Automatic music mood detection
First Claim
1. A method comprising:
- extracting an intensity feature, a timbre feature, and a rhythm feature from a music clip;
classifying the music clip into a mood group based on the intensity feature; and
classifying the music clip into an exact music mood from the mood group based on the timbre feature and the rhythm feature.
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Accused Products
Abstract
A system and methods use music features extracted from music to detect a music mood within a hierarchical mood detection framework. A two-dimensional mood model divides music into four moods which include contentment, depression, exuberance, and anxious/frantic. A mood detection algorithm uses a hierarchical mood detection framework to determine which of the four moods is associated with a music clip based on the extracted features. In a first tier of the hierarchical detection process, the algorithm determines one of two mood groups to which the music clip belongs. In a second tier of the hierarchical detection process, the algorithm then determines which mood from within the selected mood group is the appropriate, exact mood for the music clip. Benefits of the mood detection system include automatic detection of music mood which can be used as music metadata to manage music through music representation and classification.
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Citations
37 Claims
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1. A method comprising:
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extracting an intensity feature, a timbre feature, and a rhythm feature from a music clip; classifying the music clip into a mood group based on the intensity feature; and classifying the music clip into an exact music mood from the mood group based on the timbre feature and the rhythm feature. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method, comprising:
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extracting features from a music clip; selecting a first mood group or a second mood group based on a first feature; and determining an exact mood from within the selected mood group based on a second feature and a third feature. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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37. A computer, comprising:
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a music clip; a mood detection algorithm configured to classify the music clip as a music mood according to music features extracted from the music clip; a music feature extraction tool configured to extract the music features; and a hierarchical music mood detection process configured to determine a mood group based on a first music feature and an exact music mood from within the mood group based on a second and third music feature.
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Specification