Parallel Visual Radio Station Selection

• US 20100031146A1
• Filed: 08/01/2008
• Published: 02/04/2010
• Est. Priority Date: 08/01/2008
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Mizrachi, Boaz, Goldberg, Itzhack, Hoory, Ron, Finkelstein, Barbara
• Granted Patent: US 8,196,046 B2
• Time in Patent Office: Days
• US Class Current: 715/716
• CPC Class Codes: H04H 60/58 of audio determination or detection of speech characteristics in general G10L25/00; speech recognition in general G10L15/00
• CPC Class Codes: H04H 60/74 using programme related information, e.g. title, composer or interpreter
• CPC Class Codes: H04N 21/25891 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 Class Codes: H04N 21/4755 for defining user preferences, e.g. favourite actors or genre retrieval personalisation and generation of user profiles for the retrieval of video data G06F16/739; user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 21/482 End-user interface for program selection broadcast systems using EPGs H04H60/72
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

A computer implemented method in a data processing system and a computer program product enable visual selection of a media signal. A set of media signals is received from a set of media providers. A subject matter and a performer of the subject matter are then identified for at least one of the set of media signals. A set of icons is then identified. Each of the set of icons corresponds to at least one of media signals. The set of icons and the set of media providers are then forwarded to a client media player.

Claims

1. A computer implemented method in a data processing system for selecting a media signal, the method comprising:

receiving a set of media signals from a set of media providers;

identifying at least one of a subject matter and a performer of the subject matter for at least one of the set of media signals;

responsive to identifying the at least one of the subject matter and the performer, identifying a set of icons, each of the set of icons corresponding to at least one of the subject matter and the performer of the at least one of the set of media signals;

responsive to identifying the set of icons, forwarding a set of displayed icons and a set of displayed media providers to a client media player, the set of displayed icons being selected from the set of icons, wherein each of the set of displayed media providers corresponds to both one of the set of displayed icons and to one of the set of media providers.

2. The computer implemented method of claim 1, further comprising:

receiving an indication of a selected icon from the client media player, the selected icon being one of the set of displayed icons; and

responsive to receiving a selection of the displayed icon, instructing the client media player to play a selected media signal of the set of media signals, the selected media signal corresponding to the selected icon.

3. The computer implemented method of claim 1, wherein the step of identifying the subject matter and the performer of the subject matter for at least one of the set of media signals comprises:

extracting a set of features from the at least one of the set of media signals;

isolating at least one characteristic from the set of features;

comparing the at least one characteristic to at least one of a statistical model of known subject matter and a statistical model of known performers; and

identifying similarities between the at least one characteristic to the statistical model of known subject matter and the statistical model of known performers to determine at least one of a probable subject matter and a probable performer, wherein the subject matter is the probable subject matter and the performer is the probable performer.

4. The computer implemented method of claim 3, further comprising:

extracting the set of features from the at least one of the set of media signals utilizing a short-time Fourier transformation; and

identifying similarities between the at least one characteristic to the at least one of the statistical model of known subject matter and the statistical model of known performers to determine the probable subject matter and the probable performer, wherein the similarities are identified using a statistical classification method selected from the group consisting of a K-nearest neighbor, a Gaussian mixture modeling, a support vector machines, a vector quantization, a hidden Markov modeling, a multivariate auto-regression modeling, and combinations thereof.

5. The computer implemented method of claim 1, wherein the set of media providers is a set of preferred media providers, the method further comprising:

identifying the set of preferred media providers; and

responsive to identifying the set of icons, forwarding only a set of preferred displayed icons and only a set of preferred displayed media providers to the client media player, the set of preferred displayed icons being selected from the set of icons, wherein each of the set of preferred displayed media providers corresponds to both one of the set of preferred displayed icons and to one of the set of preferred media providers.

6. The computer implemented method of claim 1, wherein the step of identifying the subject matter and the performer of the subject matter for at least one of the set of media signals comprises:

identifying a metadata for the at least one of the set of media signals, the metadata indicating the subject matter and the performer of the subject matter.

