KR20190073045A - Apparatus for recommending music, method thereof and computer recordable medium storing program to perform the method - Google Patents

Abstract

The present invention relates to an apparatus for recommending music, a method thereof, and a computer-readable record medium recorded with a program performing the method. Provided in the present invention are an apparatus for recommending music comprising: a storage module to store a music preference profile; a communications module communicating with a user device to receive user data from the user device; a sensitivity derivation unit deriving from the user data music sensitivity which is sensitivity expressed by the music being played at the user device; a circumstance derivation unit deriving a user circumstance which is a circumstance experienced by a user at a point when the music is being listened; an emotion derivation unit deriving a user emotion which is an emotion felt by the user from the user data at a point when the music is being listened; and a profile generation unit generating the music preference profile by inter-mapping the music sensitivity, user circumstance, and user emotion in a three-dimensional graph. The present invention also provides a method of for recommending music, and a computer-readable record medium recorded with a program to perform the method.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a device for recommending music, a method therefor, and a computer-readable storage medium storing a program for performing the method.

The present invention relates to music recommendation technology, and more particularly, to a device for recommending music in consideration of music emotion, user emotion, and user situation, a method therefor, and a computer readable recording medium storing a program Media.

As a representative example, the popularity of smart-end portable devices such as Smart Phones has made it easier for users to access a large number of digital media, thereby increasing the need for effective information retrieval and recommendation methods. In particular, there is a growing demand for a method for recommending music suitable for a user in recommending music.

Korea Publication No. 2014-0111152 Published on September 18, 2014 (Name: Music recommendation system and method)

An object of the present invention is to provide an apparatus for recommending music in consideration of user's emotions and user's situation, a method therefor, and a computer-readable recording medium on which a program for performing the method is recorded.

According to another aspect of the present invention, there is provided an apparatus for recommending music comprising a storage module for storing a music preference profile, a communication module for communicating with the user device and receiving user data from the user device, And a user interface unit for inputting a user's preference to the user apparatus based on the user's preference. The user's preference information may include a user's preference, An emotion derivation unit for deriving emotional user emotions felt by the user at the time of listening to the music from the user data, and a music preference profile mapping unit for mapping the music emotion, the user situation, And a profile generating unit.

And a controller for receiving user data at the time of requesting a music recommendation from the user apparatus through the communication module and transmitting the music recommendation message to a user who is in a situation that the user is experiencing at the time of requesting the music recommendation through the situation deriving unit, Deriving a feeling of a user who is feeling at the time of requesting the music recommendation through the emotion derivation unit and deriving musical emotion corresponding to the derived user situation and user emotion on the three dimensional graph of the preferred music profile And a music recommendation unit that selects at least one music having similarity and similarity within a predetermined range as the recommended music.

Wherein the user data includes music emotion data including at least one of articulation, composition, and tempo of the music, and the emotion derivation unit includes an emotion generating unit for generating emotion based on excitation (Arousal) expressing emotion intensity from the music emotion data, The degree of the emotion is determined as a normalized value, and the sensibility of the music is determined according to the respective values of the excitement and the significance.

Wherein the user data includes user environment data including at least one of location information of the user device, inertia information of the user device, weather information of the location of the user device, and time information, And derives the user status based on the user status.

Wherein the user data includes user emotion data including at least one of user's bio-signal information and user's device operation information, and the emotion derivation unit derives the user emotion based on the user emotion data.

According to another aspect of the present invention, there is provided a method of recommending music in a recommendation server, the method comprising: receiving user data from a user device; The method comprising the steps of: deriving musical emotions as emotions to be expressed; deriving a user situation as a user is experiencing at the time of listening to the music; And generating the music preference profile by mapping the music emotion, the user situation, and the user emotion to a three-dimensional graph.

The method of recommending music may further include receiving a music recommendation request from the user device, receiving user data at the time of requesting the music recommendation, A step of deriving an emotional user emotion felt by the user at the time of requesting the music recommendation and a user situation which is a situation that the user is experiencing at the time of the music recommendation; Selecting at least one piece of music having similarity to the derived music sensibility within a predetermined range as recommended music, and transmitting the selected recommended music to the user device.

