IP Library Granted Patent US 12,242,771
Granted Patent B2
US 12,242,771 · App. 18/316,990 · Granted Mar 4, 2025

Systems and methods for composition of audio content from multi-object audio

Inventors: Yatish Jayant Naik Raikar (Bangalore, IN); Mohammed Rasool (Bangalore, IN); Trinadha Harish Babu Pallapothu (Chirala, IN)
Assignee: DISH Network Technologies India Private Limited
G06F3/165G10L25/51
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,242,771
App. No.
18/316,990
Granted
Mar 4, 2025
Kind
B2
Abstract

Embodiments are related to processing of one or more input audio feeds for generation of a target audio stream that includes at least one object of interest to a listener. In some embodiments, the target audio stream may exclusively or primarily include the sound of the object of interest to the listener, without including other persons. This allows a listener to focus on an object of his or her interest and not necessarily have to listen to the performances of other objects in the input audio feed. Some embodiments contemplate multiple audio feeds and/or with multiple objects of interest.

Claims (40)

1. A method for composition of audio content comprising:

receiving an input audio feed including one or more objects distributed in multiple frames, wherein an object of interest in the one or more objects is identifiable based on a unique characteristic;

comparing of at least a portion of the input audio feed with the unique characteristic of the object of interest to detect matched frames that include the unique characteristic of the object of interest;

creating a timeline of the input audio feed;

annotating the timeline of the input audio feed at positions corresponding to positions of the matched frames;

generating a target audio stream having the object of interest by compositing the matched frames; and

partially eliminating objects that do not correspond to the object of interest from the target audio stream by suppressing, in the target audio stream, sounds of objects that do not correspond to the object of interest.

2. The method of claim 1 , wherein the annotating allows playing of the target audio stream at the positions of the matched frames.

3. The method of claim 1 , wherein the annotating allows selective seeking the positions of the matched frames, without generation of the target audio stream.

4. The method of claim 1 , wherein a user selects the object of interest from the timeline.

5. The method of claim 1 , wherein the object of interest is included in a user interface configured to enable a user selection of a set of objects of interest comprising the object of interest.

6. The method of claim 5 , wherein the object of interest is identified, at the user interface, using an identifier comprising one or more of a name, a role, a position in an event, a family, or an organization, the identifier being selectable via the user interface.

7. The method of claim 5 , wherein the object of interest is identified, at the user interface, using an image.

8. The method of claim 1 , further comprising:

generating a reference set comprising the object of interest; and

using the reference set to train a machine learning model to identify the object of interest in input audio streams.

9. The method of claim 8 , further comprising:

applying the machine learning model to compare the at least a portion of the input audio feed with the unique characteristic of the object of interest to detect the matched frames.

10. A non-transitory computer-readable storage medium storing instructions configured for composition of audio content to perform a method comprising:

receiving an input audio feed including one or more objects distributed in multiple frames, wherein an object of interest in the one or more objects is identifiable based on a unique characteristic;

comparing at least a portion of the input audio feed with the unique characteristic of the object of interest to detect matched frames that include the unique characteristic of the object of interest;

creating a timeline of the input audio feed;

annotating the timeline of the input audio feed at positions corresponding to positions of the matched frames;

generating a target audio stream having the object of interest by compositing the matched frames; and

partially eliminating objects that do not correspond to the object of interest, from the target audio stream by suppressing, in the target audio stream, sounds of objects that do not correspond to the object of interest.

11. The computer-readable storage medium of claim 10 , wherein the annotating allows playing of the target audio stream at the positions of the matched frames.

12. The computer-readable storage medium of claim 10 , wherein the annotating allows selective seeking the positions of the matched frames, without generation of the target audio stream.

13. The computer-readable storage medium of claim 10 , wherein a user selects the object of interest from the timeline.

14. An apparatus for composition of audio content comprising:

a memory;

one or more processors electronically coupled to the memory and configured for:

receiving an input audio feed including one or more objects distributed in multiple frames, wherein an object of interest in the one or more objects is identifiable based on a unique characteristic;

comparing at least a portion of the input audio feed with the unique characteristic of the object of interest to detect matched frames that include the unique characteristic of the object of interest;

creating a timeline of the input audio feed; and

annotating the timeline of the input audio feed at positions corresponding to positions of the matched frames;

generating a target audio stream having the object of interest by compositing the matched frames; and

partially eliminating objects that do not correspond to the object of interest, from the target audio stream by suppressing, in the target audio stream, sounds of objects that do not correspond to the object of interest.

15. The apparatus of claim 14 , wherein the annotating allows playing of the target audio stream at the positions of the matched frames.

16. The apparatus of claim 14 , wherein the annotating allows selective seeking the positions of the matched frames, without generation of the target audio stream.

