SENTIMENT MAPPING IN A MEDIA CONTENT ITEM

• US 20130243392A1
• Filed: 03/14/2012
• Published: 09/19/2013
• Est. Priority Date: 03/14/2012
• Status: Active Grant

• Current Assignee: ARRIS Enterprises LLC (CommScope Holding Company, Inc.)
• Original Assignee: General Instrument Corporation (CommScope Holding Company, Inc.)
• Inventors: Vasudevan, Venugopal, Wickramasuriya, Jehan, Xu, Chao
• Granted Patent: US 8,995,822 B2
• Time in Patent Office: Days
• US Class Current: 386/241
• CPC Class Codes: H04N 21/23418 involving operations for analysing video streams, e.g. detecting features or characteristics television picture signal circuitry for scene change detection H04N5/147; filtering for image enhancement G06T5/00; methods or arrangements for recognising scenes G06V20/00; arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59
• CPC Class Codes: H04N 21/26603 for automatically generating descriptors from content, e.g. when it is not made available by its provider, using content analysis techniques
• CPC Class Codes: H04N 21/2665 Gathering content from different sources, e.g. Internet and satellite
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 21/8456 by decomposing the content in the time domain, e.g. in time segments

Abstract

A media content item is evaluated for its “sentiment states.” That is, segments of the content item are determined to be, for example, “happy,” “exciting,” “sad,” “funny,” and the like. A “sentiment map” is created that delimits segments of the content item and contains the sentiment-state keywords associated with the segments. Some maps include an amplitude for each assigned sentiment keyword and a confidence value for the segment delimitation and for each keyword. As an exemplary use of the sentiment map, an advertisement broker matches the sentiments of his advertisement offerings with segments of a content item in order to place appropriate advertisements at times when they would be most favorably received. In another example, a recommender system recommends to a user a content item whose sentiment map compares favorably to that of a content item already enjoyed by the user.

Claims

1. A method for analyzing a media content item, the method comprising:

receiving, by a media analyzer, the media content item;

evaluating, by the media analyzer, at least a portion of the media content item;

delimiting, by the media analyzer, a segment of the media content item;

based, at least in part, on the evaluating, associating, by the media analyzer, a sentiment-state keyword with the delimited segment; and

storing, by the media analyzer, a map of the delimited segment, the map comprising the associated sentiment-state keyword and a delimitation of the segment;

wherein the delimited segment comprises an element selected from the group consisting of;

audio content and video content; and

wherein the associating is based, at least in part, on an evaluation of an element selected from the group consisting of;

audio content of the delimited segment and video content of the delimited segment.

2. The method of claim 1 wherein the media content item is selected from the group consisting of:

a movie, a television program, a radio program, a segment of video, a segment of audio, a song, a music video, a personal message, a public-service message, a service alert, an advertisement, a health-service recommendation, a web page, an e-mail message, and a telephone call.

3. The method of claim 1 wherein the media analyzer is selected from the group consisting of:

a set-top box, a personal communications device, a mobile telephone, a personal digital assistant, a personal computer, a tablet computer, a gaming console, a head-end server, a server, and a plurality of servers.

4. The method of claim 1 wherein receiving the media content item comprises receiving the content item from an element selected from the group consisting of:

a broadcast television channel, a cable television channel, a broadcast radio channel, a private radio channel, a satellite-provided channel, the Internet-provided channel, and a local content-storage device.

5. The method of claim 1 wherein evaluating, delimiting, associating, and storing are performed, at least in part, before the receiving of the media content item is complete.

6. The method of claim 1 wherein delimiting is based, at least in part, on metadata associated with the media content item.

7. The method of claim 1 wherein delimiting is based, at least in part, on the evaluating.

8. The method of claim 1 wherein the delimited segment comprises the entire media content item.

9. The method of claim 1:

wherein delimiting comprises associating a confidence value to the delimitation of the segment; and

wherein storing comprises storing the delimitation confidence value in the map of the delimited segment.

10. The method of claim 1:

wherein delimiting comprises delimiting a plurality of segments of the media content item; and

wherein at least two of the plurality of delimited segments overlap.

11. The method of claim 1 wherein the sentiment-state keyword is selected from the group consisting of:

happy, sad, funny, successful, romantic, exciting, violent, unknown.

12. The method of claim 1:

wherein associating comprises associating an amplitude value with the sentiment-state keyword associated with the segment; and

wherein storing comprises storing the amplitude value in the map of the delimited segment.

13. The method of claim 1:

wherein associating comprises associating a confidence value with the sentiment-state keyword associated with the segment; and

wherein storing comprises storing the keyword confidence value in the map of the delimited segment.

14. The method of claim 1 wherein associating comprises associating a plurality of sentiment-state keywords with the delimited segment.

15. The method of claim 1:

wherein the media content item comprises metadata associated with the delimited segment; and

wherein evaluating is based, at least in part, on evaluating at least a portion of the metadata associated with the delimited segment.

16. The method of claim 15 wherein the metadata are selected from the group consisting of:

text, an electronic program guide, closed-captioning information, a script, and staging instructions.

17. The method of claim 1 wherein evaluating is based, at least in part, on evaluating social-response information associated with the delimited segment.

18. The method of claim 1 wherein evaluating is based, at least in part, on evaluating information specific to a consumer of the media content item, the information selected from the group consisting of:

health information, demographic information, preference information, social-group information, Internet-use information, behavioral information, software-use information, purchase information, content-consumption information, contextual information, and peer-presence information.

19. The method of claim 1 further comprising:

sending, by the media analyzer, at least a portion of the map of the delimited segment to a device distinct from the media analyzer;

wherein the device is selected from the group consisting of;

an advertising broker, a recommender system, a media content producer, and a media content provider.

20. The method of claim 1 further comprising:

re-evaluating, by the media analyzer, the delimited segment of the media content item, the re-evaluating based, at least in part, on information not available to the media analyzer during the evaluating;

based, at least in part, on the re-evaluating, re-associating, by the media analyzer, a sentiment-state keyword with the delimited segment; and

storing, by the media analyzer, an updated map of the delimited segment, the map comprising the re-associated sentiment-state keyword and a delimitation of the segment.

21. A media analyzer for analyzing a media content item, the media analyzer comprising:

a network interface configured for receiving the media content item; and

a processor operatively connected to the network interface, the processor configured for;

evaluating at least a portion of the media content item;

delimiting a segment of the media content item;

based, at least in part, on the evaluating, associating a sentiment-state keyword with the delimited segment; and

storing a map of the delimited segment, the map comprising the associated sentiment-state keyword and a delimitation of the segment;

wherein the delimited segment comprises an element selected from the group consisting of;

audio content and video content; and

wherein the associating is based, at least in part, on an evaluation of an element selected from the group consisting of;

audio content of the delimited segment and video content of the delimited segment.