According to another aspect of the present invention, there is provided a computer-readable recording medium having recorded thereon a program for performing a method for recommending music according to a preferred embodiment of the present invention .

According to the present invention as described above, it is possible to recommend music having a music sensibility suitable for a situation experienced by a user and an emotion felt by a user. Accordingly, a new user experience (UX: User experience) can be provided to the user.

1 is a diagram for explaining a system for recommending music according to an embodiment of the present invention.
FIG. 2 is a diagram for explaining a method of constructing a preferred music profile according to an embodiment of the present invention.
3 is a diagram for explaining a method for deriving a recommended music from a preferred music profile according to an embodiment of the present invention.
4 is a block diagram for explaining a configuration of an evaluation server for recommending music according to an embodiment of the present invention.
5 is a block diagram illustrating a configuration of a user apparatus for recommending music according to an embodiment of the present invention.
6 is a flowchart illustrating a method of generating a preferred music profile according to an exemplary embodiment of the present invention.
7 is a flowchart illustrating a method for recommending music according to an embodiment of the present invention.

Prior to the detailed description of the present invention, the terms or words used in the present specification and claims should not be construed as limited to ordinary or preliminary meaning, and the inventor may designate his own invention in the best way It should be construed in accordance with the technical idea of the present invention based on the principle that it can be appropriately defined as a concept of a term to describe it. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and are not intended to represent all of the technical ideas of the present invention. Therefore, various equivalents It should be understood that water and variations may be present.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Note that, in the drawings, the same components are denoted by the same reference symbols as possible. Further, the detailed description of known functions and configurations that may obscure the gist of the present invention will be omitted. For the same reason, some of the elements in the accompanying drawings are exaggerated, omitted, or schematically shown, and the size of each element does not entirely reflect the actual size.

First, a system for recommending music according to an embodiment of the present invention will be described. 1 is a diagram for explaining a system for recommending music according to an embodiment of the present invention. FIG. 2 is a diagram for explaining a method of constructing a preferred music profile according to an embodiment of the present invention. 3 is a diagram for explaining a method for deriving a recommended music from a preferred music profile according to an embodiment of the present invention.

Referring to FIG. 1, a music recommendation system according to an embodiment of the present invention includes a recommendation server 100 and a user device 200. The recommendation server 100 provides a service for recommending music to the user of the user device 200. [ In order to provide such a service, the recommendation server 100 includes functions of a web server, an application server, and a database server. The recommendation server 100 may be realized by physically combining the above functions with one apparatus or two or more apparatuses.

The user device 200 is a device used by a user. The user device 200 is recommended by the recommendation server 100 according to a user's request, and plays the recommended music. The user device 200 may be a hand-held device or a wearable device. Typically, a hand-held device may illustrate a smartphone. A wearable device can exemplarily represent a SmartWatch. The user device 200 may provide the recommendation server 100 with user data in order to receive the music recommendation. To this end, one user may use one or more user devices 200. For example, a single user may use only one smartphone, or one user may use both a smartphone and a smart watch.

Referring to FIG. 2, as a preparation process for recommending music, the recommendation server 100 generates a music preference profile that profiles a user's favorite music from a user's experience. For example, the user may prefer to exercise and to listen to cheerful music when there is sad feelings. Alternatively, when the user is in commute, he or she may prefer to listen to calm music in situations with depressed feelings. Therefore, the recommendation server 100 generates a music preference profile by mapping the user's situation, the user's emotion, and the musical sensibility to each other. Here, music sensibility means emotion expressed by music. User emotion means emotion that the user feels. Also, the user situation indicates a situation that the user is experiencing.

In order to create a music preference profile, the recommendation server 100 receives a plurality of pieces of user data collected by the user device 200 every time the user listens to music through the user device 200, Emotion, user situation and user emotion. Herein, the user data means each kind of data that can be collected from the user device 200 of the user. The user data includes music preference data such as a music reproduction time relative to the original music runtime for deriving the preference of the music, music preference data such as music reproduction or stop operation record, music emotion data such as articulation, composition and tempo of music for deriving music emotion, User condition data such as position information, inertial sensor information, weather information, and time information for deriving user's emotions, bio-signal information obtained by measuring the user's heart rate, sweat discharge level, etc., And user operation data such as device operation information generated as the user operates the operation unit. Therefore, as shown in FIG. 2, the recommendation server 100 creates a favorite music profile by mapping the music emotion derived from the user data, the user's situation, and the user's emotions to a three-dimensional graph.

