Abstract: A system and method for identifying a user of a device includes comparing audio received by a device with acoustic fingerprint information to identify a user of the device. Image data, video data and other data may also be used in the identification of the user. Once the user is identified, operation of the device may be customized based on the user. Further, once the user is identified, data can be associated with the user, for example, usage data, location data, gender data, age data, dominant hand data of the user, and other data. This data can then be used to further customize the operation of the device to the specific user.

Abstract: A computing device can obtain usage data associated with the device. The usage data indicate how the computing device operates or how the device is used. The device can analyze the usage data to recognize usage patterns. The usage patterns can correspond to recurring actions or tasks initiated by the user using the device, such as actions or tasks initiated due to the user's habits and/or routines. Based on the usage patterns, the device can determine a task that has a sufficient likelihood of being performed using the device within a specified or determined time (e.g., 5 minutes from now, one year from now, etc.). The device can provide information (e.g., recommendations) associated with the task, and likely relevant to the user. The user can use the provided information to perform the task, thereby increasing the ease of access or efficiency associated with performing the task.

Abstract: A system and method for identifying a user of a device includes comparing audio received by a device with acoustic fingerprint information to identify a user of the device. Image data, video data and other data may also be used in the identification of the user. Once the user is identified, operation of the device may be customized based on the user. Further, once the user is identified, data can be associated with the user, for example, usage data, location data, gender data, age data, dominant hand data of the user, and other data. This data can then be used to further customize the operation of the device to the specific user.

Abstract: A system and method for identifying a user of a device includes comparing audio received by a device with acoustic fingerprint information to identify a user of the device. Image data, video data and other data may also be used in the identification of the user. Once the user is identified, operation of the device may be customized based on the user. Further, once the user is identified, data can be associated with the user, for example, usage data, location data, gender data, age data, dominant hand data of the user, and other data. This data can then be used to further customize the operation of the device to the specific user.

Abstract: Described herein are systems, devices and methods for presenting content based on the spatial relationship between a media device and a user of the media device. The media device may present content based on an angle between an eye axis of the user and a device axis of the media device.

Abstract: A computing device can obtain usage data associated with the device. The usage data indicate how the computing device operates or how the device is used. The device can analyze the usage data to recognize usage patterns. The usage patterns can correspond to recurring actions or tasks initiated by the user using the device, such as actions or tasks initiated due to the user's habits and/or routines. Based on the usage patterns, the device can determine a task that has a sufficient likelihood of being performed using the device within a specified or determined time (e.g., 5 minutes from now, one year from now, etc.). The device can provide information (e.g., recommendations) associated with the task, and likely relevant to the user. The user can use the provided information to perform the task, thereby increasing the ease of access or efficiency associated with performing the task.

Abstract: Approaches to enable a computing device, such as a phone or tablet computer, to compute a probability that the user currently using the device matches a profile of an authorized user and to set or change a security level of the computing device based on the computed probability. The security level can be one of many security levels each having a different scope of authorized access to data or functions of the computing device. The computing device may periodically re-compute the probability and change the security level whenever the probability crosses certain predefined thresholds.

Abstract: A system and method for identifying a user of a device includes comparing audio received by a device with acoustic fingerprint information to identify a user of the device. Image data, video data and other data may also be used in the identification of the user. Once the user is identified, operation of the device may be customized based on the user. Further, once the user is identified, data can be associated with the user, for example, usage data, location data, gender data, age data, dominant hand data of the user, and other data. This data can then be used to further customize the operation of the device to the specific user.

Abstract: In some examples, an electronic device may include one or more recognition devices able to be used to recognize a current user. If the electronic device recognizes that a primary user, such as an owner, is currently using the electronic device, the electronic device may allow access to all of the primary user's private information and all of the features of the electronic device. On the other hand, when the electronic device determines that the current user is an unknown user, or that the current user is a known user who is authorized to access only limited information or features of the electronic device, the electronic device may send a communication to restrict the current user from accessing private information of the primary user. In some cases, the electronic device may enable the primary user to designate which items known users and/or unknown users may access.

Abstract: Content is presented by media devices to a user. Described herein are techniques and systems for determining occurrence of one or more events at, or proximate to, the media device. Once an event is determined, one or more actions to modify presentation of the content may be initiated. The actions may include starting presentation of the content, stopping presentation of the content, applying noise mitigation techniques to the content, and so forth. The noise mitigation techniques may include modification of an intended signal from the content to produce a noise mitigation zone 118 proximate to, or encompassing, at least a portion of the user's head.

Abstract: Described herein are systems, devices and methods for presenting content based on the spatial relationship between a media device and a user of the media device. The media device may present content based on an angle between an eye axis of the user and a device axis of the media device.

Abstract: Systems and approaches are provided for automating privacy control for a computing device based on a privacy or security context of the device. The privacy or security context of the computing device can be determined by analyzing sensor data or other input data captured by the device. The sensor and other input data can provide information such as a location of the computing device or the presence of other persons within the vicinity of the device to indicate whether the user is situated within a private or secure setting or a public or unsecure setting. A privacy or security control can be updated based on the determined privacy or security context, such as modifying a manner of displaying a pin or password during entry, elements of a home screen of the computing device, or preview content of user applications.

Abstract: An adaptive navigation system anticipates a user's interactions with a device, modifying the device in the future based on past user movements and interactions. The system records a user's movement patterns and correlates movement patterns with how the user interacts with the device. When the movement patterns recur, the system modifies at least one behavior of the device based upon past interaction of the user with the device.