IPC분류정보
국가/구분 |
United States(US) Patent
등록
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국제특허분류(IPC7판) |
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출원번호 |
US-0896847
(2001-06-29)
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발명자
/ 주소 |
- Pitman,Michael C.
- Fitch,Blake G.
- Abrams,Steven
- Germain,Robert S.
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출원인 / 주소 |
- International Business Machines Corporation
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대리인 / 주소 |
Fleit, Kain, Gibbons, Gutman, Bongini &
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인용정보 |
피인용 횟수 :
13 인용 특허 :
12 |
초록
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A method is provided for monitoring audio content available over a network. According to the method, the network is searched for audio files, and audio identifying information is generated for each audio file that is found. It is determined whether the audio identifying information generated for eac
A method is provided for monitoring audio content available over a network. According to the method, the network is searched for audio files, and audio identifying information is generated for each audio file that is found. It is determined whether the audio identifying information generated for each audio file matches audio identifying information in an audio content database. In one preferred embodiment, each audio file that is found is analyzed so as to generate the audio file information, which is an audio feature signature that is based on the content of the audio file. Also provided is a system for monitoring audio content available over a network.
대표청구항
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What is claimed is: 1. A method for monitoring audio content available over a network, said method comprising the steps of: searching the network for audio files; generating audio identifying information for each audio file that is found based on detected events in audio content from each audio fil
What is claimed is: 1. A method for monitoring audio content available over a network, said method comprising the steps of: searching the network for audio files; generating audio identifying information for each audio file that is found based on detected events in audio content from each audio file; and determining whether the audio identifying information generated for each audio file matches audio identifying information in an audio content database, wherein the generating step includes, for each audio file, the sub-step of: detecting a plurality of events in the audio content from that audio file, each of the events being a crossing of the value of a first running average and the value of a second running average, wherein the first running average is an average over a first averaging period of a plurality of time dependent frequency components of the audio content from that audio file, and the second running average is an average over a second averaging period, which is different than the first averaging period, of the time dependent frequency components of the audio content that audio file. 2. The method according to claim 1, wherein the audio identifying information is an audio feature signature that is based on the detected events in the audio content of the audio file. 3. The method according to claim 2, wherein the determining step includes the sub-step of comparing the audio feature signature generated for each audio file with the audio feature signatures stored in the audio content database. 4. The method according to claim 1, further comprising the steps of: generating audio identifying information for predetermined audio content based on detected events in the predetermined audio content; and storing the audio identifying information for the predetermined audio content in the audio content database. 5. The method according to claim 1, further comprising the step of: for each audio file that is determined to match audio identifying information in the audio content database, recording information including identification of the audio content and the location at which the audio file was found. 6. The method according to claim 5, further comprising the step of: compiling at least one list from the recorded information, the list including all locations on the network where at least one piece of the audio content was found; and charging a fee for the list. 7. The method according to claim 1, wherein the generating step further includes the sub-steps of: obtaining an audio signal characterized by a time dependent power spectrum; analyzing the spectrum to obtain the time dependent frequency components; and producing the audio identifying information for audio content from the audio file based on the detected events. 8. The method according to claim 7, wherein in the sub-step of detecting a plurality of events, a plurality of extremum are detected in the plurality of time dependent frequency components. 9. The method according to claim 7, wherein the generating step further includes the sub-steps of: detecting a set of events occurring approximately simultaneously in a set of adjacent time dependent frequency components; and selecting a subset of the set of events for further processing. 10. The method according to claim 7, wherein the generating step includes the sub-step of determining a time dependent frequency component power corresponding to each event. 11. The method according to claim 7, wherein the sub-step of analyzing the spectrum includes: sampling the audio signal to obtain a plurality of audio signal samples; taking a plurality of subsets from the plurality of audio signal samples; and performing a Fourier transform on each of the plurality of subsets to obtain a set of Fourier frequency components. 12. The method according to claim 7, wherein the sub-step of detecting a plurality of events includes: keeping the first running average over the first averaging period of the plurality of time dependent frequency components so as to obtain a first series of averages for the first averaging period; keeping the second running average over the second averaging period of the plurality of time dependent frequency components so as to obtain a second series of averages for the first averaging period; and recording a plurality of event times, each of the event times being a time at which there occurs one of the detected events of the first running average crossing the second running average. 13. The method according to claim 7, wherein the generating step further includes the sub-step of collecting the plurality of events in a plurality of time groups each of which covers an interval of time. 14. The method according to claim 7, wherein the generating step further includes the sub-steps of: performing a Fourier transformation of the audio content into a time series of audio power dissipated over a first plurality of frequencies; grouping the frequencies into a smaller second plurality of bands that each include a range of neighboring frequencies; detecting power dissipation events in each of the bands; and grouping together the power dissipation events from mutually adjacent bands at a selected moment so as to form an identifying feature. 