Real Time Popularity Based Audible Content Acquisition

Patent metadata

Field	Value
Publication number	US-2023043879-A1
Application number	US-202217969509-A
Country	US
Kind code	A1
Filing date	Oct 19, 2022
Priority date	Mar 4, 2014
Publication date	Feb 9, 2023
Grant date	—

Abstract

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.

First claim

What is claimed is:

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.

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 , further comprising:
determining that references to the particular media item have been included 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.

4 . The computer-implemented method of claim 3 , 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.

5 . The computer-implemented method of claim 3 , wherein the client device begins playing out the audio file of the human verbal reading before retrieval thereof completes.

6 . The computer-implemented method of claim 3 , wherein the particular media item, prior to updating, is an initial audio file generated by a computerized text-to-speech system.

7 . The computer-implemented method of claim 6 , 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.

8 . The computer-implemented method of claim 3 , wherein the particular media item, prior to updating, is a text file.

9 . 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.

10 . 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.

11 . 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.

12 . 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.

13 . The non-transitory computer-readable medium of claim 12 , 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.

14 . The non-transitory computer-readable medium of claim 12 , further comprising:
determining that references to the particular media item have been included 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.

15 . The non-transitory computer-readable medium of claim 14 , wherein the particular media item, prior to updating, is an initial audio file generated by a computerized text-to-speech system.

16 . The non-transitory computer-readable medium of claim 15 , 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.

17 . The non-transitory computer-readable medium of claim 14 , wherein the particular media item, prior to updating, is a text file.

18 . 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.

19 . The computing system of claim 18 , 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.

20 . The computing system of claim 18 , the operations further comprising:
determining that references to the particular media item have been included 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.

Assignees

• Gracenote Digital Ventures Llc

Inventors

• Panguluri Venkatarama Anilkumar
• Yarram Venkata Sunil Kumar
• Kumar Lalit
• Defouw Gregory P

Classifications

• H04N21/26258

  for generating a list of items to be played back in a given order, e.g. playlist, or scheduling item distribution according to such list (retrieval of multimedia data based on playlists G06F16/40) · CPC title

• G10L13/00 Primary

  Speech synthesis; Text to speech systems · CPC title

• G06F16/639

  using playlists · CPC title

• H04N21/233

  Processing of audio elementary streams {(monitoring, identification or recognition of audio in broadcast systems H04H60/58)} · CPC title

• H04N21/25891

  being end-user preferences (retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18) · CPC title