CN107301185B - Music recommendation system and method - Google Patents
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- CN107301185B CN107301185B CN201610235644.8A CN201610235644A CN107301185B CN 107301185 B CN107301185 B CN 107301185B CN 201610235644 A CN201610235644 A CN 201610235644A CN 107301185 B CN107301185 B CN 107301185B
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Abstract
The invention provides a music recommendation method, which is applied to a server, wherein the server is connected with at least one client and a music database, and music containing emotion numerical value information is stored in the music database, and the method comprises the following steps: a receiving step of receiving an emotion value X selected by a user of a client from the client; and a recommendation step, selecting a piece of music with the emotion value closest to X from the music database according to a preset rule, and sending the information of the music to the client. The invention also provides a music recommendation system. The invention can be used for recommending music to users in a personalized way.
Description
Technical Field
The invention relates to a music recommendation system and a music recommendation method.
Background
The existing music recommending method recommends music to a user according to the music style or music type selected by the user, but the emotion change and the like of the user after listening to the music cannot be detected, so that the recommended music cannot meet the personalized requirements of the user.
Disclosure of Invention
In view of the above, it is desirable to provide a music recommendation system and a music recommendation method that can personalize recommended music according to the emotional change of a user after hearing the recommended music.
A music recommendation system is applied to a server, the server is connected with at least one client and a music database, music containing emotion numerical value information is stored in the music database, and the system comprises: the receiving module is used for receiving the emotion numerical value X selected by a user of the client from the client; and the recommending module is used for selecting a piece of music with the emotion numerical value closest to X from the music database according to a preset rule and sending the information of the music to the client.
The music recommendation system further comprises an adjusting module, which is used for receiving physiological data of a user of the client after listening to the music from the client, calculating a current emotion numerical value Z of the user according to the physiological data and a preset algorithm, selecting another piece of music from the music database according to the current emotion numerical value Z of the user and the selected emotion numerical value X, and sending the information of the music to the client.
A music recommendation method is applied to a server, the server is connected with at least one client and a music database, music containing emotion numerical value information is stored in the music database, and the method comprises the following steps: a receiving step of receiving an emotion value X selected by a user of a client from the client; and a recommendation step, selecting a piece of music with the emotion value closest to X from the music database according to a preset rule, and sending the information of the music to the client.
The music recommendation method further comprises an adjusting step of receiving physiological data of a user of the client after listening to the music from the client, calculating a current emotion numerical value Z of the user according to the physiological data and a preset algorithm, selecting another piece of music from the music database according to the current emotion numerical value Z of the user and the selected emotion numerical value X, and sending the information of the music to the client.
Compared with the prior art, the music recommendation system provided by the invention can adjust the recommended music in a personalized manner by acquiring the emotion change of the user after hearing the recommended music, so that the experience effect of the user is improved.
Drawings
FIG. 1 is a diagram illustrating an operating environment of a music recommendation system according to a preferred embodiment 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 illustrating a music recommendation method according to a preferred embodiment of the present invention.
Description of the main elements
The following detailed description will further illustrate the invention in conjunction with the above-described figures.
Detailed Description
Referring to fig. 1, a schematic diagram of an operating environment of a music recommendation system according to a preferred embodiment of the invention is shown. The music recommendation system 10 is installed in the client 1 and the server 2. The server 2 is communicatively connected to at least one client 1 (only one is shown in the figure). The client 1 further includes, but is not limited to, a first communication device 11, a first storage device 12, a first processor 13, an input device 14, a playing device 15, and a physiological detection device 16. The server 2 further comprises, but is not limited to, a second communication means 21, a second storage means 22, a second processor 23 and a music database 220.
The client 1 and the server 2 are communicatively connected by 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 may be devices capable of wired communication, such as a network card.
