System for searching music based on combination of components of music and method thereof
AssigneeKeiser Corporation
InventorDuHeon Gyeon
Life of this patent
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Abstract
The present disclosure relates to a music search system based on a combination of components of music and a method thereof. The system may include: a learning unit which trains a learning model by setting a plurality of candidate music as input data and setting a level value for a main category as output data; a database which quantizes and stores an attribute for each main category for each extracted candidate music as a level value; an input unit which receives a level value for at least one main category from a user; and a searching unit which inputs the input level value for each main category to a previously trained learning model to search one or more candidate music and provide the searched candidate music to a user terminal.
Claims22
A music search system based on a combination of components of music, comprising:
- a learning unit which trains a learning model by setting a plurality of candidate music as input data and setting a level value for a main category including a tempo, a beat, an electric (EDM), a vocal, a spatial density, a time density, a brightness, and a popularity for the music, as output data;
- a database which quantizes and stores an attribute for each main category for the each extracted candidate music as the level value;
- an input unit which receives the level value for at least one main category, among the tempo, the beat, the electric (EDM), the vocal, the spatial density, the time density, the brightness, and the popularity, from a user;
- and
- a searching unit which inputs the input level value for each main category to the previously trained learning model to search one or more candidate music and provide the searched candidate music to a user terminal.
A music search method performed by a music search system, comprising:
- a step of training a learning model by setting a plurality of candidate music as input data and setting a level value for a main category including a tempo, a beat, an electric (EDM), a vocal, a spatial density, a time density, a brightness, and a popularity for the music, as output data;
- a step of quantizing and storing an attribute for each main category for the each extracted candidate music as the level value;
- a step of receiving the level value for at least one main category, among the tempo, the beat, the electric (EDM), the vocal, the spatial density, the time density, the brightness, and the popularity, from a user;
- and
- a step of searching one or more candidate music and providing the searched candidate music to a user terminal by inputting the input level value for each main category to the previously trained learning model.
Dependencies are inferred from the claim text.