7. The computer implemented method of claim 1, wherein the step of identifying the subject matter and the performer of the subject matter for at least one of the set of media signals comprises:

comparing the at least one of the set of media signals with a set of exemplary media signals in a media library to determine a matching media signal;

identifying a matching subject matter and a matching performer of the matching subject matter corresponding to the matching media signal;

identifying the subject matter as being the matching subject matter and identifying the performer of the subject matter as being the matching performer.

8. The computer implemented method of claim 1, wherein the step of identifying the subject matter and the performer of the subject matter for the at least one of the set of media signals comprises:

serially identifying and updating the subject matter and the performer of the subject matter for the at least one of the set of media signals.

9. The computer implemented method of claim 1, the method further comprising:

responsive to receiving a set of media signals from a set of media providers, applying a speech recognition to convert the set of media signals to text; and

identifying at least one of a subject matter and a performer of the subject matter for at least one of the set of media signals, wherein the subject matter and the performer are identified by applying text analysis and topic detection methods to the text.

10. The computer implemented method of claim 1, the method further comprising:

identifying at least one of a subject matter and a performer of the subject matter for at least one of the set of media signals by accessing information regarding the media signal from a network informational database.

11. A computer program product comprising:

a computer readable medium having a computer usable program code for selecting a media signal, the computer program product comprising;

computer usable program code for receiving a set of media signals from a set of media providers;

computer usable program code for identifying at least one of a subject matter and a performer of the subject matter for at least one of the set of media signals;

computer usable program code, responsive to identifying the at least one of the subject matter and the performer, for identifying a set of icons, each of the set of icons corresponding to at least one of the subject matter and the performer of the at least one of the set of media signals;

computer usable program code, responsive to identifying the set of icons, for forwarding a set of displayed icons and a set of displayed media providers to a client media player, the set of displayed icons being selected from the set of icons, wherein each of the set of displayed media providers corresponds to both one of the set of displayed icons and to one of the set of media providers.

12. The computer program product of claim 11, further comprising:

computer usable program code for receiving an indication of a selected icon from the client media player, the selected icon being one of the set of displayed icons; and

computer usable program code, responsive to receiving a selection of the displayed icon, for instructing the client media player to play a selected media signal of the set of media signals, the selected media signal corresponding to the selected icon.

13. The computer program product of claim 11, wherein the computer usable program code for identifying the subject matter and the performer of the subject matter for at least one of the set of media signals comprises:

computer usable program code for extracting a set of features from at least one of the set of media signals;

computer usable program code for isolating at least one characteristic from the set of features;

computer usable program code for comparing the at least one characteristic to at least one of a statistical model of known subject matter and a statistical model of known performers; and

computer usable program code for identifying similarities between the at least one characteristic to the statistical model of known subject matter and the statistical model of known performers to determine at least one of a probable subject matter and a probable performer, wherein the subject matter is the probable subject matter and the performer is the probable performer.

14. The computer program product of claim 13, further comprising:

computer usable program code for extracting the set of features from the at least one of the set of media signals utilizing a short-time Fourier transformation; and

computer usable program code for identifying similarities between the at least one characteristic to the at least one of the statistical model of known subject matter and the statistical model of known performers to determine the probable subject matter and the probable performer, wherein the similarities are identified using a statistical classification method selected from the group consisting of a K-nearest neighbor, a Gaussian mixture modeling, a support vector machines, a vector quantization, a hidden Markov modeling, a multivariate auto-regression modeling, and combinations thereof.

15. The computer program product of claim 11, wherein the computer usable program code for identifying the subject matter and the performer of the subject matter for at least one of the set of media signals comprises:

computer usable program code for identifying a metadata for the at least one of the set of media signals, the metadata indicating the subject matter and the performer of the subject matter.

16. The computer program product of claim 11, wherein the computer usable program code for identifying the subject matter and the performer of the subject matter for at least one of the set of media signals comprises:

computer usable program code for comparing the at least one of the set of media signals with a set of exemplary media signals in a media library to determine a matching media signal;

computer usable program code for identifying a matching subject matter and a matching performer of the matching subject matter corresponding to the matching media signal; and

computer usable program code for identifying the subject matter as being the matching subject matter and identifying the performer of the subject matter as being the matching performer.

