KR101943638B1 - Music recommendation system and method based on user context - Google Patents

Abstract

The present invention relates to a device and method for recommending music according to a user's situation, which can determine a situation of a user of a mobile device whether a driver of a mobile device is a driver or a simple passenger, and recommend music corresponding to the situation, A sensor unit built in the mobile device or sensing the state information of the mobile device mounted on the mobile device, and a controller for classifying the status of the user of the mobile device as driving, traveling and other based on the information input from the sensor portion, A situation analyzer for outputting weights and other weights, and a controller for recommending music suitable for the situation of the mobile device based on the weights output from the situation analyzer.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a music recommendation apparatus and method,

The present invention relates to a music recommendation apparatus and method according to a user's situation, which can determine a situation of a user of a mobile device whether a driver of a mobile device is a driver or a simple passenger, and recommend music corresponding to the situation.

Mobile devices such as smart phones, tablets and wearable devices that are currently being launched have music functions, and these music functions are one of the important functions of mobile devices.

As a result, a variety of music management programs are being developed, and a music recommendation function suited to the user's taste is one of the core functions of the music management program. The music recommendation function can generally recommend personalized music according to the user and recommend the music according to the change of environment such as weather and time.

In this connection, Korean Patent Laid-Open Publication No. 2015-0001871 entitled " User Situation Based Music Recommendation System and Method, and Service Device Applied to It " A user situation based music recommendation system and method for recommending music to a user, and a service apparatus applied thereto.

However, conventionally, the user can not automatically check the status of the user by directly inputting the user's situation, and does not disclose a technique for recommending suitable music according to whether the user is driving or traveling.

 An embodiment of the present invention is to provide a music recommendation apparatus and method according to a user's situation recommending differentiated music according to boarding and driving to a user of a mobile device.

According to an embodiment of the present invention, a music recommendation apparatus according to a user's situation, which can determine whether a user of the mobile device is a driver or a passenger (occupant) by utilizing a sensor built in a mobile device or using a sensor mounted outside the mobile device Method.

It is to be understood, however, that the technical scope of the present invention is not limited to the above-described technical problems, and other technical problems may exist.

According to an aspect of the present invention, there is provided a music recommendation apparatus according to a user situation, the apparatus comprising: a sensor unit mounted in or incorporated in a mobile device for sensing status information of the mobile device; A situation analyzer for classifying the status of the user of the mobile device as driving, driving and other based on the information input from the sensor unit and outputting driver weights, passenger weights, and other weights; And recommending music suitable for the situation of the mobile device.
The music recommendation apparatus includes: a music database storing music to be recommended; And a tempo analyzer for outputting a weight value for music for driving and a weight value for music for boarding for each music in the music database, wherein the controller calculates a weight value output from the situation analyzer, And recommends music suitable for the situation of the mobile device based on the weight value output from the mobile device.
The condition analyzer includes a preprocessor and a processor. The preprocessor preprocesses the vibration value input from the acceleration sensor, outputs a vibration pattern, preprocesses the angular velocity value input from the gyrometer to output angular velocity information, The processor processes the speed information, the foreground processor information input from the sensor unit, the touch frequency pre-processed in the preprocess, the vibration pattern, and the angular velocity information by pre-processing the number of touches inputted and outputs the touch frequency, Value, the passenger weight value, and the other weight value.
The processor increases the driver weight value and the passenger weight value when the speed is greater than the vehicle speed threshold value and increases the other weight value when the speed is less than the vehicle speed threshold value.
The processor increases the occupant weight value when the touch frequency is greater than the touch threshold value and increases the other weight value when the touch frequency is less than the touch threshold value.
The processor increases the driver weight value if the vibration pattern is regular and increases the passenger weight value and the other weight value when the vibration pattern is irregular.
The processor increases the occupant weight value when the angular velocity is greater than the angular velocity threshold value, and increases the driver weight value when the angular velocity is smaller than the angular velocity threshold value.
The processor increases the driver weight value when the process is in a list of previously stored processes and increases the passenger weight value and the other weight value when the process is not present in the process list.

According to any one of the above-described tasks, the mobile device user can automatically determine whether the user is driving or not, using the speed, foreground processor information, touch frequency, vibration pattern, angular velocity information, can do.

In addition, according to the present invention, according to the music recommendation technique according to the user's situation, it is possible to recommend suitable music according to the user's situation (driving, traveling, etc.)

1 is a configuration diagram of a music recommendation apparatus according to a user situation according to an embodiment of the present invention.
FIG. 2 is a diagram showing the sensor unit of FIG. 1 in physical and software form included in a mobile device.
3 is a diagram showing an internal configuration and operation of the situation analyzing unit of FIG.
4 is a diagram showing a data flow in the situation analyzing unit.
5 is a diagram showing a decision table necessary for data processing by the situation analyzing unit.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, which will be readily apparent to those skilled in the art. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly explain the present invention in the drawings, parts not related to the description are omitted.

