Abstract: Technologies disclosed herein relate to construction of a composite image to provide a parallax effect. An image is generated, and a first computer-readable image and a second computer-readable image are generated based upon the image. The first computer-readable image represents foreground of a scene and the second computer-readable image represents background of a scene. A location of eyes of a viewer relative to a display is determined, and the first computer-readable image is overlaid upon the second computer-readable image at a position that is based upon the location of the eyes of the viewer.

Abstract: Systems and methods are disclosed for transitioning communication sessions across services. In one implementation, a first communication is received from a user via a first service. The first communication is associated with a communication session. The first communication is processed to identify a request with respect to a second service. The second service is initiated in response to the request.

Abstract: In an embodiment described herein, a method for a mechanism to turn a post processing feature in the Device Media Foundation Transform is described. The method comprises managing, at a device integration service executing on a computing device, a current setting of a feature and updating the current setting as stored in a registry in response to a changed setting of the feature and asserting a setting changed event. The method also includes applying the updated current setting to captured media samples via the Device Media Foundation Transform in response to the asserted setting changed event.

Abstract: In an embodiment described herein, a method for a mechanism to turn a post processing feature in the Device Media Foundation Transform is described. The method comprises managing, at a device integration service executing on a computing device, a current setting of a feature and updating the current setting as stored in a registry in response to a changed setting of the feature and asserting a setting changed event. The method also includes applying the updated current setting to captured media samples via the Device Media Foundation Transform in response to the asserted setting changed event.

Abstract: One disclosed example provides a computing system configured to receive input defining a machine conversation dialog flow, display in an editing user interface a first representation of the machine conversation dialog flow in the form of a symbolic representation, receive input requesting display of a second representation of the machine conversation dialog flow, and in response to the request display in the editing user interface the machine conversation dialog flow in the character-based representation. The computing system is further configured to, based upon the machine conversation dialog flow, update a machine conversation schema template to form an updated machine conversation schema, and form an agent definition file based upon the updated machine conversation schema for use in executing the machine conversation dialog flow.

Abstract: An electronic device can receive user input via voice or text that includes tasks to be performed. A digital personal assistant infrastructure service can control to which registered action provider the task is assigned. Per-task action provider preferences can be stored. If a preferred action provider is not able to complete the task, the task can still be performed by a registered action provider that has appropriate capabilities. Machine learning can determine a user's preferences. Resource conservation and effective user interaction can result.

Abstract: Systems and methods are disclosed for transitioning communication sessions across services. In one implementation, a first communication is received from a user via a first service. The first communication is associated with a communication session. The first communication is processed to identify a request with respect to a second service. The second service is initiated in response to the request.

Abstract: A method to execute computer-actionable directives conveyed in human speech comprises: receiving audio data recording speech from one or more speakers; converting the audio data into a linguistic representation of the recorded speech; detecting a target corresponding to the linguistic representation; committing to the data structure language data associated with the detected target and based on the linguistic representation; parsing the data structure to identify one or more of the computer-actionable directives; and submitting the one or more of the computer-actionable directives to the computer for processing.

Abstract: Examples are disclosed that relate to a conversation runtime for automating transitions of conversational user interfaces. One example provides a computing system comprising a logic subsystem and a data-holding subsystem. The data-holding subsystem comprises instructions executable by the logic subsystem to execute a conversation runtime configured to receive one or more agent definitions for a conversation robot program, each agent definition defining a state machine including a plurality of states, detect a conversation trigger condition, select an agent definition for a conversation based on the conversation trigger condition, and execute a conversation dialog with a client computing system using the agent definition selected for the conversation and automatically transition the state machine between different states of the plurality of states during execution of the conversation dialog.

Abstract: One disclosed example provides a computing system configured to receive input defining a machine conversation dialog flow, display in an editing user interface a first representation of the machine conversation dialog flow in the form of a symbolic representation, receive input requesting display of a second representation of the machine conversation dialog flow, and in response to the request display in the editing user interface the machine conversation dialog flow in the character-based representation. The computing system is further configured to, based upon the machine conversation dialog flow, update a machine conversation schema template to form an updated machine conversation schema, and form an agent definition file based upon the updated machine conversation schema for use in executing the machine conversation dialog flow.