Referring to FIG. 3, if there is a music recommendation request from the user device 100 in a state in which the preferred music profile is generated, the recommendation server 100 receives the user data collected by the user device 200, The situation and the user's feelings are derived. Then, the recommendation server 100 maps the derived user situation and user's emotions on the three-dimensional graph of the preferred music profile to generate music emotion corresponding to the derived user situation and user emotion on the three-dimensional graph of the preferred music profile And derives the recommended music m, a, b, c, d, e having the similarity and similarity within the predetermined range (M). Accordingly, the recommendation server 100 can provide the derived recommended music m, a, b, c, d, and e to the user device 200. [

Hereinafter, the configuration of the recommendation server 100 for recommending music according to the embodiment of the present invention will be described in more detail. 4 is a block diagram for explaining a configuration of an evaluation server for recommending music according to an embodiment of the present invention. Referring to FIG. 4, a recommendation server 100 for recommending music according to an embodiment of the present invention includes a communication module 110, a storage module 120, and a control module 130.

The communication module 110 is for communicating with the user device 200 via the network. The communication module 110 receives user data from the user device 200 under the control of the control module 130 or provides the recommended music to the user device 200. The communication module 110 may include a modem for modulating a signal transmitted to transmit / receive data through a network, and for demodulating the received signal. The communication module 110 may transmit data received from the control module 130, for example, recommended music, to the user device 200 through the network. In addition, the communication module 110 may transmit the received data, for example, user data to the control module 130.

The storage module 120 stores programs and data necessary for the operation of the recommendation server 100. For example, the storage module 120 may store music emotion, an application for deriving user conditions and user emotions, an application for generating a user preference profile, and the like. In addition, the storage module 120 may store a music file to be provided to the user, a generated user preference profile, and the like. Each kind of data stored in the storage module 120 can be registered, deleted, changed or added according to the operation of the user.

The control module 130 may control the overall operation of the recommendation server 100 and the signal flow between the internal blocks of the recommendation server 100 and may perform a data processing function for processing the data. The control module 130 may be a central processing unit (CPU), a digital signal processor (DSP), or the like.

The control module 130 includes a emotion derivation unit 131, a situation derivation unit 133, a feeling derivation unit 135, a profile generation unit 137, and a music recommendation unit 139. The emotion derivation unit 131 can derive musical emotion based on the user data received through the communication module 110. [ The situation derivation unit 133 can derive the user situation based on the user data received through the communication module 110. [ The emotion derivation unit 135 can derive the user emotion based on the user data received through the communication module 110. [ The profile generation unit 137 determines whether the music is the user's favorite music based on the user data received through the communication module 110. If the music is the user's favorite music, the profile generation unit 137 generates the emotion derivation unit 131, 133 and the emotion derivation unit 135 on the three-dimensional graph to constitute a preferred music profile. The music recommendation unit 139 derives the user's situation through the situation derivation unit 133 at the time of the user's music recommendation request through the communication module 110 and outputs the user's emotion through the emotion derivation unit 135 (M, a, b, c, d, e) in a predetermined range (M) on a three-dimensional graph of the preferred music profile by mapping the derived user conditions and user emotions on a three- . Then, the music recommendation unit 139 transmits the derived recommended music (at least one of m, a, b, c, d, and e) to the user device 200 through the communication module 110. The operation of this control module 130 will be described in more detail below.

The configuration of the user device 200 for psychological evaluation according to an embodiment of the present invention will now be described in more detail. 5 is a block diagram illustrating a configuration of a user apparatus for recommending music according to an embodiment of the present invention. 5, a user apparatus 200 according to an exemplary embodiment of the present invention includes a communication unit 210, a camera unit 220, a position information unit 230, a sensor unit 240, an audio unit 250, 260, a display unit 270, a storage unit 280, and a control unit 290.