The first storage device 12 and the second storage device 22 are used for storing program instruction segments and data of programs installed in the client 1 and the server 2, respectively, and may be internal storage devices such as a memory, or external storage devices such as a Smart Media Card (Smart Media Card), a Secure Digital Card (Secure Digital Card), and a Flash memory Card (Flash Card).
The first processor 13 and the second processor 23 are respectively used for executing program instruction segments of programs installed in the client 1 and the server 2 and controlling each device to execute corresponding operations.
The input device 14 is used for receiving input operations of the user of the client 1, such as inputting emotion values, selecting music, and the like. The input device 14 may be a touch screen, or may be 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 physiological data of a user of the client 1. The physiological data may be one or more of heartbeat, pulse, finger temperature, etc. In an embodiment, the physiological detection device 16 may be located in the client 1, in this case, the physiological detection device 16 may be a pressure sensor, a temperature sensor, or the like, and the client 1 may be a wearable device having functions of detecting physiological data of a user and playing music, such as a smart watch, a smart bracelet, or the like. In another embodiment, the physiological detection device 16 can also be located outside the client 1, for example, the physiological detection device 16 and the client 1 are connected through wireless communication. In this case, the physiological detection device 16 may be a wearable device having a function 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 with a music playing function, such as a smart phone, a tablet computer, and the like.
The music database 220 stores emotion values of each piece of music. The music may be stored in the first storage device 12 of the client 1, the second storage device 22 of the server 2, or another electronic device connected to the server 2 or the client 1. In the present 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 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 emotion value of each music by the following steps: extracting various sound characteristics from music, determining model parameters corresponding to the sound characteristics according to the existing statistical method, and then calculating the emotion value of the music according to the model parameters. Each emotion type corresponds to one or more ranges of emotion values. 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 may be happy.
In the client 1, the music recommendation system 10 is configured to receive, through an input device 14, an emotion value X selected by a user of the client 1 (in this specification, X represents the emotion value selected by the user), send the selected emotion value X to the server 2, and, when receiving music information sent by the server 2, obtain and play corresponding music according to the music information. The music recommendation system 10 is further configured to detect physiological data of the user of the client 1 after listening to the music through a 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, when receiving an emotion value X selected by a user of the client 1, pick out a piece of music with an emotion value closest to X from the music database 220 according to a preset rule, and send information of the music to the client 1. The music recommendation system 10 is further configured to, when receiving physiological data of a user at the client 1, calculate a current emotion value Z of the user (in this specification, Z represents a detected emotion value) according to the physiological data and a preset algorithm, select another piece of music from the music database 220 according to the current emotion value Z of the user and the selected emotion value X, and send information of the piece of music to the client 1.
Referring to fig. 2, a functional block diagram of a music recommendation system according to a preferred embodiment of the present invention is shown. 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 to the client 1. The second receiving module 102, the recommending module 103 and the adjusting module 106 are applied to 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 are all operated in the client 1. The modules referred to in the present invention refer to a series of computer program segments capable of performing specific functions, and are more suitable than programs for describing the execution process of the music recommendation system 10, and the specific functions of each module will be described below with reference to the flowchart of fig. 3.
Referring to FIG. 3, a flowchart of a music recommendation method according to a preferred embodiment of the invention is shown. In this embodiment, the execution order of the steps in the flowchart shown in fig. 3 may be changed and some steps may be omitted according to different requirements.
In step S31, the first receiving module 101 receives the emotion value X selected by the user of the client 1 through the input device 14, and sends the emotion 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 1 inputs the emotion value X through the input device 14. In other embodiments, the input device 14 may also be a microphone. The user of the client 1 inputs an emotion value X, for example a spoken number, via the input device 14.
In step S32, the second receiving module 102 receives the emotion value X selected by the user of the client 1 and transmitted 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 recommending module 103 selects a piece of music with emotion value closest to X from the music database 220 according to a preset rule, and sends the information of the piece of music to the client 1 through the second communication device 21.
