Abstract: A method for personalizing media content for a user is provided. The method includes, at an electronic device, streaming a first media item from a first set of media items, the first set of media items compiled using a first recommendation hypothesis. The method further includes, while streaming the first media item, in response to a first user request, selecting, without user intervention, a second set of media items, distinct from the first set of media items, including determining a presentation order of a plurality of sets of media items using a heuristic applied to the plurality of sets of media items. The second set of media items is compiled using a second recommendation hypothesis, wherein the second recommendation hypothesis is distinct from the first recommendation hypothesis. The method includes streaming a second media item from the second set of media items.

Abstract: A method includes retrieving a plurality of transcripts from a database. Each transcript in the plurality of transcripts corresponds to audio from a media content item of a plurality of media content items that are provided by a media providing service. The method also includes applying each transcript of the plurality of transcripts to a trained computational model, and receiving a user request for information regarding a topic. The method further includes, in response to the user request, identifying a transcript from the database that is relevant to the topic, and a position within the transcript that is relevant to the topic. The method also includes providing, by the media providing service, at least a portion of a media content item corresponding to the identified transcript, beginning at a starting position that is based on the position within the identified transcript that is relevant to the topic.

Abstract: A method for personalizing media content for a user is provided. The method includes, at an electronic device, streaming a first media item from a first set of media items, the first set of media items compiled using a first recommendation hypothesis. The method further includes, while streaming the first media item, in response to a first user request, selecting, without user intervention, a second set of media items, distinct from the first set of media items, including determining a presentation order of a plurality of sets of media items using a heuristic applied to the plurality of sets of media items. The second set of media items is compiled using a second recommendation hypothesis, wherein the second recommendation hypothesis is distinct from the first recommendation hypothesis. The method includes streaming a second media item from the second set of media items.

Abstract: A system for refinement of a voice query interpretation interprets a voice query received at a voice-enabled device to identify commands responsive to the voice query for execution at the voice-enabled device, and enables refinement of the interpretation of the voice query through a graphical user interface generated and displayed at a GUI-capable device. The graphical user interface includes a set of selectable options relating to the voice query and identifying a refinement of the interpretation of the voice query to enable control and/or adjustment of commands to be executed by the voice-enabled device. For example, if one of the selectable options is selected, then a command associated with the selected option is identified and executed by the voice-enabled device.

Abstract: A method includes retrieving a plurality of transcripts from a database. Each transcript in the plurality of transcripts corresponds to audio from a media content item of a plurality of media content items that are provided by a media providing service. The method also includes applying each transcript of the plurality of transcripts to a trained computational model, and receiving a user request for information regarding a topic. The method further includes, in response to the user request, identifying a transcript from the database that is relevant to the topic, and a position within the transcript that is relevant to the topic. The method also includes providing, by the media providing service, at least a portion of a media content item corresponding to the identified transcript, beginning at a starting position that is based on the position within the identified transcript that is relevant to the topic.

Abstract: A system for refinement of a voice query interpretation interprets a voice query received at a voice-enabled device to identify commands responsive to the voice query for execution at the voice-enabled device, and enables refinement of the interpretation of the voice query through a graphical user interface generated and displayed at a GUI-capable device. The graphical user interface includes a set of selectable options relating to the voice query and identifying a refinement of the interpretation of the voice query to enable control and/or adjustment of commands to be executed by the voice-enabled device. For example, if one of the selectable options is selected, then a command associated with the selected option is identified and executed by the voice-enabled device.

Abstract: An electronic device displays a first icon comprising a shape. While displaying the first icon, the device receives a voice command corresponding to a request for media content from the application. In response to, and while receiving, the voice command, the device dynamically animates the first icon, including distorting a radius of a portion of the shape in accordance with a direction of the voice command. The dynamic animation indicates that the electronic device is in a first state. After the voice command is completed, the device displays an indication that the device is in a second state that is distinct from the first state.

Abstract: A system for refinement of a voice query interpretation interprets a voice query received at a voice-enabled device to identify commands responsive to the voice query for execution at the voice-enabled device, and enables refinement of the interpretation of the voice query through a graphical user interface generated and displayed at a GUI-capable device. The graphical user interface includes a set of selectable options relating to the voice query and identifying a refinement of the interpretation of the voice query to enable control and/or adjustment of commands to be executed by the voice-enabled device. For example, if one of the selectable options is selected, then a command associated with the selected option is identified and executed by the voice-enabled device.

Abstract: A system for refinement of a voice query interpretation interprets a voice query received at a voice-enabled device to identify commands responsive to the voice query for execution at the voice-enabled device, and enables refinement of the interpretation of the voice query through a graphical user interface generated and displayed at a GUI-capable device. The graphical user interface includes a set of selectable options relating to the voice query and identifying a refinement of the interpretation of the voice query to enable control and/or adjustment of commands to be executed by the voice-enabled device. For example, if one of the selectable options is selected, then a command associated with the selected option is identified and executed by the voice-enabled device.

Abstract: A system for refinement of a voice query interpretation interprets a voice query received at a voice-enabled device to identify commands responsive to the voice query for execution at the voice-enabled device, and enables refinement of the interpretation of the voice query through a graphical user interface generated and displayed at a GUI-capable device. The graphical user interface includes a set of selectable options relating to the voice query and identifying a refinement of the interpretation of the voice query to enable control and/or adjustment of commands to be executed by the voice-enabled device. For example, if one of the selectable options is selected, then a command associated with the selected option is identified and executed by the voice-enabled device.