CN107301185A - Music commending system and method - Google Patents

Abstract

The present invention provides a kind of music and recommends method, and applied in server, the server is connected with least one client and a musical database, and storage includes the music of emotion numerical information in the musical database, and this method includes：Receiving step, the selected emotion numerical value X of user for receiving the client from client；Recommendation step, picks out a first emotion numerical value closest to X music, and the information of the music is sent into the client according to default rule from the musical database.Present invention also offers a kind of music commending system.Music can be recommended to personalization to user by the present invention.

Description

Music Recommendation System and Method

technical field

The invention relates to a music recommendation system and a music recommendation method.

Background technique

The existing music recommendation method will recommend music to the user according to the music style or music type selected by the user, but it will not detect the emotional changes of the user after listening to the music, so that the recommended music cannot meet the requirements of the user. the individual needs of the individual.

Contents of the invention

In view of the above, it is necessary to provide a music recommendation system and a music recommendation method, which can recommend music personalizedly according to the user's emotional changes after hearing the recommended music.

A music recommendation system, applied to a server, the server is connected to at least one client and a music database, the music database stores music containing emotional value information, the system includes: a receiving module, used to receive from the client The emotional value X selected by the user of the client; the recommendation module is used to select a piece of music whose emotional value is closest to X from the music database according to preset rules, and send information about the music to the client.

The music recommendation system further includes an adjustment module, configured to receive the physiological data of the user of the client after listening to the music from the client, and calculate the usage according to the physiological data and a preset algorithm. The user's current emotional value Z, and select another piece of music from the music database according to the user's current emotional value Z and the selected emotional value X, and send the music information to the client.

A method for recommending music, applied to a server, the server is connected to at least one client and a music database, the music database stores music containing emotional value information, the method includes: a receiving step, receiving the client from the client The emotional value X selected by the user at the terminal; the recommendation step is to select a piece of music whose emotional value is closest to X from the music database according to the preset rules, and send the information of the music to the client.

The music recommendation method further includes an adjustment step, receiving from the client the physiological data of the user of the client after listening to the music, and calculating the current state of the user according to the physiological data and a preset algorithm. According to the user's current emotional value Z and the selected emotional value X, another piece of music is selected from the music database, and the information of the music is sent to the client.

Compared with the prior art, the music recommendation system of the present invention adjusts the recommended music individually by acquiring the emotional changes of the user after hearing the recommended music, thereby improving the experience effect of the user.

Description of drawings

FIG. 1 is a schematic diagram of the operating environment of a preferred embodiment of the music recommendation system of the present invention.

Fig. 2 is a functional block diagram of a preferred embodiment of the music recommendation system of the present invention.

Fig. 3 is a flowchart of a preferred embodiment of the music recommendation method of the present invention.

Description of main component symbols

The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings.

detailed description

Referring to FIG. 1 , it is a schematic view of the operating environment of a preferred embodiment of the music recommendation system of the present invention. The music recommendation system 10 is installed in the client 1 and the server 2 . The server 2 communicates with at least one client 1 (only one is shown in the figure). The client 1 further includes, but not limited to, a first communication device 11 , a first storage device 12 , a first processor 13 , an input device 14 , a playback device 15 and a physiological detection device 16 . The server 2 also includes, but not limited to, a second communication device 21 , a second storage device 22 , a second processor 23 and a music database 220 .

The client 1 communicates with the server 2 through the first communication device 11 and the second communication device 21 . The first communication device 11 and the second communication device 21 may be devices capable of wireless communication such as a wireless network card and a GPRS module, or devices capable of wired communication such as a network card.

The first storage device 12 and the second storage device 22 are used to store the program instruction segment and data data of each program installed in the client 1 and the server 2 respectively, which can be internal storage devices such as memory, or intelligent External storage devices such as SmartMedia Card, Secure Digital Card, and Flash Card.

The first processor 13 and the second processor 23 are respectively used to execute the program instruction segment of the program installed in the client 1 and the server 2 and control each device to perform corresponding operations.