Whenever a component is referred to as "including" an element throughout the specification, it is to be understood that the element may include other elements, not the exclusion of any other element, unless the context clearly dictates otherwise.

Hereinafter, an apparatus and method for recommending music according to a user's situation according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is a configuration diagram of a music recommendation apparatus according to a user situation according to an embodiment of the present invention.

As shown in FIG. 1, the music recommendation apparatus according to the present invention includes at least one processor for performing a function, and further includes at least one processor for storing information necessary for performing a function, Or more memory.

Specifically, the music recommendation apparatus includes a sensor unit 101 including a plurality of sensors, a situation analyzing unit 102, a first weighting unit 103, a control unit 104, a music DB 105, a tempo analyzing unit 106, and a second weighting unit 107.

At this time, the sensor unit 101 may be a sensor built in a user's mobile device or a sensor mounted in a mobile device.

The situation analyzing unit 102 can classify the driver's situation into three types according to the sensing information input from the sensor unit 101: driving, moving, and the like.

The situation analyzing unit 102 processes the information obtained from the sensor unit 101 through preprocessing, analysis, and post-processing, and assigns three weight values for driving, traveling, and the like to the first weighting unit 103 Output.

The first weighting unit 103 stores three weighting values for the inputted driving, traveling, and the like, and the weighting value of the first weighting unit 103 is output to the control unit 104.

The music DB 105 stores music to be a recommendation target. At this time, the music DB 105 may be located in the mobile device or may be stored in the external cloud environment.

The tempo analyzer 106 measures a change in the tempo of the song, the length of the song, and the volume of the song with respect to each of the music in the music DB 105, and gives the weight for the driving music and the boarding music. The weight values for the driving music and the boarding music are output to the second weighting unit 107.

The second weighting unit 107 stores weight values of the input driving music and boarding music. The weight value of the second weighting unit 107 is output to the control unit 104. [

The control unit 104 controls the weighting value of the first weighting unit 103 for driving, traveling and others and weight values for the driving music and boarding music of the second weighting unit 107 to the mobile device user We recommend music that matches the current situation classification.

FIG. 2 is a diagram showing a physical and software configuration of the sensor unit 101 of FIG. 1 included in a mobile device.

2, the sensor unit 101 may be divided into a physical sensor unit 210, a software sensor unit 220, and a basic device information sensor unit 230.

The physical sensor unit 210 includes a GPS 211 for providing speed information, an acceleration sensor 212 for providing strength of vibration, a gyrometer 213 for providing a degree of tilting of the mobile device through angular velocity information, And a touch sensor 214 for providing a touch frequency.

The sensors of the physical sensor unit 210 operate independently of each other and may be mounted inside the mobile device 200 or may be mounted outside the mobile device 200 to transmit information to the mobile device 200 through a communication interface .

The software sensor unit 220 may include a process monitor 221 for providing information on a process currently operating in the mobile device 200 and a processor operating in the background with the help of an internal operating system (OS) .

The base device information sensor unit 230 may include a data storage 231 for storing parameters to be used for user status classification in advance. The data storage 231 may be mounted inside the mobile device 200 or may be mounted outside the mobile device 200 to transmit information to the mobile device through the communication interface.

FIG. 3 is a diagram showing an internal configuration and operation of the situation analyzing unit 102 of FIG. 1, FIG. 4 is a view showing a data flow in the situation analyzing unit 102, Fig.

3 to 5, a description will be given of a method for assigning weights for driving, traveling and others of the mobile device user in the situation analyzing unit 102. FIG.

The situation analyzer 102 mainly includes a preprocessor 301, a processor 302, a period timer 303, and a data repository 304.

At this time, the situation analyzer 102 is activated every time period determined by the period timer 303 and analyzes the situation based on the sensor values after the previous period.

The situation analyzing unit 102 receives " feature information " from the sensor unit 101 that can determine the user's situation. At this time, the feature information may include at least one of speed, touch frequency, foreground processor information, vibration pattern, and angular velocity.

Here, the speed means an average of the moving speed of the device during the last period input from the GPS 211. [

The touch frequency refers to information input from the front touch panel of the device during the last period, which means the number of touches of the user.

The foreground processor information means the app information currently displayed on the screen of the mobile device.

The vibration pattern is a value obtained by preprocessing the vibration value inputted from the acceleration sensor 212 by the preprocessor 301. The preprocessor 301 calculates the frequency of the vibration during the last period, Is compared with the stored value to extract the pattern.

The vibration pattern is determined to be regular when the difference between the frequency and the intensity is small, and is judged to be irregular when the difference between the frequency and the intensity is large. The value of the last period is again stored in the data store 304 and used to compare with the value of the next period.

The angular velocity information refers to an average value of the angular velocity sensor values input during the past period, which is a value obtained by preprocessing the angular velocity values input by the gyro-meter 213 during the past period.

The processor 302 processes the velocity, foreground processor information input from the sensor unit 101 and the touch frequency, vibration pattern, and angular velocity information preprocessed in the preprocessing 301 according to the determination table of FIG. 5, Lt; / RTI >

More specifically, the processor 302 utilizes speed information to increase the driver weight and the occupant weight when the vehicle speed is greater than the vehicle speed threshold value Vt. The processor 302 increases other weights if the vehicle speed is less than the vehicle speed threshold value Vt.