The communication unit 210 is a means for communication between the user devices 200 or communication with the recommendation server 100. [ The communication unit 210 can communicate with other user devices 200 using a communication method such as NFC (Near Field Communication), Bluetooth, ZigBee, or IrDA (Infrared Data Association). The communication unit 210 can communicate with the recommendation server 100 via the network. The communication unit 210 may include an RF (Radio Frequency) transmitter (Tx) for up-converting and amplifying the frequency of a transmitted signal, and an RF receiver (Rx) for low-noise amplifying the received signal and down-converting the frequency. The communication unit 210 may include a modem for modulating the transmitted signal and demodulating the received signal. The communication unit 210 receives data transmitted from the control unit 290, for example, user data, and transmits the received data to the recommendation server 100 through the network. In addition, the communication unit 210 delivers the received message, for example, the recommended music to the control unit 290.

The camera unit 220 is for capturing an image, and includes at least an image sensor. The image sensor receives light reflected from a subject and converts the light into an electrical signal. The image sensor can be implemented based on a CCD (Charge Coupled Device) or a CMOS (Complementary Metal-Oxide Semiconductor). The camera unit 220 may further include an analog-to-digital converter, and may convert the analog signal output from the image sensor to a digital signal and output the digital signal to the controller 290.

The location information unit 230 is for receiving GPS signals. For example, the location information unit 230 continuously receives a GPS signal from a GPS satellite or the like, and derives location information from the received GPS signal. The derived location information is transmitted to the control module 290. Such location information may be coordinates such as latitude, longitude, and altitude.

The sensor unit 240 collects a plurality of different user data through a plurality of different sensors. Such a sensor can be implemented by MEMS (Micro Electro-Mechanical Systems). The sensor unit 240 may include at least one inertial sensor such as an accelerometer, a gyroscope, or the like. The sensor unit 240 can sense inertial information such as acceleration and displacement as well as the moving speed of the user device 200 through the inertial sensor. In addition, the sensor unit 240 includes at least one living body signal sensor for collecting the user's living body signal. For example, the sensor unit 240 may include a heart rate sensor for measuring a heart rate of a user through a blood flow rate observed in a blood vessel of a user's wrist (wrist) portion, a region where the user device 200 is worn in case of a wearable device, And a sweat sensor for measuring sweat or the like sensed by a user's hand holding the user device 200 when the handheld device is a handheld device. The sensor unit 240 provides the control unit 290 with user data including sensed inertial information or biological signal information.

The audio unit 250 includes a microphone MIC and a speaker SPK. The audio unit 250 receives the voice of the user through the microphone (MIC) and provides the input voice to the control unit 290. Also, the audio unit 250 outputs the music provided from the control unit 290 through the speaker SPK.

The input unit 260 receives user's key operation for controlling the user device 200, generates an input signal, and transmits the input signal to the control unit 290. The input unit 260 may include various kinds of keys for controlling the user device 200. In the case where the display unit 270 is a touch screen, the functions of the various keys can be performed on the display unit 270. In the case where all functions can be performed only by the touch screen, the input unit 260 is omitted It is possible.

The display unit 270 visually provides a menu of the user device 200, input data, function setting information, and various other information to the user. The display unit 270 displays a screen such as a boot screen, a standby screen, a menu screen, and the like of the user device 200. The display unit 270 may be formed of a liquid crystal display (LCD), an organic light emitting diode (OLED), an active matrix organic light emitting diode (AMOLED), or the like. Meanwhile, the display unit 270 may be implemented as a touch screen. In this case, the display unit 270 includes a touch sensor. The touch sensor senses the user's touch input. The touch sensor may be constituted by a touch sensing sensor such as a capacitive overlay, a pressure type, a resistive overlay, or an infrared beam, or may be constituted by a pressure sensor . In addition to the above sensors, all kinds of sensor devices capable of sensing contact or pressure of an object can be used as the touch sensor of the present invention. The touch sensor senses the touch input of the user, generates a sensing signal, and transmits the sensing signal to the controller 290. Particularly, when the display unit 270 is a touch screen, some or all of the functions of the input unit 260 may be performed through the display unit 270.

The storage unit 280 stores programs and data necessary for the operation of the user apparatus 200. In particular, the storage unit 280 may store music files, applications for playing music, and the like. Each kind of data stored in the storage unit 280 can be deleted, changed, or added according to a user's operation.