The input device 14 is used for receiving input operations of the user of the client 1 , such as inputting emotional values, selecting music, and so on. The input device 14 may be a touch screen, or other input devices, such as a keyboard. The playing device 15 is used for playing music.

The physiological detection device 16 is used for detecting the physiological data of the user of the client terminal 1 . The physiological data may be one or more of data such as heartbeat, pulse, and finger temperature. In one embodiment, the physiological detection device 16 may be located in the client 1, at this time, the physiological detection device 16 may be a pressure sensor, a temperature sensor, etc., and the client 1 may have a detection Wearable devices that measure user physiological data and play music, such as smart watches, smart bracelets, etc. In another embodiment, the physiological detection device 16 can also be located outside the client 1 , for example, the physiological detection device 16 is connected to the client 1 through wireless communication. At this time, the physiological detection device 16 may be a wearable device capable of detecting physiological data of a user, such as a smart watch, a smart bracelet, and the like. The client 1 may be an electronic device capable of playing music, such as a smart phone, a tablet computer, and the like.

The emotional value of each piece of music is stored in the music database 220 . The music can be stored in the first storage device 12 of the client 1, can also be stored in the second storage device 22 of the server 2, or can be stored in a other connected electronic devices. In this embodiment, the music database 220 is stored in the second storage device 22 of the server 2 . In another embodiment, the music database 220 is stored in the first storage device 12 of the client 1 . In yet another embodiment, the music database 220 may also be stored in another electronic device connected to the server 2 or the client 1 .

The music database 220 obtains the emotional value of each music through the following steps: extract various sound features from the music, determine the model parameters corresponding to each sound feature according to existing statistical methods, and then calculate the music value according to each model parameter. emotional value. Each emotion type corresponds to one or more emotion value ranges. For example, when the emotion value is between X1 and X2, the corresponding emotion type is happy. When the emotion value is between X3 and X4, the corresponding emotion type can also be happy.

In the client 1, the music recommendation system 10 is configured to receive the emotional value X selected by the user of the client 1 through the input device 14 (in this specification, X represents the emotional value selected by the user), and The selected emotional value X is sent to the server 2, and when the music information sent by the server 2 is received, the corresponding music is acquired and played according to the music information. The music recommendation system 10 is also used to detect the physiological data of the user of the client 1 after listening to the music through the physiological detection device 16 , and send the detected physiological data to the server 2 . In the server 2, the music recommendation system 10 is configured to select an emotional value X from the music database 220 according to preset rules when receiving the emotional value X selected by the user of the client 1 The music closest to X, and send the information of the music to the client 1. The music recommendation system 10 is also used to calculate the user's current emotional value Z (in this specification, Z represent the detected emotional value), and select another piece of music from the music database 220 according to the user's current emotional value Z and the selected emotional value X, and send the information of the music to the client 1.

Referring to FIG. 2 , it is a functional block diagram of a preferred embodiment of the music recommendation system of the present invention. The music recommendation system 10 can be divided into a first receiving module 101 , a second receiving module 102 , a recommending module 103 , a playing module 104 , a detecting module 105 and an adjusting module 106 . In this embodiment, the first receiving module 101 , the playing module 104 and the detecting module 105 are applied in the client 1 . The second receiving module 102 , the recommending module 103 and the adjusting module 106 are applied in the server 2 . In another embodiment, if the music database 220 is stored in the client 1, the first receiving module 101, the second receiving module 102, the recommending module 103, the playing module 104, the detecting module 105 and the adjusting module 106 Both run on client 1. The modules referred to in the present invention refer to a series of computer program segments capable of completing specific functions, which are more suitable than programs for describing the execution process of the music recommendation system 10. The specific functions of each module will be described below in conjunction with the flowchart of FIG. 3 .

Referring to FIG. 3 , it is a flowchart of a preferred embodiment of the music recommendation method of the present invention. In this embodiment, according to different requirements, the execution order of the steps in the flowchart shown in FIG. 3 may be changed, and some steps may be omitted.

