System and methods for providing automatic classification of media entities according to consonance properties
First Claim
1. A method of classifying data according to consonance properties of the data, comprising:
- assigning to each media entity of a plurality of media entities in a data set to at least one consonance class;
processing each media entity of said data set to extract at least one consonance characteristic based on digital signal processing of each media entity;
generating a plurality of consonance vectors for said plurality of media entities, wherein each consonance vector includes said at least one consonance class and at least one consonance characteristic based on digital signal processing; and
forming a classification chain based upon said plurality of feature vectors.
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Abstract
In connection with a classification system for classifying media entities that merges perceptual classification techniques and digital signal processing classification techniques for improved classification of media entities, a system and methods are provided for automatically classifying and characterizing musical consonance properties of media entities. Such a system and methods may be useful for the indexing of a database or other storage collection of media entities, such as media entities that are audio files, or have portions that are audio files. The methods also help to determine media entities that have similar consonance by utilizing classification chain techniques that test distances between media entities in terms of their properties. For example, a neighborhood of songs may be determined within which each song has a similar consonance.
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Citations
13 Claims
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1. A method of classifying data according to consonance properties of the data, comprising:
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assigning to each media entity of a plurality of media entities in a data set to at least one consonance class;
processing each media entity of said data set to extract at least one consonance characteristic based on digital signal processing of each media entity;
generating a plurality of consonance vectors for said plurality of media entities, wherein each consonance vector includes said at least one consonance class and at least one consonance characteristic based on digital signal processing; and
forming a classification chain based upon said plurality of feature vectors. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer readable medium bearing computer executable instructions for:
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assigning to each media entity of a plurality of media entities in a data set to at least one. consonance class;
processing each media entity of said data set to extract at least one consonance characteristic based on digital signal processing of each media entity;
generating a plurality of consonance vectors for said plurality of media entities, wherein each consonance vector includes said at least one consonance class and at least one consonance characteristic based on digital signal processing; and
forming a classification chain based upon said plurality of feature vectors.
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8. A modulated data signal carrying computer executable instructions for:
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assigning to each media entity of a plurality of media entities in a data set to at least one consonance class;
processing each media entity of said data set to extract at least one consonance characteristic based on digital signal processing of each media entity;
generating a plurality of consonance vectors for said plurality of media entities, wherein each consonance vector includes said at least one consonance class and at least one consonance characteristic based on digital signal processing; and
forming a classification chain based upon said plurality of feature vectors.
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9. At least one computing device comprising means for:
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assigning to each media entity of a plurality of media entities in a data set to at least one consonance class;
processing each media entity of said data set to extract at least one consonance characteristic based on digital signal processing of each media entity;
generating a plurality of consonance vectors for said plurality of media entities, wherein each consonance vector includes said at least one consonance class and at least one consonance characteristic based on digital signal processing; and
forming a classification chain based upon said plurality of feature vectors.
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10. A computing system, comprising:
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a computing device including;
a classification chain data structure stored thereon having a plurality of classification vectors, wherein each vector includes data representative of a consonance class as classified by humans and consonance characteristics as determined by digital signal processing; and
processing means for comparing an unclassified media entity to the classification chain data structure to determine an estimate of the consonance class of the unclassified media entity. - View Dependent Claims (11, 12)
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13. A classification chain data structure utilized in connection with the classification of consonance of new unclassified media entities, comprising:
a plurality of classification vectors, wherein each vector includes;
consonance data as classified by humans; and
consonance data determined by digital signal processing techniques.
Specification