The controller 290 may control the overall operation of the user device 200 and the signal flow between the internal blocks of the user device 200 and may perform a data processing function for processing the data. The control unit 290 basically controls various functions of the user device 200. The control unit 290 may be a central processing unit (CPU), a digital signal processor (DSP), or the like. The control unit 290 collects user data through at least one of the position information unit 230, the sensor unit 240, the audio unit 250, the input unit 260, and the display unit 270, To the recommendation server 100. The recommendation server 100 transmits the collected user data to the recommendation server 100. [ Then, the recommendation server 100 will generate a preferred music profile. The control unit 290 collects user data through at least one of the position information unit 230, the sensor unit 240, the audio unit 250, the input unit 260, and the display unit 270, And transmits the user data collected through the communication unit 210 to the recommendation server 100. Then, the recommendation server 100 will derive the recommended music through the preferred music profile. The control unit 290 receives the recommended music derived from the recommendation server 100 through the communication unit 210 and can reproduce the received music. The operation of this controller 290 will be described in more detail below.

Next, a method for recommending music according to an embodiment of the present invention will be described. According to an embodiment of the present invention, a preferred music profile is created to recommend music. First, a method of generating a preferred music profile will be described. 6 is a flowchart illustrating a method of generating a preferred music profile according to an exemplary embodiment of the present invention.

The control unit 290 of the user device 200 assumes that music is being reproduced in step S110. At this time, the controller 290 collects user data through at least one of the position information unit 230, the sensor unit 240, the audio unit 250, the input unit 260 and the display unit 270 in step S120, The recommendation server 100 transmits the user data collected through the communication unit 210 to the recommendation server 100.

Here, the user data may include music preference data such as a music reproduction time relative to the original music runtime for deriving a preference of the music, music data such as musical composition data such as musical composition, composition and tempo for deriving musical emotion, User's situation data such as position information, inertial sensor information, weather information, time information for deriving a user situation, bio-signal information obtained by measuring the user's heart rate and sweat discharge level for deriving user's feeling, 200, and the like, such as device operation information.

When the recommendation server 100 receives user data through the communication module 110, the recommendation server 100 performs a procedure of generating a preferred music profile. First, in step S140, the profile generating unit 137 determines the preference of the music from the preference data such as the music reproduction time, the music reproduction or the stop operation record relative to the original music runtime to determine whether or not the music is preferred. In the case of stopping the reproduction of the music and ending the execution of the music reproduction application, it is determined that there is no preference of the music, and the process is terminated without generating a preferred music profile using the music. If the user has listened to the music for a predetermined time or more with respect to the original music runtime, it is determined that there is a preference of the music, and the procedure for generating the preferred music profile using the music continues.

If it is determined that the music is preferred, the emotion derivation unit 131 derives music emotion, which is emotion expressed by the music reproduced in the user device 200, from the music emotion data in the user data in step S150. Here, the music emotion data includes at least one of a plurality of parameters derived from a characteristic of a time-domain signal of music and a characteristic of a frequency-domain signal. Such a plurality of parameters may exemplify tone color, articulation, composition, tempo, and the like. At this time, the emotional derivation unit 131 derives the arousal expressing the emotion intensity from the music emotion data and the significance indicating the degree of affirmation and negation as normalized values. For example, the degree of excitement can be determined according to the tempo. That is, the higher the tempo, the higher the excitability is, so that the value can be derived.

Further, for example, a tone color is derived according to the characteristics of the frequency domain of the music, and the tone color can be normalized and quantified from the affirmation degree of affirmation to the degree of negative according to the frequency magnitude. Accordingly, the value of the valence can be derived from the tone color derived from the characteristics of the frequency domain of the music. Then, the emotion derivation unit 131 determines the music emotion according to the respective values of the excitement degree and the significance. Each of the music emotions according to embodiments of the present invention has a range of numerical values of predetermined excitement and significance. For example, music emotion can be expressed in similar order as 'calm', 'excited', 'happy', 'pleased', 'relaxed', 'peaceful', 'sleepy', 'sad', 'bored', 'nervous' '.