In this embodiment, the predetermined rule is to select one or more pieces of music from the music database 220 with a difference between an emotion value and a specified emotion value (e.g., X) within a certain range, and then randomly select one piece of music from the one or more pieces of music.
In another embodiment, the predetermined rule is to select one or more pieces of music from the music database 220 with a difference between the emotion value and the specified emotion value (e.g., X) within a certain range, and then select one piece of music with the smallest playing time from the one or more pieces of music. At this time, 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) needs to be stored in the music database 220.
In another embodiment, the predetermined rule is to select one or more pieces of music from the music database 220 with a difference between the emotion value and the specified emotion value (e.g., X) within a certain range, remove the music that is not liked by the user from the one or more pieces of music, and randomly select one piece of music from the rest of music.
In another embodiment, the predetermined rule is to select the music database 220 with the emotion value closest to the specified emotion value (e.g., X).
In step S34, the playing module 104 receives the information of the music sent by the server 2 through the first communication device 11, obtains the music according to the information of the music, and plays the music through the playing device 15. The music may be stored in the first storage device 12 of the client 1, may be stored in the second storage device 22 of the server 2, or may be stored in another electronic device connected to the server 2 or the client 1.
In step S35, the detecting module 105 detects the physiological data of the user of the client 1 after listening to the music through the physiological detecting device 16, and sends the detected physiological data to the server 2 through the first communication device 11.
It should be noted that, when the user of the client 1 listens to the music to a certain extent (for example, the music is played to two thirds, or the music is played completely, or the music is played for 2 minutes), the detecting module 105 detects the physiological data of the user of the client 1 through the physiological detecting device 16. The physiological data may be one or more of heartbeat, pulse, finger temperature, etc.
In step S36, the adjusting module 106 receives the physiological data sent by the client 1 through the second communication device 21, and calculates the current emotion value Z of the user of the client 1 according to the physiological data and a preset algorithm. The predetermined algorithm may be an algorithm for estimating Arousal-value.
In step S37, the adjusting module 106 selects another piece of music from the music database 220 according to the current emotion value Z and the selected emotion value X of the user of the client 1, and sends the information of the piece of music to the client 1 through the second communication device 21.
The adjusting module 106 selects another piece of music from the music database 220 according to the current emotion value Z and the selected emotion value X of the user of the client 1 by: calculating a compensation value Y according to the current emotion numerical value Z of the user and the selected emotion numerical value X, wherein Y is X-Z; and selecting a piece of music with emotion value closest to X + Y (i.e. 2X-Z) from the music database 220 according to a preset rule.
In step S38, the playing module 104 receives the information of the music sent by the server 2 through the first communication device 11, obtains the music according to the information of the music, and plays the music through the playing device 15, and the process ends.
In another embodiment, if the next piece of music is to be recommended, the process returns to step S35.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and not for limiting, and those skilled in the art should understand that the technical solutions of the present invention can be modified or substituted with equivalents without departing from the spirit and scope of the technical solutions of the present invention.
Claims (11)
1. A music recommendation system is applied to a server, the server is connected with at least one client and a music database, and emotion numerical value information of each piece of music is stored in the music database, and the system is characterized by comprising:
the receiving module is used for receiving the emotion numerical value X selected by a user of the client from the client;
the recommendation module is used for selecting a piece of music with the emotion numerical value closest to X from the music database according to a preset rule and sending the information of the music to the client; and
the adjusting module is used for receiving the physiological data of the user of the client after listening to the music from the client, calculating the current emotion numerical value Z of the user according to the physiological data and a preset algorithm, calculating a compensation value Y according to the current emotion numerical value Z of the user and the selected emotion numerical value X, selecting another piece of music from the music database according to the emotion numerical value X selected by the user and the calculated compensation value Y, and sending the information of the music to the client.
2. The music recommendation system of claim 1 wherein the adjustment module selects another piece of music from the music database based on the user selected emotion value X and the calculated compensation value Y by:
and selecting a piece of music with the emotion value closest to X + Y from the music database according to a preset rule, wherein Y is X-Z.
