Content generation framework
    33.
    发明授权

    公开(公告)号:US11580182B2

    公开(公告)日:2023-02-14

    申请号:US17099295

    申请日:2020-11-16

    Abstract: Techniques for performing outputting additional content associated with but nonresponsive to an input command are described. A system receives input data from a device. The system determines an intent representing the input data and receives first output data responsive to the input data. The system determines, based on context data, that additional content associated with the first output data but nonresponsive to the input data should be output. The system receives second output data associated with but nonresponsive to the input data thereafter. The system then presents first content corresponding to the first output data and second content corresponding to the second output data.

    Creating scenes from voice-controllable devices

    公开(公告)号:US11422772B1

    公开(公告)日:2022-08-23

    申请号:US16424285

    申请日:2019-05-28

    Abstract: Techniques for causing different devices to perform different operations using a single voice command are described herein. In some instances, a user may define a “scene”, in which a user sets different devices to different states and then associates an utterance with those states or with the operations performed by the devices to reach those states. For instance, a user may dim a light, turn on his television, and turn on his set-top box before sending a request to a local device or to a remote service to associate those settings with a predefined utterance, such as “my movie scene”. Thereafter, the user may cause the light to dim, the television to turn on, and the set-top box to turn on simply by issuing the voice command “execute my movie scene”.

    Naming devices via voice commands
    37.
    发明授权

    公开(公告)号:US10825454B1

    公开(公告)日:2020-11-03

    申请号:US16031909

    申请日:2018-07-10

    Abstract: Techniques for naming devices via voice commands are described herein. For instance, a user may issue a voice command to a voice-controlled device stating, “you are the kitchen device”. Thereafter, the device may respond to voice commands directed, by name, to this device. For instance, the user may issue a voice command requesting to “play music on my kitchen device”. Given that the user has configured the device to respond to this name, the device may respond to the command by outputting the requested music.

    Noise cancellation for open microphone mode

    公开(公告)号:US10217461B1

    公开(公告)日:2019-02-26

    申请号:US15498086

    申请日:2017-04-26

    Abstract: A system has multiple audio-enabled devices that communicate with one another over an open microphone mode of communication. When a user says a trigger word, the nearest device validates the trigger word and opens a communication channel with another device. As the user talks, the device receives the speech and generates an audio signal representation that includes the user speech and may additionally include other background or interfering sound from the environment. The device transmits the audio signal to the other device as part of a conversation, while continually analyzing the audio signal to detect when the user stops talking. This analysis may include watching for a lack of speech in the audio signal for a period of time, or an abrupt change in context of the speech (indicating the speech is from another source), or canceling noise or other interfering sound to isolate whether the user is still speaking. Once the device confirms that the user has stopped talking, the device transitions from a transmission mode to a reception mode to await a reply in the conversation.

    Training models using voice tags
    40.
    发明授权

    公开(公告)号:US10163437B1

    公开(公告)日:2018-12-25

    申请号:US15171787

    申请日:2016-06-02

    Abstract: Techniques for training machine-learning algorithms with the aid of voice tags are described herein. An environment may include sensors configured to generate sensor data and devices configured to perform operations. Sensor data as well as indications of actions performed by devices within the environment may be collected over time and analyzed to identify one or more patterns. Over time, a model that includes an association between this sensor data and device actions may be created and trained such that one or more device actions may be automatically initiated in response to identifying sensor data matching the sensor data of the model. To aid in the training, a user may utter a predefined voice tag each time she performs a particular sequence of actions, with the voice tag indicating to the system that temporally proximate sensor data and device-activity data should be used to train a particular model.

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