15. A computer-readable medium encoded with a program for monitoring audio content available over a network, said program containing instructions for performing the steps of: searching the network for audio files; generating audio identifying information for each audio file that is found based on detected events in audio content from each audio file; and determining whether the audio identifying information generated for each audio file matches audio identifying information in an audio content database, wherein the generating step includes, for each audio file, the sub-step of: detecting a plurality of events in the audio content from that audio file, each of the events being a crossing of the value of a first running average and the value of a second running average, wherein the first running average is an average over a first averaging period of a plurality of time dependent frequency components of the audio content from that audio file, and the second running average is an average over a second averaging period, which is different than the first averaging period, of the time dependent frequency components of the audio content that audio file. 16. A method for obtaining royalty payments for usage of copyrighted audio content, said method comprising the steps of: searching a network for audio files; generating audio identifying information for each audio file that is found based on detected events in audio content from each audio file; determining whether the audio identifying information generated for each audio file matches audio identifying information in a copyrighted audio content database; and if the audio identifying information generated for an audio file matches audio identifying information in the copyrighted audio content database, receiving payment from a site on the network where the audio file was found, wherein the generating step includes, for each audio file, the sub-step of: detecting a plurality of events in the audio content from that audio file, each of the events being a crossing of the value of a first running average and the value of a second running average, wherein the first running average is an average over a first averaging period of a plurality of time dependent frequency components of the audio content from that audio file, and the second running average is an average over a second averaging period, which is different than the first averaging period, of the time dependent frequency components of the audio content that audio file. 17. The computer-readable medium according to claim 15, wherein the audio identifying information is an audio feature signature that is based on the detected events in the audio content of the audio file. 18. The computer-readable medium according to claim 17, wherein the determining step includes the sub-step of comparing the audio feature signature generated for each audio file with the audio feature signatures stored in the audio content database. 19. The computer-readable medium according to claim 15, wherein said program further contains instructions for performing the steps of: generating audio identifying information for predetermined audio content based on detected events in the predetermined audio content; and storing the audio identifying information for the predetermined audio content in the audio content database. 20. The computer-readable medium according to claim 15, wherein the generating step further includes the sub-steps of: obtaining an audio signal characterized by a time dependent power spectrum; analyzing the spectrum to obtain the time dependent frequency components; and producing the audio identifying information for audio content from the audio file based on the detected events. 21. The computer-readable medium according to claim 20, wherein the sub-step of analyzing the spectrum includes: sampling the audio signal to obtain a plurality of audio signal samples; taking a plurality of subsets from the plurality of audio signal samples; and performing a Fourier transform on each of the plurality of subsets to obtain a set of Fourier frequency components. 22. The computer-readable medium according to claim 20, wherein the sub-step of detecting a plurality of events includes: keeping the first running average over the first averaging period of the plurality of time dependent frequency components so as to obtain a first series of averages for the first averaging period; keeping the second running average over the second averaging period of the plurality of time dependent frequency components so as to obtain a second series of averages for the first averaging period; and recording a plurality of event times, each of the event times being a time at which there occurs one of the detected events of the first running average crossing the second running average. 23. The computer-readable medium according to claim 15, wherein the generating step further includes the sub-steps of: performing a Fourier transformation of the audio content into a time series of audio power dissipated over a first plurality of frequencies; grouping the frequencies into a smaller second plurality of bands that each include a range of neighboring frequencies; detecting power dissipation events in each of the bands; and grouping together the power dissipation events from mutually adjacent bands at a selected moment so as to form an identifying feature. 24. A system for monitoring audio content available over a network, said system comprising: a spider for searching the network for audio files; an identifying information generator for generating audio identifying information for each audio file that is found based on detected events in audio content from each audio file; and a match detector for determining whether the audio identifying information generated for each audio file matches audio identifying information in an audio content database, wherein, for each audio file, the identifying information generator detects a plurality of events in the audio content from that audio file, each of the events being a crossing of the value of a first running average and the value of a second running average, the first running average being an average over a first averaging period of a plurality of time dependent frequency components of the audio content from that audio file, and the second running average being an average over a second averaging period, which is different than the first averaging period, of the time dependent frequency components of the audio content that audio file. 25. The system according to claim 24, wherein the audio identifying information is an audio feature signature that is based on the detected events in the audio content of the audio file. 26. The system according to claim 24, wherein the audio content database stores audio identifying information for predetermined audio content. 27. The system according to claim 24, further comprising: an invoicer for charging a fee to a site on the network where an audio file was found, if the audio identifying information generated for the audio file matches audio identifying information in an audio content database. 28. The system according to claim 24, further comprising: an information collector for recording information including identification of the audio content and the location at which an audio file was found, for each audio file that is determined to match audio identifying information in the audio content database; a list generator for compiling at least one list from the recorded information, the list including all locations on the network where at least one piece of the audio content was found; and an invoicer for charging a fee for the list.
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