Next, in step S160, the context derivation unit 133 derives a user situation, which is a situation that the user is experiencing at the time of listening to the music using the user context data of the user data. The user environment data includes at least one of location information of the user device 200, inertia information of the user device 200, weather information of the location of the user device 200, and time information. The situation derivation unit 133 derives the user situation based on the user environment data. For example, the time information is in the morning time, the location information moves along the subway line, and if the speed of the user device 200 is equal to the speed of the subway through the inertia information, the user situation can be derived from the work. As another example, if the time information is the evening time, the location information is the gym, and the inertia information indicates a regular repetitive motion, the user situation can be derived from being exercised in the gym.

Next, in step S170, the emotion derivation unit 135 derives the emotion user emotion that the user feels at the time of listening to the music from the user emotion data of the user data. The user emotion data includes at least one of the user's bio-signal information and the user's device operation information. For example, the user may derive emotions felt by the user through the bio-signal information such as pulse or sweat discharge, or may listen to the music and listen to the music through the user's device operation information, The user's feelings can be derived. Therefore, the emotion derivation unit 135 can derive the user emotion based on the user emotion data.

As described above, when the music emotion, the user situation, and the user emotion are derived, the profile generating unit 137 mutually maps the music emotion, the user situation, and the user emotion into a three-dimensional graph as shown in FIG. 2 Thereby generating a music preference profile.

The above-described steps S110 to S180 are repeated so that the reliability of the music preference profile can be improved. For example, such a music preference profile can be used to determine whether a particular user is alone at home, listening to music that is 'excited' or sad when it is 'bored' Able to know.

Hereinafter, a method for recommending music based on the music preference profile will be described. 7 is a flowchart illustrating a method for recommending music according to an embodiment of the present invention.

Referring to FIG. 7, the control unit 290 of the user device 200 transmits a music recommendation request message to the recommendation server 100 through the communication unit 210 according to the user's operation in step S210.

Recommendation Server 100 Upon receiving the music recommendation request message through the communication module 110, the music recommendation unit 139 of the control module 130 transmits the music recommendation request message to the user device 200 through the communication module 110 in step S220. Request data.

The control unit 290 of the user device 200 receives the user data request through the communication unit 210. In step S230, the position information unit 230, the sensor unit 240, the audio unit 250, the input unit 260, And transmits the collected user data to the recommendation server 100 through the communication unit 210 in step S240.

When the recommendation server 100 receives the user data through the communication module 110, the recommendation server 100 starts the music recommendation procedure. First, the context derivation unit 133 derives a user situation, which is a situation that the user is experiencing at the time of requesting a music recommendation, using the user context data of the user data in step S250. The user environment data includes at least one of location information of the user device 200, inertia information of the user device 200, weather information of the location of the user device 200, and time information. The situation derivation unit 133 derives the user situation based on the user environment data.

Next, in step S260, the emotion derivation unit 135 derives an emotional user emotion that the user feels at the time of requesting the music recommendation from the user emotion data in the user data. The user emotion data includes at least one of the user's bio-signal information and the user's device operation information. Therefore, the emotion derivation unit 135 can derive the user emotion based on the user emotion data.

As described above, when the user situation and the user's feeling at the time of requesting the music recommendation are derived, the recommendation music unit 139 derives the recommended music based on the user's situation and the user's feeling at step S270. 3, the recommendation music unit 139 derives the music emotion corresponding to the user's situation and the user emotion on the three-dimensional graph of the preferred music profile, and determines whether or not the derived music emotion and similarity are within a predetermined range (M) (At least one of m, a, b, c, d, and e) of at least one music. More specifically, referring to FIG. 3, the recommendation music unit 139 derives a reference music m having music emotion corresponding to a user situation and a user emotion on a three-dimensional graph of a preferred music profile, and outputs the derived reference music m (M, a, b, b) of at least one music whose similarity is within a predetermined range (M) by calculating the similarity through the difference between the values of the arousal and the valence c, at least one of d and e).

When the recommended music is selected, the recommended music unit 139 transmits the recommended music to the user device 200 through the communication module 110 in step S280. The control unit 290 of the user device 200 receives the recommended music through the communication unit 210 and reproduces the received recommended music to output through the audio unit 250. [ Accordingly, the user can listen to the music suitable for the current environment and the emotion felt by the user.

