Steering for Unstructured Media Stations

Abstract

The present technology pertains to steering a playlisting service toward media items that are likely to receive positive feedback from a user operating a client device. The present technology permits a request to play media items without requiring an input context. A playlist service can begin to receive feedback on the playback of the media items and the received playback can be utilized by a steering service in response to a steering request to identify media items for playback that are likely to receive positive feedback based on the feedback received on a sequence of previously played media items.

1 . (canceled) 
     
     
         2 . At least one non-transitory computer readable medium comprising instructions stored on the computer readable medium that when executed cause a computing system to:
 receive a request to play unspecified media items from a client device;   transmit, in response to the request, a first collection of media items for playback to the client device;   receive, during playback of the first collection of media items, a steering request and listener feedback from the client device, wherein the steering request indicates a request to modify criteria by which media items are selected for playback and the listener feedback includes a feedback sequence for the first collection of media items;   determine a second collection of media items for playback based on the steering request and the listener feedback; and   transmit the second collection of media items for playback to the client device.   
     
     
         3 . The at least one non-transitory computer readable medium of  claim 2 , wherein the determination of the second collection of media items is based on user profile information associated with a user of the client device that provided the request to play unspecified media items, the user profile information identifying one or more media item preferences of the user. 
     
     
         4 . The at least one non-transitory computer readable medium of  claim 2 , wherein the determination of the second collection of media items is based on user taste information associated with a user of the client device that provided the request to play unspecified media items, the user profile information identifying one or more media item preferences of the user, wherein user taste information represents favorite genres of the user. 
     
     
         5 . The at least one non-transitory computer readable medium of  claim 2 , wherein the listener feedback includes implied feedback data including one or more observations, wherein the one or more observations include increased volume and client device orientation. 
     
     
         6 . The at least one non-transitory computer readable medium of  claim 2 , wherein the determination of the second collection of media items includes selection of one or more candidate media items for playback by the client device, wherein the one or more candidate media items were not included with the first collection of media items. 
     
     
         7 . The at least one non-transitory computer readable medium of  claim 2 , wherein the determination of the second collection of media items is performed using a machine learned function. 
     
     
         8 . The at least one non-transitory computer readable medium of  claim 7 , wherein the instructions are effective to cause the computing system to train a machine learning system to yield the machine learned function, the instructions cause the computing system to:
 input feedback data for media items played in a historical sequence to the machine learning system, where some of the listener feedback for the media items played in the historical sequence is negative feedback;   learn, using the machine learning system, which media items were played in the historical sequence after the negative feedback; and   output the machine learned function by the machine learning system.   
     
     
         9 . A method comprising:
 receiving a request to play unspecified media items from a client device;   transmitting, in response to the request, a first collection of media items for playback to the client device;   receiving, during playback of the first collection of media items, a steering request and listener feedback from the client device, wherein the steering request indicates a request to modify criteria by which media items are selected for playback and the listener feedback includes a feedback sequence for the first collection of media items;   determining a second collection of media items for playback based on the steering request and the listener feedback; and   transmitting the second collection of media items for playback to the client device.   
     
     
         10 . The method of  claim 10 , wherein the determination of the second collection of media items is based on user profile information associated with a user of the client device that provided the request to play unspecified media items, the user profile information identifying one or more media item preferences of the user. 
     
     
         11 . The method of  claim 10 , wherein the determination of the second collection of media items is based on user taste information associated with a user of the client device that provided the request to play unspecified media items, the user profile information identifying one or more media item preferences of the user, wherein user taste information represents favorite genres of the user. 
     
     
         12 . The method of  claim 10 , wherein the listener feedback includes implied feedback data including one or more observations, wherein the one or more observations include increased volume and client device orientation. 
     
     
         13 . The method of  claim 10 , wherein the determination of the second collection of media items includes selection of one or more candidate media items for playback by the client device, wherein the one or more candidate media items were not included with the first collection of media items. 
     
     
         14 . The method of  claim 10 , wherein the determination of the second collection of media items is performed using a machine learned function. 
     
     
         15 . The method of  claim 14 , further comprising:
 providing feedback data for media items played in a historical sequence as input to a machine learning system, where some of the listener feedback for the media items played in the historical sequence is negative feedback;   learning, using the machine learning system, which media items were played in the historical sequence after the negative feedback; and   outputting the machine learned function by the machine learning system.   
     
     
         16 . A system comprising:
 at least one processor; and at least one storage comprising instructions stored on the storage that when executed cause the system to:
 receive a request to play unspecified media items from a client device; 
 transmit, in response to the request, a first collection of media items for playback to the client device; 
 receive, during playback of the first collection of media items, a steering request and listener feedback from the client device, wherein the steering request indicates a request to modify criteria by which media items are selected for playback and the listener feedback includes a feedback sequence for the first collection of media items; 
 determine a second collection of media items for playback based on the steering request and the listener feedback; and 
 transmit the second collection of media items for playback to the client device. 
   
     
     
         17 . The system of  claim 16 , wherein the determination of the second collection of media items is based on user profile information associated with a user of the client device that provided the request to play unspecified media items, the user profile information identifying one or more media item preferences of the user. 
     
     
         18 . The system of  claim 16 , wherein the determination of the second collection of media items is based on user taste information associated with a user of the client device that provided the request to play unspecified media items, the user profile information identifying one or more media item preferences of the user, wherein user taste information represents favorite genres of the user. 
     
     
         19 . The system of  claim 16 , wherein the listener feedback includes implied feedback data including one or more observations, wherein the one or more observations include increased volume and client device orientation. 
     
     
         20 . The system of  claim 16 , wherein the determination of the second collection of media items includes selection of one or more candidate media items for playback by the client device, wherein the one or more candidate media items were not included with the first collection of media items. 
     
     
         21 . The system of  claim 16 , wherein the determination of the second collection of media items is performed using a machine learned function.