The processor 302 increases passenger weights and other weights if the touch frequency is greater than the touch threshold value Tt. The processor 302 increases the driver weight when the touch frequency is smaller than the touch threshold value Tt.

The processor 302 increases the driver weight if the process is in a list of previously stored processes. The processor 302 increases the equal winner weight and other weights if the process is not present in the pre-stored process list.

The processor 302 increases driver weights if the vibration pattern is regular and increases passenger weights and other weights if the vibration pattern is uneven.

The processor 302 increases the occupant weights and other weights if the angular velocity is greater than the angular velocity threshold value Ta. The processor 302 increases the driver weight when the angular velocity is smaller than the angular velocity threshold value Ta.

For the operation of the processor 302, parameters to be determined in advance in the present invention include an analysis cycle, a vibration pattern extraction (a frequency difference threshold value, an intensity difference threshold value), a vehicle speed threshold value, a touch threshold value, Threshold value, driver weight increase, passenger weight increase, and other weight increase. These parameters are stored in advance and are not changed during system operation.

As described above, the present invention can automatically determine whether the user of the mobile device is driving or not, using the speed, foreground processor information, touch frequency, vibration pattern, angular velocity information, and the like without user intervention.

In addition, in the present invention, it is possible to recommend suitable music according to the user's situation (driving, traveling, etc.).

In the present invention, the controller 104 recommends suitable music according to the user's situation. However, the present invention is not limited to this, and various kinds of services such as automatic execution of navigation, automatic rejection of messages and telephone, . ≪ / RTI >

In addition, in the present invention, the situation analyzer 102 has analyzed the situation of the user by dividing it into driving, moving and other, but the present invention is not limited to this and can be extended to situations such as cycling and walking.

The operating method in the music recommendation apparatus according to the user situation according to an embodiment of the present invention can also be implemented in the form of a recording medium including a computer program stored in a medium executed by the computer or an instruction executable by the computer . Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, the computer-readable medium may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Communication media typically includes any information delivery media, including computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, or other transport mechanism.

While the methods and apparatus of the present invention have been described with reference to particular embodiments, some or all of those elements or operations may be implemented using a computer system having a general purpose hardware architecture.

It will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the following claims . It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the present invention is defined by the appended claims rather than the detailed description and all changes or modifications derived from the meaning and scope of the claims and their equivalents are to be construed as being included within the scope of the present invention do.

101:
102: Situation Analysis Department
103: first weight portion
104:
105: Music DB
106: tempo analyzer
107: second weight portion

Claims (8)

A sensor unit built in or incorporated in the mobile device to sense status information of the mobile device;
A situation analyzer for classifying the status of the user of the mobile device as driving, driving and other on the basis of information input from the sensor unit and outputting driver weight values, passenger weight values, and other weight values; And
And a controller for recommending music suitable for the situation of the mobile device based on the weight value output from the situation analyzer,
Wherein the situation analyzer includes a preprocessor and a processor,
The preprocessor preprocesses the vibration value input from the acceleration sensor to output a vibration pattern, preprocesses the angular velocity value input from the gyrometer, outputs angular velocity information, preprocesses the touch frequency inputted from the touch panel, and outputs the touch frequency ,
The processor processes velocity information, foreground processor information input from the sensor unit, touch frequency, vibration pattern, and angular velocity information preprocessed in the preprocessing to determine the driver weight value, the passenger weight value, and the other weight value doing
Music recommendation device according to user situation. The method according to claim 1,
A music database storing music to be recommended; And
And a tempo analyzer for outputting a weight value for driving music and a weight value for traveling music for each music in the music database,
Wherein the controller recommends music suitable for a situation of the mobile device based on a weight value output from the situation analyzer and a weight value output from the tempo analyzer. delete The method according to claim 1,
Wherein the processor increases the driver weight value and the passenger weight value when the speed is greater than the vehicle speed threshold value and increases the other weight value when the speed is less than the vehicle speed threshold value
Music recommendation device according to user situation. The method according to claim 1,
Wherein the processor increases the passenger weight value when the touch frequency is greater than the touch threshold value and increases the other weight value when the touch frequency is less than the touch threshold value
Music recommendation device according to user situation. The method according to claim 1,
The processor increases the driver weight value if the vibration pattern is regular and increases the passenger weight value and the other weight value when the vibration pattern is irregular
Music recommendation device according to user situation. The method according to claim 1,
Wherein the processor increases the occupant weight value when the angular velocity is greater than the angular velocity threshold value and increases the driver weight value when the angular velocity is smaller than the angular velocity threshold value
Music recommendation device according to user situation. The method according to claim 1,
The processor increases the driver weight value when the process is in a list of previously stored processes and increases the passenger weight value and the other weight value when the process is not present in the process list
Music recommendation device according to user situation.

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