17. The apparatus of claim 14 , wherein a user selects the object of interest from the timeline.

Assignments (2)
CHANGE OF NAME Recorded May 15, 2023
From: SLING MEDIA PVT. LTD.
To: DISH NETWORK TECHNOLOGIES INDIA PRIVATE LIMITED
Reel/Frame 063647/0467 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 12, 2023
From: RAIKAR, YATISH JAYANT NAIK; RASOOL, MOHAMMED; PALLAPOTHU, TRINADHA HARISH BABU
To: SLING MEDIA PVT. LTD.
Reel/Frame 063631/0625 →
Continuity (4)
Continuation 17148471 · Jan 13, 2021
Continuation 16440199 · Jun 13, 2019
Continuation 15901703 · Feb 21, 2018
Related Publication 20230280972A1 · Sep 7, 2023
References Cited (111)
US 5005204A · Deaett · 1991 [cited by applicant]
US 6204840B1 · Petelycky et al. · 2001 [cited by applicant]
US 8121843B2 · Rhoads · 2012 [cited by examiner]
US 8315396B2 · Schreiner · 2012 [cited by examiner]
US 8854447B2 · Conness et al. · 2014 [cited by applicant]
US 9053711B1 · Smith et al. · 2015 [cited by applicant]
US 9251798B2 · Miao et al. · 2016 [cited by applicant]
US 9292895B2 · Rodriguez et al. · 2016 [cited by applicant]
US 9299364B1 · Pereira et al. · 2016 [cited by applicant]
US 9456273B2 · Wang et al. · 2016 [cited by applicant]
US 9626084B2 · Waggoner et al. · 2017 [cited by applicant]
US 9728188B1 · Rosen et al. · 2017 [cited by applicant]
US 9904509B1 · Raffa et al. · 2018 [cited by applicant]
US 9912373B1 · Wang · 2018 [cited by applicant]
US 9972187B1 · Srinivasan · 2018 [cited by examiner]
US 10121165B1 · Mohajer · 2018 [cited by examiner]
US 10275209B2 · Klimanis · 2019 [cited by examiner]
US 10276175B1 · Garcia · 2019 [cited by applicant]
US 10365885B1 · Naik Raikar · 2019 [cited by examiner]
US 10430154B2 · Gillespie · 2019 [cited by examiner]
US 10657174B2 · Master et al. · 2020 [cited by applicant]
US 11662972B2 · Raikar · 2023 [cited by examiner]
US 20020035723A1 · Inoue et al. · 2002 [cited by applicant]
US 20020152117A1 · Cristofalo · 2002 [cited by examiner]
US 20030122862A1 · Takaku et al. · 2003 [cited by applicant]
US 20030229514A2 · Brown · 2003 [cited by applicant]
US 20050065976A1 · Holm et al. · 2005 [cited by applicant]
US 20050166258A1 · Vasilevsky et al. · 2005 [cited by applicant]
US 20070005795A1 · Gonzalez · 2007 [cited by examiner]
US 20070087756A1 · Hoffberg · 2007 [cited by applicant]
US 20070250716A1 · Brunk et al. · 2007 [cited by applicant]
US 20080041220A1 · Foust et al. · 2008 [cited by applicant]
US 20100332003A1 · Yaguez · 2010 [cited by applicant]
US 20110013790A1 · Hilpert et al. · 2011 [cited by applicant]
US 20110082877A1 · Gupta et al. · 2011 [cited by applicant]
US 20120062729A1 · Hart · 2012 [cited by examiner]
US 20120155653A1 · Jax et al. · 2012 [cited by applicant]
US 20130007201A1 · Jeffrey et al. · 2013 [cited by applicant]
US 20130318071A1 · Cho · 2013 [cited by examiner]
US 20130345840A1 · Lempel et al. · 2013 [cited by applicant]
US 20140016787A1 · Neuendorf et al. · 2014 [cited by applicant]
US 20140032775A1 · Abiezzi et al. · 2014 [cited by applicant]
US 20140063055A1 · Osterhout · 2014 [cited by examiner]
US 20140129560A1 · Grokop · 2014 [cited by examiner]
US 20140172961A1 · Clemmer · 2014 [cited by examiner]
US 20140195028A1 · Emerson, III · 2014 [cited by applicant]
US 20140270699A1 · Casey · 2014 [cited by examiner]
US 20140277645A1 · Thirumale · 2014 [cited by examiner]
US 20140307896A1 · Park et al. · 2014 [cited by applicant]
US 20140330413A1 · Anniballi · 2014 [cited by applicant]
US 20150025664A1 · Cory · 2015 [cited by examiner]
US 20150149173A1 · Korycki · 2015 [cited by applicant]
US 20150172787A1 · Geramifard · 2015 [cited by applicant]
