keyword (370) if at least one of the keyword scores is greater than a threshold score.