Real time popularity based audible content acquisition
A personalized news service provides personalized news programs for its users by generating personalized combinations of audible versions of news stories derived from text-based versions of the news stories. The audible versions may be generated from the text-based version by a text-to-speech system, or may by recording a person reading aloud the text-based version. To acquire recordings, the personalized news service can make a determination that a particular news story has a threshold extent of popularity. The news service can then transmit a request to a remote recording station for a recording of a verbal reading of the particular news story. The news service can then receive the requested recording from the remote recording station.
1. A computer-implemented method comprising:
generating a plurality of playlists for a plurality of users, wherein each of the playlists includes references to one or more media items selected from a plurality of media items, and wherein generating the plurality of playlists comprises determining rankings for each of the plurality of media items;
based on the rankings, determining that a particular media item of the plurality of media items has at least a threshold extent of popularity;
transmitting, to a remote recording station, a request for a human verbal reading of the particular media item;
receiving, from the remote recording station, an audio file of the human verbal reading; and
storing, for future inclusion in a generated playlist, the audio file of the human verbal reading;
determining that references to the particular media item have been included in one or more further playlists;
updating the references to the particular media item in the one or more further playlists to refer to the audio file of the human verbal reading; and
transmitting, to a client device, a particular playlist of the one or more further playlists, wherein the particular playlist includes a reference to the audio file of the human verbal reading, and wherein the client device is configured to: traverse the particular playlist, retrieve the audio file of the human verbal reading during traversal of the particular playlist, and Play out the audio file of the human verbal reading.
2. The computer-implemented method of claim 1 , wherein determining that the particular media item has at least the threshold extent of popularity comprises determining an extent of correspondence between attributes associated with the particular media item and attributes associated with users.
3. The computer-implemented method of claim 1 , wherein the client device begins playing out the audio file of the human verbal reading before retrieval thereof completes.
4. The computer-implemented method of claim 1 , wherein the particular media item, prior to updating, is an initial audio file generated by a computerized text-to-speech system.
5. The computer-implemented method of claim 4 , wherein transmitting the request for the human verbal reading is based on the initial audio file having been automatically generated by the computerized text-to-speech system.
6. The computer-implemented method of claim 1 , wherein the particular media item, prior to updating, is a text file.
7. The computer-implemented method of claim 1 , wherein the particular media item comprises a news story, and wherein the remote recording station comprises a remote news studio.
8. The computer-implemented method of claim 1 , further comprising:
selecting the remote recording station from a plurality of remote recording stations based on a correspondence between a feature of the remote recording station and an attribute associated with the particular media item.
9. The computer-implemented method of claim 1 , further comprising:
selecting the remote recording station from a plurality of remote recording stations based on a correspondence between a geographic location of the remote recording station and an attribute associated with the particular media item.
10. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause performance of operations comprising:
generating a plurality of playlists for a plurality of users, wherein each of the playlists includes references to one or more media items selected from a plurality of media items, and wherein generating the plurality of playlists comprises determining rankings for each of the plurality of media items;
based on the rankings, determining that a particular media item of the plurality of media items has at least a threshold extent of popularity;
transmitting, to a remote recording station, a request for a human verbal reading of the particular media item;
receiving, from the remote recording station, an audio file of the human verbal reading; and
storing, for future inclusion in a generated playlist, the audio file of the human verbal reading;
determining that references to the particular media item have been included in one or more further playlists;
updating the references to the particular media item in the one or more further playlists to refer to the audio file of the human verbal reading; and
transmitting, to a client device, a particular playlist of the one or more further playlists, wherein the particular playlist includes a reference to the audio file of the human verbal reading, and wherein the client device is configured to: traverse the particular playlist, retrieve the audio file of the human verbal reading during traversal of the particular playlist, and Play out the audio file of the human verbal reading.
11. The non-transitory computer-readable medium of claim 10 , wherein determining that the particular media item has at least the threshold extent of popularity comprises determining an extent of correspondence between attributes associated with the particular media item and attributes associated with users.
12. The non-transitory computer-readable medium of claim 10 , wherein the particular media item, prior to updating, is an initial audio file generated by a computerized text-to-speech system.
13. The non-transitory computer-readable medium of claim 12 , wherein transmitting the request for the human verbal reading is based on the initial audio file having been automatically generated by the computerized text-to-speech system.
14. The non-transitory computer-readable medium of claim 10 , wherein the particular media item, prior to updating, is a text file.
15. The non-transitory computer-readable medium of claim 10 , wherein the client device begins playing out the audio file of the human verbal reading before retrieval thereof completes.
16. A computing system comprising:
a processor;
a memory; and
program instructions, stored in the memory, that when executed by the processor, cause the computing system to perform operations comprising:
generating a plurality of playlists for a plurality of users, wherein each of the playlists includes references to one or more media items selected from a plurality of media items, and wherein generating the plurality of playlists comprises determining rankings for each of the plurality of media items;
based on the rankings, determining that a particular media item of the plurality of media items has at least a threshold extent of popularity;
transmitting, to a remote recording station, a request for a human verbal reading of the particular media item;
receiving, from the remote recording station, an audio file of the human verbal reading; and
storing, for future inclusion in a generated playlist, the audio file of the human verbal reading;
determining that references to the particular media item have been included in one or more further playlists;
updating the references to the particular media item in the one or more further playlists to refer to the audio file of the human verbal reading; and
transmitting, to a client device, a particular playlist of the one or more further playlists, wherein the particular playlist includes a reference to the audio file of the human verbal reading, and wherein the client device is configured to: traverse the particular playlist, retrieve the audio file of the human verbal reading during traversal of the particular playlist, and play out the audio file of the human verbal reading.
17. The computing system of claim 16 , wherein determining that the particular media item has at least the threshold extent of popularity comprises determining an extent of correspondence between attributes associated with the particular media item and attributes associated with users.
18. The computing system of claim 16 , wherein the client device begins playing out the audio file of the human verbal reading before retrieval thereof completes.