Abstract: Touchscreen testing techniques are described. In one or more implementations, a piece of conductor (e.g., metal) is positioned as proximal to a touchscreen device and the touchscreen device is tested by simulating a touch of a user. This technique may be utilized to perform a variety of different testing of a touchscreen device, such as to test latency and probabilistic latency. Additional techniques are also described including contact geometry testing techniques.

Abstract: Techniques are described for headlessly completing a task of an application in the background of a digital personal assistant. For example, a method can include receiving a voice input via a microphone. Natural language processing can be performed using the voice input to determine a user voice command. The user voice command can include a request to perform a task of the application. The application can be caused to execute the task as a background process without a user interface of the application appearing. A user interface of the digital personal assistant can provide a response to the user, based on a received state associated with the task, so that the response comes from within a context of the user interface of the digital personal assistant without surfacing the user interface of the application.

Abstract: Techniques are described for discovering capabilities of voice-enabled resources. A voice-controlled digital personal assistant can respond to user requests to list available voice-enabled resources that are capable of performing a specific task using voice input. The voice-controlled digital personal assistant can also respond to user requests to list the tasks that a particular voice-enabled resource can perform using voice input. The voice-controlled digital personal assistant can also support a practice mode in which users practice voice commands for performing tasks supported by voice-enabled resources.

Abstract: Techniques are described for discovering capabilities of voice-enabled resources. A voice-controlled digital personal assistant can respond to user requests to list available voice-enabled resources that are capable of performing a specific task using voice input. The voice-controlled digital personal assistant can also respond to user requests to list the tasks that a particular voice-enabled resource can perform using voice input. The voice-controlled digital personal assistant can also support a practice mode in which users practice voice commands for performing tasks supported by voice-enabled resources.

Abstract: An electronic device in a topology of interconnected electronic devices can listen for a wake phrase and voice commands. The device can control when and how it responds so that a single device responds to voice commands. Per-task device preferences can be stored for a user. If a preferred device is not available, the task can still be performed on a device that has appropriate capabilities. Machine learning can determine a user's preferences. Power conservation and effective user interaction can result.

Abstract: Acoustic touch sensitive testing techniques are described. In one or more implementations, a touch-sensitive surface of a touch-sensitive device is tested by detecting contact made with the touch sensitive surface using an acoustic sensor and comparing data describing the contact that is received from the acoustic sensor with data describing the contact that is received from the touch-sensitive device.

Abstract: Touchscreen testing techniques are described. In one or more implementations, a conductor is placed proximal to a touchscreen device and the touchscreen device is tested by simulating a touch of a user by placing the conductor in a grounded state and lack of a touch by the user by placing the conductor in an ungrounded state.

Abstract: Systems, methods, and computer-readable storage media are provided for efficient real-time ink stroke smoothing, trajectory prediction, and GPU-leveraged rendering of ink stroke input. First and second ink points are received and an active Bézier approximation is computed based thereupon. Sequentially later in time that the first and second ink points, a third ink point is received. It is determined whether the third ink point adequately fits the active Bézier approximation. Where it is determined that the third ink point adequately fits, an updated active Bézier approximation is computed that includes the first, second and third ink points. Where it is determined that the third ink point fails to adequately fit, a different new Bézier approximation is computed that includes the third ink point but not the first and second ink points. Leveraging a GPU, a smoothed ink stroke based upon the Bézier approximation(s) is rendered.

Abstract: A method for providing digital personal assistant responses may include receiving, by a digital personal assistant associated with a plurality of reactive agents, a user input initiating a dialog with the digital personal assistant within the computing device. In response to receiving the input, an operation mode of the computing device may be detected from a plurality of available operation modes. One of the plurality of reactive agents can be selected based on the received input. A plurality of response strings associated with the selected reactive agent can be accessed. At least one of the plurality of response strings is selected based at least on the operation mode and at least one hardware characteristic of the computing device. The selected at least one of the plurality of response strings is providing during the dialog, as a response to the user input.

Abstract: The techniques described herein are directed to receiving parameters directed to correcting spatial error and/or jitter associated with an interaction device connected to a computing device. In some instances, the parameters are encrypted parameters that may be decrypted and consumed to correct the spatial error and/or the jitter associated with the interaction device. For instance, the parameters may provide an adjustment to one or more reported positions of input received from a detection area of the interaction device, so that a display position more accurately reflects, based on the adjustment, an actual position of input on the detection area of the interaction device.