Step S31, the first receiving module 101 receives the emotional value X selected by the user of the client 1 through the input device 14, and sends the emotional value X to the server 2 through the first communication device 11 . The first receiving module 101 is executed by the client 1 . In this embodiment, the input device 14 is a touch screen. The user of the client terminal 1 inputs the emotional value X through the input device 14 . In other embodiments, the input device 14 may also be a microphone. The user of the client terminal 1 inputs the emotional value X through the input device 14 , such as speaking a number.

Step S32 , the second receiving module 102 receives the emotional value X selected by the user of the client 1 sent by the client 1 through the second communication device 21 . The second receiving module 102 is executed by the server 2 .

In step S33, the recommendation module 103 selects a piece of music whose emotional value is closest to X from the music database 220 according to preset rules, and sends information about the music to the client through the second communication device 21 1.

In this embodiment, the preset rule is to first select one or more pieces of music whose difference between the emotional value and the specified emotional value (such as X) is within a certain range from the music database 220, and then select from the music database 220. A piece of music is randomly selected from one or more pieces of music.

In another embodiment, the preset rule is to first select from the music database 220 one or more pieces of music whose difference between the emotional value and the specified emotional value (such as X) is within a certain range, and then select A music with the least number of times of playing is selected from the one or more pieces of music. At this point, the music database 220 also needs to store the total number of times each piece of music is played or the total number of times within a preset time (for example, three days).

In yet another embodiment, the preset rule is to select one or more pieces of music whose difference between the emotional value and the specified emotional value (such as X) is within a certain range from the music database 220, and then select The music that the user does not like is removed from the one or more pieces of music, and then a piece of music is randomly selected from the remaining music.

In yet another embodiment, the preset rule is to select from the music database 220 a piece of music whose emotional value is closest to a specified emotional value (for example, X).

Step S34 , the playing module 104 receives the music information sent by the server 2 through the first communication device 11 , acquires the music according to the music information, and plays the music through the playing device 15 . The music can be stored in the first storage device 12 of the client 1, can also be stored in the second storage device 22 of the server 2, or can be stored in a connected to another electronic device.

Step S35, the detection module 105 detects the physiological data of the user of the client 1 after listening to the music through the physiological detection device 16, and transmits the detected physiological data through the first communication device 11 to the server 2.

It should be noted that the detection module 105 is when the user of the client 1 is listening to the music to a certain extent (for example, the music is played to two-thirds, or the music is played, or the music is played for 2 minutes. ), the physiological data of the user of the client terminal 1 is detected by the physiological detection device 16 . The physiological data may be one or more of data such as heartbeat, pulse, and finger temperature.

Step S36, the adjustment module 106 receives the physiological data sent by the client 1 through the second communication device 21, and calculates the current emotional value of the user of the client 1 according to the physiological data and a preset algorithm Z. The preset algorithm may be an algorithm for estimating Arousal-Valence.

Step S37, the adjustment module 106 selects another piece of music from the music database 220 according to the current emotional value Z and the selected emotional value X of the user of the client 1, and passes the information of the music through the The second communication device 21 sends to the client 1 .

The adjustment module 106 selects another piece of music from the music database 220 according to the user's current emotional value Z and the selected emotional value X through the following steps: According to the user's current emotional value Z and the selected emotional value X calculate the compensation value Y, said Y=X-Z; and select an emotional value closest to X+Y (that is, 2*X-Z) from the music database 220 according to preset rules music.

Step S38 , the playing module 104 receives the music information sent by the server 2 through the first communication device 11 , obtains the music according to the music information, and plays the music through the playing device 15 , and the process ends.

It should be noted that, in another embodiment, if the next music is to be further recommended, it is necessary to return to step S35.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention without limitation. Those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the technical solutions of the present invention. The spirit and scope of the programme.