17. The computer program product of claim 11, wherein the computer usable program code for identifying the subject matter and the performer of the subject matter for the at least one of the set of media signals comprises:

computer usable program code for serially identifying and updating the subject matter and the performer of the subject matter for the at least one of the set of media signals.

18. The computer program product of claim 11 further comprising:

computer usable program code, responsive to receiving a set of media signals from a set of media providers, for applying a speech recognition to convert the set of media signals to text; and

computer usable program code for identifying at least one of a subject matter and a performer of the subject matter for at least one of the set of media signals, wherein the subject matter and the performer are identified by applying text analysis and topic detection methods to the text.

19. The computer program product of claim 11 further comprising:

computer usable program code for identifying at least one of a subject matter and a performer of the subject matter for at least one of the set of media signals by accessing information regarding the media signal from a network informational database.

20. A data processing system for selecting a media signal, the data processing system comprising:

a bus;

a storage device connected to the bus, wherein the storage device contains a computer usable code; and

a processing unit connected to the bus, wherein the processing unit executes the computer usable program code to receive a set of media signals from a set of media providers, to identify at least one of a subject matter and a performer of the subject matter for at least one of a set of media signals, responsive to identifying the at least one of the subject matter and the performer, to identify a set of icons, each of the set of icons corresponding to at least one of the at least one of the subject matter and the performer of the at least one of the set of media signals, and responsive to identifying the set of icons, to forward a set of displayed icons and a set of displayed media providers to a client media player, the set of displayed icons being selected from the set of icons, wherein each of the set of displayed media providers corresponds to both one of the set of displayed icons and to one of the set of media providers.

21. The data processing system of claim 20, wherein the processing unit further executes the computer usable program code:

to receive an indication of a selected icon from the client media player, the selected icon being one of the set of displayed icons, and responsive to receiving a selection of the displayed icon, to instruct the client media player to play a selected media signal of the set of media signals, the selected media signal corresponding to the selected icon.

22. The data processing system of claim 20, wherein the processing unit executing the computer usable program code to identify the subject matter and the performer of the subject matter for at least one of the set of media signals further comprises the processing unit executing the computer usable program code:

to extract a set of features from the at least one of the set of media signals, to isolate the at least one characteristic from the set of features, to compare the at least one characteristic to at least one of a statistical model of known subject matter and a statistical model of known performers, and to identify similarities between the at least one characteristic to the statistical model of known subject matter and the statistical model of known performers to determine at least one of a probable subject matter and a probable performer, wherein the subject matter is the probable subject matter and the performer is the probable performer.

23. The data processing system of claim 20, wherein the processing unit further executes the computer usable program code:

to extract the set of features from the at least one of the set of media signals utilizing a short-time Fourier transformation, and to identify similarities between the at least one characteristic to the at least one of the statistical model of known subject matter and the statistical model of known performers to determine the probable subject matter and the probable performer, wherein the similarities are identified using a statistical classification method selected from the group consisting of a K-nearest neighbor, a Gaussian mixture modeling, a support vector machines, a vector quantization, a hidden Markov modeling, a multivariate auto-regression modeling, and combinations thereof.

24. A computer implemented method in a data processing system for selecting a media signal, the method comprising:

receiving a set of displayed icons and a set of displayed media providers;

responsive to receiving the set of displayed icons and the set of displayed media providers, displaying the set of icons and the set of displayed media providers;

receiving an indication of a selected icon, the selected icon being one of the set of displayed icons;

receiving an instruction to play a selected media signal, the selected media signal corresponding to the selected icon; and

playing the selected media signal.

25. The computer implemented method of claim 24, wherein the step of receiving an instruction to play the selected media signal comprises one of:

receiving an instruction to receive the selected media signal directly from a selected media provider;

or

receiving an instruction to receive the selected media signal from a visual media service provider.