Abstract: A context-aware voice guidance method is provided that interacts with other voice services of a user device. The voice guidance does not provide audible guidance while the user is making a verbal request to any of the voice-activated services. Instead, the voice guidance transcribes its output on the screen while the verbal requests from the user are received. In some embodiments, the voice guidance only provides a short warning sound to get the user's attention while the user is speaking on a phone call or another voice-activated service is providing audible response to the user's inquires. The voice guidance in some embodiments distinguishes between music that can be ducked and spoken words, for example from an audiobook, that the user wants to pause instead of being skipped. The voice guidance ducks music but pauses spoken words of an audio book in order to provide voice guidance to the user.

Abstract: A mobile device with a route prediction engine is provided that can predict current/future destinations or routes to destinations for the user, and can relay prediction information to the user. The engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on user-specific data. The user-specific data includes data about (1) previous destinations traveled, (2) previous routes taken, (3) locations of calendared events, (4) locations of events for which the user has electronic tickets, and/or (5) addresses parsed from e-mails and/or messages. The prediction engine relies on one or more of user-specific data stored on the device and data stored outside of the device by external devices/servers.

Abstract: Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user’s calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user.

Abstract: Exemplary methods, apparatuses, and systems read location data representing a current location of a mobile device. The location data for the mobile device is taken at a first sampling rate. Upon determining that the location data indicates that the mobile device is approaching a geographic area having a history of wireless communication loss, the mobile device is triggered to increase location data sampling from the first sampling rate to a second sampling rate.

Abstract: Exemplary methods, apparatuses, and systems read location data representing a current location of a mobile device. The location data for the mobile device is taken at a first sampling rate. Upon determining that the location data indicates that the mobile device is approaching a geographic area having a history of wireless communication loss, the mobile device is triggered to increase location data sampling from the first sampling rate to a second sampling rate.

Abstract: Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user.

Abstract: A context-aware voice guidance method is provided that interacts with other voice services of a user device. The voice guidance does not provide audible guidance while the user is making a verbal request to any of the voice-activated services. Instead, the voice guidance transcribes its output on the screen while the verbal requests from the user are received. In some embodiments, the voice guidance only provides a short warning sound to get the user's attention while the user is speaking on a phone call or another voice-activated service is providing audible response to the user's inquires. The voice guidance in some embodiments distinguishes between music that can be ducked and spoken words, for example from an audiobook, that the user wants to pause instead of being skipped. The voice guidance ducks music but pauses spoken words of an audio book in order to provide voice guidance to the user.

Abstract: A context-aware voice guidance method is provided that interacts with other voice services of a user device. The voice guidance does not provide audible guidance while the user is making a verbal request to any of the voice-activated services. Instead, the voice guidance transcribes its output on the screen while the verbal requests from the user are received. In some embodiments, the voice guidance only provides a short warning sound to get the user's attention while the user is speaking on a phone call or another voice-activated service is providing audible response to the user's inquires. The voice guidance in some embodiments distinguishes between music that can be ducked and spoken words, for example from an audiobook, that the user wants to pause instead of being skipped. The voice guidance ducks music but pauses spoken words of an audio book in order to provide voice guidance to the user.

Abstract: A context-aware voice guidance method is provided that interacts with other voice services of a user device. The voice guidance does not provide audible guidance while the user is making a verbal request to any of the voice-activated services. Instead, the voice guidance transcribes its output on the screen while the verbal requests from the user are received. In some embodiments, the voice guidance only provides a short warning sound to get the user's attention while the user is speaking on a phone call or another voice-activated service is providing audible response to the user's inquires. The voice guidance in some embodiments distinguishes between music that can be ducked and spoken words, for example from an audiobook, that the user wants to pause instead of being skipped. The voice guidance ducks music but pauses spoken words of an audio book in order to provide voice guidance to the user.

Abstract: Exemplary methods, apparatuses, and systems receive an indication that an order associated with a user account is ready for pickup. One or more messages to a user device associated with the user account are transmitted in response to the received indication that the order is ready. The one or more messages include identification of the order as being ready for pickup, a pickup location for the order, and a threshold distance from the pickup location for the order. Location data is received at a limited interval from a user device while the user device is outside of the threshold distance from the pickup location. Location data is received at a more frequent interval than the limited interval while the user device is within the threshold distance. The location data is transmitted to a local pickup device to trigger an alert when the user device is approaching the pickup location.