Claims (15)

1. A music recommendation system, applied in a server, the server is connected with at least one client and a music database, the emotional value information of each music is stored in the music database, it is characterized in that the system includes: The receiving module is used to receive the emotional value X selected by the user of the client from the client; The recommending module is configured to select a piece of music whose emotional value is closest to X from the music database according to preset rules, and send information about the music to the client. 2. music recommendation system as claimed in claim 1, is characterized in that, this system also comprises: An adjustment module, configured to receive physiological data of the user of the client after listening to the music from the client, calculate the user's current emotional value Z according to the physiological data and a preset algorithm, and Select another piece of music from the music database according to the user's current emotion value Z and the selected emotion value X, and send information about the music to the client. 3. The music recommendation system according to claim 2, wherein the adjustment module selects another piece of music from the music database according to the user's current emotional value Z and the selected emotional value X through the following steps : Calculate the compensation value Y according to the user's current emotional value Z and the selected emotional value X, where Y=X-Z; and Select a piece of music whose emotional value is closest to X+Y=2*X-Z from the music database according to preset rules. 4. The music recommendation system according to claims 1 to 3, wherein the preset rule is to select from the music database a song or song whose difference between the emotional value and the specified emotional value is within a certain range. Multiple pieces of music, and a piece of music is randomly selected from the one or more pieces of music. 5. The music recommendation system according to claims 1 to 3, wherein the preset rule is to select from the music database a song or song whose difference between the emotional value and the specified emotional value is within a certain range. multiple pieces of music, and then select a piece of music with the least number of plays from the one or more pieces of music. 6. The music recommendation system according to claims 1 to 3, wherein the preset rule is to select from the music database a song or song whose difference between the emotional value and the specified emotional value is within a certain range. A plurality of pieces of music, then remove the music that the user does not like from the one or more pieces of music, and then randomly select a piece of music from the remaining music. 7. A music recommendation method, applied in a server, the server is connected with at least one client and a music database, the emotional value information of each music is stored in the music database, it is characterized in that the method comprises: The receiving step is to receive the emotional value X selected by the user of the client from the client; In the recommending step, a piece of music whose emotional value is closest to X is selected from the music database according to preset rules, and the information of the music is sent to the client. 8. The music recommendation method according to claim 7, further comprising: The adjustment step is to receive the physiological data of the user of the client after listening to the music from the client, calculate the current emotional value Z of the user according to the physiological data and a preset algorithm, and calculate the user's current emotional value Z according to the usage Select another piece of music from the music database based on the user's current emotional value Z and the selected emotional value X, and send the music information to the client. 9. The music recommendation method according to claim 8, wherein the adjustment step selects another piece of music from the music database according to the user's current emotional value Z and the selected emotional value X through the following steps : Calculate the compensation value Y according to the user's current emotional value Z and the selected emotional value X, where Y=X-Z; and Select a piece of music whose emotional value is closest to X+Y=2*X-Z from the music database according to preset rules. 10. The method for recommending music as claimed in claims 7 to 9, wherein the preset rule is to select from the music database a song or song whose difference between the emotional value and the specified emotional value is within a certain range. Multiple pieces of music, and a piece of music is randomly selected from the one or more pieces of music. 11. The method for recommending music as claimed in claims 7 to 9, wherein the preset rule is to select from the music database a song or song whose difference between the emotional value and the specified emotional value is within a certain range. multiple pieces of music, and then select a piece of music with the least number of plays from the one or more pieces of music. 12. The method for recommending music as claimed in claims 7 to 9, wherein the preset rule is to select from the music database a song or song whose difference between the emotional value and the specified emotional value is within a certain range. A plurality of pieces of music, then remove the music that the user does not like from the one or more pieces of music, and then randomly select a piece of music from the remaining music. 13. A method for recommending music, which is applied to a client, the client is connected to a server, the server is connected to a music database storing emotional value information of each music, the client includes an input device and a playback device, It is characterized in that the method includes: The receiving step is to receive the emotional value X selected by the user of the client through the input device, and send the emotional value X to the server; The playing step is to receive from the server the information of the music selected by the server from the music database according to the emotional value X, obtain the music according to the information of the music, and play the music through the playing device. 14. The music recommendation method according to claim 13, wherein the client also includes a physiological detection device, and the method also includes: The detection step is to detect the physiological data of the user of the client after listening to the music through the physiological detection device, and send the detected physiological data to the server. 15. The method for recommending music according to claim 14, wherein said playing step also receives from said server said server from said music database according to said emotional value X and said physiological data. information of the selected music, obtain the music according to the information of the music, and play the music through the playback device.