Meanwhile, the methods for recommending music according to the embodiment of the present invention described above may be implemented in a form of a program readable by various computer means and recorded in a computer-readable recording medium. Here, the recording medium may include program commands, data files, data structures, and the like, alone or in combination. Program instructions to be recorded on a recording medium may be those specially designed and constructed for the present invention or may be available to those skilled in the art of computer software. For example, the recording medium may be a magnetic medium such as a hard disk, a floppy disk and a magnetic tape, an optical medium such as a CD-ROM or a DVD, a magneto-optical medium such as a floppy disk magneto-optical media, and hardware devices that are specially configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions may include machine language wires such as those produced by a compiler, as well as high-level language wires that may be executed by a computer using an interpreter or the like. Such a hardware device may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

While the present invention has been described with reference to several preferred embodiments, these embodiments are illustrative and not restrictive. It will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit of the invention and the scope of the appended claims.

100: recommended server 110: communication module
120: storage module 130: control module
131: Sensibility deriving part 133: Situation deriving part
135: emotion derivation unit 137: profile generation unit
139: music recommendation unit 200: user equipment
210: communication unit 220: camera unit
230: position information section 240: sensor section
250: audio part 260: input part
270: display unit 280: storage unit
290:

Claims (8)

An apparatus for recommending music,
A storage module for storing a music preference profile;
A communication module for communicating with a user device and receiving user data from the user device; And
A emotion derivation unit for deriving a music emotion that is emotional expressed by music played on the user device from the user data;
A situation derivation unit for deriving a user situation as a user is experiencing at the time of listening to the music;
An emotion derivation unit for deriving emotional user emotions felt by the user at the time of listening to the music from the user data; And
And a profile generator for generating the music preference profile by mapping the music emotion, the user situation, and the user emotion to a three-dimensional graph. The method according to claim 1,
And a controller for receiving user data at the time of requesting a music recommendation from the user apparatus through the communication module and transmitting the music recommendation message to a user who is in a situation that the user is experiencing at the time of requesting the music recommendation through the situation deriving unit, Deriving a feeling of a user who is feeling at the time of requesting the music recommendation through the emotion derivation unit and deriving musical emotion corresponding to the derived user situation and user emotion on the three dimensional graph of the preferred music profile And a music recommendation unit for selecting at least one music having similarity to the derived music sensibility within a predetermined range as a recommended music. 3. The method of claim 2,
Wherein the user data includes music emotion data including at least one of a plurality of parameters derived from a characteristic of a time domain signal of the music and a characteristic of a frequency domain signal,
Wherein the emotion derivation unit derives the excitivity representing the intensity of emotion from the music emotion data and the value representing the degree of affirmation and negation as a normalized value, And determining the sensibility of the music according to the music score. 3. The method of claim 2,
Wherein the user data includes user environment data including at least one of location information of the user device, inertia information of the user device, and weather information and time information of a location of the user device,
Wherein the context derivation unit derives the user context based on the user environment data. 3. The method of claim 2,
Wherein the user data includes user emotion data including at least one of user's bio-signal information and user's device operation information,
Wherein the emotion derivation unit derives the user emotion based on the user emotion data. 1. A method for recommending music in a recommendation server,
Receiving user data from a user device;
Deriving musical emotion that is emotional expressed by music played on the user apparatus from the user data;
Deriving a user situation that a user is experiencing at the time of listening to the music;
Deriving a user emotion as an emotion felt by the user at the time of listening to the music from the user data; And
And generating the music preference profile by mapping the music emotion, the user situation, and the user emotion to a three-dimensional graph. The method according to claim 6,
Receiving a music recommendation request from the user device;
Receiving user data at the music recommendation time point;
Deriving a user situation, which is a situation that a user is experiencing at the time of requesting the music recommendation, using the received user data, and an emotional user emotion felt by the user at the time of requesting the music recommendation;
Deriving musical emotion corresponding to the derived user situation and user emotion on the three-dimensional graph of the preferred music profile;
Selecting at least one piece of music having similarity to the derived music emotion within a predetermined range as recommended music; And
And transmitting the selected recommended music to the user device. ≪ RTI ID = 0.0 > 11. < / RTI > A computer-readable recording medium having recorded thereon a program for performing a method for recommending music according to claim 6 or 7.

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