Abstract: Exemplary methods, apparatuses, and systems receive an indication that an order associated with a user account is ready for pickup. One or more messages to a user device associated with the user account are transmitted in response to the received indication that the order is ready. The one or more messages include identification of the order as being ready for pickup, a pickup location for the order, and a threshold distance from the pickup location for the order. Location data is received at a limited interval from a user device while the user device is outside of the threshold distance from the pickup location. Location data is received at a more frequent interval than the limited interval while the user device is within the threshold distance. The location data is transmitted to a local pickup device to trigger an alert when the user device is approaching the pickup location.

Abstract: A mobile device with a route prediction engine is provided that can predict current/future destinations or routes to destinations for the user, and can relay prediction information to the user. The engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on user-specific data. The user-specific data includes data about (1) previous destinations traveled, (2) previous routes taken, (3) locations of calendared events, (4) locations of events for which the user has electronic tickets, and/or (5) addresses parsed from e-mails and/or messages. The prediction engine relies on one or more of user-specific data stored on the device and data stored outside of the device by external devices/servers.

Abstract: Some embodiments of the invention provide a mobile device with a novel route prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for the device's user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user.

Abstract: Embodiments may include determining a navigation route between an origination and a destination; the route may span multiple portions of a map. Embodiments may also include receiving an order of priority in which to receive the multiple portions of the map; the order may be generated based on distinct levels of expected signal strength for each of the multiple portions. For instance, within the order of priority, map portions associated with areas of low signal strength may be ranked higher than areas of higher signal strength. Embodiments may also include acquiring at least some of the portions of the map according to the order of priority, and generating a map display comprising the multiple portions of the map. For instance, map portions associated with areas of poor reception may be downloaded first whereas map portions associated with strong signal strength may be downloaded on-the-fly during route navigation.

Abstract: Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user.

Abstract: Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user.

Abstract: Some embodiments of the invention provide a navigation application that presents road signs during a navigation presentation. In presenting the road signs, the application of some embodiments differentiates the appearance of road signs at junctions that require a change of direction from road signs at junctions that do not require a change of direction. The application may perform processes that ensure that it arranges the road signs on the map in an aesthetically pleasing manner. In addition, the navigation application of some embodiments does not display too many road signs along the navigated route so that the route is not by occluded by too many road signs.

Abstract: Some embodiments provide a navigation application. The navigation application includes an interface for receiving data describing junctures along a route from a first location on a map to a second location on the map. The data for each juncture includes a set of angles at which roads leave the juncture. The navigation application includes a juncture decoder for synthesizing, from the juncture data, instruction elements for each juncture that describe different aspects of a maneuver to be performed at the juncture. The navigation application includes an instruction generator for generating at least two different instruction sets for a maneuver by combining one or more of the instruction elements for the juncture at which the maneuver is to be performed. The navigation application includes an instruction retriever for selecting one of the different instruction sets for the maneuver according to a context in which the instruction set will be displayed.

Abstract: A context-aware voice guidance method is provided that interacts with other voice services of a user device. The voice guidance does not provide audible guidance while the user is making a verbal request to any of the voice-activated services. Instead, the voice guidance transcribes its output on the screen while the verbal requests from the user are received. In some embodiments, the voice guidance only provides a short warning sound to get the user's attention while the user is speaking on a phone call or another voice-activated service is providing audible response to the user's inquires. The voice guidance in some embodiments distinguishes between music that can be ducked and spoken words, for example from an audiobook, that the user wants to pause instead of being skipped. The voice guidance ducks music but pauses spoken words of an audio book in order to provide voice guidance to the user.

Abstract: A context-aware voice guidance method is provided that interacts with other voice services of a user device. The voice guidance does not provide audible guidance while the user is making a verbal request to any of the voice-activated services. Instead, the voice guidance transcribes its output on the screen while the verbal requests from the user are received. In some embodiments, the voice guidance only provides a short warning sound to get the user's attention while the user is speaking on a phone call or another voice-activated service is providing audible response to the user's inquires. The voice guidance in some embodiments distinguishes between music that can be ducked and spoken words, for example from an audiobook, that the user wants to pause instead of being skipped. The voice guidance ducks music but pauses spoken words of an audio book in order to provide voice guidance to the user.