Abstract: A wrist-worn device control method is disclosed. The method includes: collecting first motion data of a wrist-worn device, where the first motion data includes angular velocity information and acceleration information of the wrist-worn device; and identifying, based on the first motion data of the wrist-worn device, that the wrist-worn device changes from a first posture to a second posture, and playing, by the wrist-worn device, media information, where the media information is at least one of a speech message, a text message, or incoming call information that are received by the wrist-worn device, and information displayed by the wrist-worn device, and the second posture is a posture in which a hand of a user wearing the wrist-worn device is close to an ear of the user. Therefore, a message can be played without occupying two hands of the user, interaction is convenient, and user experience is good.

Abstract: Devices, methods, systems, and media for selectively cancelling sounds at a listener's location are described. Sound sources are identified in the listener's environment using microphones and/or remote devices associated with specific sound sources. A user is presented with information identifying the sound sources, including spatial information, and prompting the user to select one or more of the sound sources. After the user designates a sound source as noise, microphones are used to monitor for sound originating from the designated sound source, and the audio information captured by the microphones is processed to generate an anti-noise signal presented to the listener to cancel sounds originating from the selected sound source. A user may designate multiple sound sources as noise and leave other sound sources unfiltered. The techniques may be used in single-listener and multi-listener applications, and in listening and speaking applications.

Abstract: Systems and method for low-power gaze prediction on touch-enabled electronic devices using touch interactions are provided. The method includes receiving an input touch interaction applied to a touch interaction area on a touchscreen display of a touch-enabled device and obtaining, by a gaze prediction module, a predicted gazing area on the touchscreen display based on the input touch interaction. A touch-enabled device has a processor, a touchscreen display and memory storing instructions to carry out the method. The gaze prediction module may utilize a model based on Bayesian inference or convolutional neural networks. Advantageously, gaze prediction is achieved without the use of image-capturing devices and with low power consumption. This can be used to develop intelligent hands-free interactions and personalized recommendation systems.

Abstract: Systems and method for low-power gaze prediction on touch-enabled electronic devices using touch interactions are provided. The method includes receiving an input touch interaction applied to a touch interaction area on a touchscreen display of a touch-enabled device and obtaining, by a gaze prediction module, a predicted gazing area on the touchscreen display based on the input touch interaction. A touch-enabled device has a processor, a touchscreen display and memory storing instructions to carry out the method. The gaze prediction module may utilize a model based on Bayesian inference or convolutional neural networks. Advantageously, gaze prediction is achieved without the use of image-capturing devices and with low power consumption. This can be used to develop intelligent hands-free interactions and personalized recommendation systems.