US 20150193199A1 · Kim · 2015 [cited by examiner]
US 20150205864A1 · Fuzell-Casey · 2015 [cited by examiner]
US 20150215496A1 · Matsuo · 2015 [cited by applicant]
US 20150220633A1 · Fuzell-Casey et al. · 2015 [cited by applicant]
US 20150234564A1 · Snibbe et al. · 2015 [cited by applicant]
US 20150269951A1 · Kalker · 2015 [cited by examiner]
US 20150331661A1 · Kalampoukas et al. · 2015 [cited by applicant]
US 20150332667A1 · Mason · 2015 [cited by examiner]
US 20160054903A1 · Jeong et al. · 2016 [cited by applicant]
US 20160071546A1 · Neymotin et al. · 2016 [cited by applicant]
US 20160098999A1 · Jacob · 2016 [cited by examiner]
US 20160103652A1 · Kuniansky · 2016 [cited by applicant]
US 20160125889A1 · Westerman · 2016 [cited by examiner]
US 20160192105A1 · Breebaart et al. · 2016 [cited by applicant]
US 20160247537A1 · Ricciardi · 2016 [cited by applicant]
US 20160261953A1 · Aggarwal et al. · 2016 [cited by applicant]
US 20160292266A1 · Mont-Reynaud et al. · 2016 [cited by applicant]
US 20170034263A1 · Archambault · 2017 [cited by examiner]
US 20170048596A1 · Fonseca, Jr. · 2017 [cited by examiner]
US 20170072321A1 · Thompson et al. · 2017 [cited by applicant]
US 20170098452A1 · Tracey · 2017 [cited by examiner]
US 20170099558A1 · Spitznagle et al. · 2017 [cited by applicant]
US 20170109128A1 · Parvizi · 2017 [cited by examiner]
US 20170125014A1 · Pogorelik et al. · 2017 [cited by applicant]
US 20170147280A1 · Lanman, III · 2017 [cited by examiner]
US 20170169827A1 · Barreira Avegliano · 2017 [cited by examiner]
US 20170169833A1 · Lecomte et al. · 2017 [cited by applicant]
US 20170185375A1 · Martel et al. · 2017 [cited by applicant]
US 20170199934A1 · Nongpiur · 2017 [cited by examiner]
US 20170220036A1 · Visser · 2017 [cited by examiner]
US 20170229121A1 · Taki et al. · 2017 [cited by applicant]
US 20170244959A1 · Ranjeet et al. · 2017 [cited by applicant]
US 20170293461A1 · McCauley et al. · 2017 [cited by applicant]
US 20170309298A1 · Scott · 2017 [cited by examiner]
US 20170329493A1 · Jia et al. · 2017 [cited by applicant]
US 20170332036A1 · Panchaksharaiah et al. · 2017 [cited by applicant]
US 20170332303A1 · Panchaksharaiah et al. · 2017 [cited by applicant]
US 20180014041A1 · Chen et al. · 2018 [cited by applicant]
US 20180060022A1 · Kozlov · 2018 [cited by applicant]
US 20180060428A1 · Lee · 2018 [cited by examiner]
US 20180095643A1 · Jia et al. · 2018 [cited by applicant]
US 20180122403A1 · Koretzky · 2018 [cited by applicant]
US 20180139268A1 · Fuzell-Casey et al. · 2018 [cited by applicant]
US 20180146446A1 · Mate · 2018 [cited by examiner]
US 20180189020A1 · Oskarsson · 2018 [cited by examiner]
US 20180261255A1 · Goshen · 2018 [cited by examiner]
US 20180322887A1 · Choo et al. · 2018 [cited by applicant]
US 20180341455A1 · Ivanov et al. · 2018 [cited by applicant]
US 20190013027A1 · Page et al. · 2019 [cited by applicant]
US 20190191188A1 · Tilaye · 2019 [cited by examiner]
US 20190258450A1 · Naik Raikar et al. · 2019 [cited by applicant]
US 20190278555A1 · Carvajal · 2019 [cited by examiner]
US 20190281389A1 · Gordon · 2019 [cited by examiner]
US 20190286409A1 · Klimanis · 2019 [cited by examiner]
US 20190294409A1 · Naik Raikar et al. · 2019 [cited by applicant]
US 20210132900A1 · Naik Raikar et al. · 2021 [cited by applicant]
US 20230280972A1 · Raikar · 2023 [cited by examiner]
Hoekstra et al., “Presentation Agents That Adapts to Users' Visual Interest and Follow Their Preferences” Proceedings of the 5th International Conference on Computer Vision System, 2007, 10 pages. [cited by applicant]