3. The music recommendation system according to claim 1 or 2, wherein the predetermined rule is to select one or more pieces of music from the music database, the one or more pieces of music having a difference between the emotion value and the specified emotion value within a certain range, and randomly select one piece of music from the one or more pieces of music.
4. The music recommendation system according to claim 1 or 2, wherein the predetermined rule is to select one or more pieces of music from the music database, the emotion value of which is within a certain range of the specified emotion value, and select one piece of music from the one or more pieces of music, the music being played for the least number of times.
5. The music recommendation system according to claim 1 or 2, wherein the predetermined rule is to select one or more pieces of music from the music database, wherein the difference between the emotion value and the specified emotion value is within a certain range, remove the music that is not liked by the user from the one or more pieces of music, and randomly select one piece of music from the remaining pieces of music.
6. A music recommendation method is applied to a server, the server is connected with at least one client and a music database, and emotion numerical value information of each piece of music is stored in the music database, and the method is characterized by comprising the following steps:
a receiving step of receiving an emotion value X selected by a user of a client from the client;
a recommendation step, selecting a piece of music with the emotion numerical value closest to X from the music database according to a preset rule, and sending the information of the music to the client; and
and an adjusting step, namely receiving the physiological data of the user of the client after listening to the music from the client, calculating the current emotion numerical value Z of the user according to the physiological data and a preset algorithm, calculating a compensation value Y according to the current emotion numerical value Z of the user and the selected emotion numerical value X, selecting another piece of music from the music database according to the emotion numerical value X selected by the user and the calculated compensation value Y, and sending the information of the music to the client.
7. The music recommendation method of claim 6, wherein the adjusting step selects another piece of music from the music database according to the emotion value X selected by the user and the calculated compensation value Y by:
and selecting a piece of music with the emotion value closest to X + Y from the music database according to a preset rule, wherein Y is X-Z.
8. The music recommendation method according to claim 6 or 7, wherein the predetermined rule is to select one or more pieces of music from the music database, wherein the difference between the emotion value and the specified emotion value is within a certain range, and randomly select one piece of music from the one or more pieces of music.
9. The music recommendation method according to claim 6 or 7, wherein the predetermined rule is to select one or more pieces of music from the music database, the emotion value of which is within a certain range of the specified emotion value, and select one piece of music from the one or more pieces of music, the music being played for the least number of times.
10. The music recommendation method according to claim 6 or 7, wherein the predetermined rule is to select one or more pieces of music from the music database, wherein the difference between the emotion value and the designated emotion value is within a certain range, remove the music that the user does not like from the one or more pieces of music, and randomly select one piece of music from the rest of music.
11. A music recommendation method is applied to a client, the client is connected with a server, the server is connected with a music database storing emotion numerical information of each piece of music, the client comprises an input device, a physiological detection device and a playing device, and the method is characterized by comprising the following steps:
a receiving step of receiving an emotion numerical value X selected by a user of the client through an input device and sending the emotion numerical value X to the server;
a playing step, namely receiving the information of the music selected by the server from the music database according to the emotion numerical value X from the server, acquiring the music according to the information of the music, and playing the music through the playing device; and
a detecting step of detecting physiological data of the user of the client after listening to the music through the physiological detecting device and sending the detected physiological data to the server;
the server determines a compensation value according to the emotion value X and the physiological data, and the playing step further receives information of music selected by the server from the music database according to the emotion value X and the compensation value, acquires the music according to the information of the music, and plays the music through the playing device.
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| CN110555128A (en) * | 2018-05-31 | 2019-12-10 | 蔚来汽车有限公司 | music recommendation playing method and vehicle-mounted infotainment system |
| CN111430006B (en) * | 2020-03-18 | 2023-09-19 | 深圳市人工智能与机器人研究院 | Emotion adjustment method, emotion adjustment device, computer equipment and storage medium |
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