CN111694982A

CN111694982A - Song recommendation method and system

Info

Publication number: CN111694982A
Application number: CN201911180369.4A
Authority: CN
Inventors: 李宣儒; 董立春
Original assignee: Shenzhen Ubox Technology Co ltd
Current assignee: Shenzhen Ubox Technology Co ltd
Priority date: 2019-11-27
Filing date: 2019-11-27
Publication date: 2020-09-22

Abstract

The application is applicable to the technical field of entertainment equipment, and provides a song recommendation method and a song recommendation system, which comprise the following steps: acquiring a target image; extracting characteristic information of an object to be detected according to the target image; the recommended song list is determined according to the characteristic information and pushed to the song ordering device, the characteristic information of the user is obtained, the songs are recommended according to the characteristic information of the user, a customized recommended song ordering interface can be provided according to the characteristics (age, sex and number of people) of the user, the user can conveniently select the songs to be ordered, and the problem that the customized recommended song ordering interface cannot be provided for the specific user in the conventional song recommending method is effectively solved.

Description

Song recommendation method and system

Technical Field

The application belongs to the technical field of entertainment equipment, and particularly relates to a song recommendation method and system.

Background

With the improvement of living standard of people, various entertainment places are more popular, including KTV. The KTV is a fixed entertainment place, a user can select favorite songs, videos corresponding to the selected songs can be played on a display screen, and the user can sing the songs by taking a microphone. The existing KTV song requesting device generally has a popular song requesting interface, popular songs are recommended song lists counted according to the song requesting times of all songs within a certain time interval, and the song recommending mode cannot provide a customized recommended song requesting interface for a specific user.

In summary, the conventional song recommendation method has the problem that a customized song recommendation and ordering interface cannot be provided for a specific user.

Disclosure of Invention

The embodiment of the application provides a song recommendation method and a song recommendation system, which can solve the problem that the conventional song recommendation method cannot provide a customized song recommendation and selection interface for a specific user.

In a first aspect, an embodiment of the present application provides a song recommendation method, including:

acquiring a target image;

extracting characteristic information of an object to be detected according to the target image;

and determining a recommended song list according to the characteristic information, and pushing the recommended song list to a singing ordering device.

For example, the characteristic information of the object to be detected includes, but is not limited to, an age characteristic, a number characteristic, a gender characteristic, an identity characteristic, and the like.

In a possible implementation manner of the first aspect, the determining a recommended song list according to the feature information and pushing the recommended song list to a singing ordering device includes:

determining user identification information and a user age interval according to the characteristic information;

acquiring a historical song order list according to the user identification information;

acquiring a recommended song list corresponding to the user age interval according to the user age interval;

and determining a recommended song list according to the historical song order list and the recommended song list.

In a possible implementation manner of the first aspect, when the target image includes a plurality of objects to be detected, the determining a recommended song list according to the user characteristics and pushing the recommended song list to a singing ordering device includes:

determining user identification information of each object to be detected according to the characteristic information of each object to be detected;

acquiring a historical song-singing-clicking list according to the user identification information of each object to be detected;

determining a user age interval of each object to be detected according to the age characteristics of each object to be detected;

acquiring a recommended song list corresponding to each user age area according to the user age interval of each object to be detected;

and determining a recommended song list according to the historical song ordering list and the recommended song list corresponding to each user age interval.

Further, still include:

detecting whether the sexes of the plurality of objects to be detected are the same;

and if the sexes of the plurality of objects to be detected are the same, determining a recommended song list according to the gender characteristics.

Further, still include:

if the sexes of the plurality of objects to be detected are different, detecting the ages of the objects to be detected with different sexes;

if the ages of the objects to be detected with different genders are larger than a preset age threshold value, pushing a male and female chorus song to the chorusing equipment;

if the ages of the objects to be tested of a certain sex are smaller than or equal to a preset age threshold value, not pushing the chorus songs of the male and the female;

and if the age interval of each object to be detected is larger than a preset age gap, pushing the familiarity golden koji to the ordering equipment.

In a possible implementation manner of the first aspect, determining a recommended song list according to the historical song order list and the recommended song list includes:

determining the priority of the songs in the historical song choosing list according to the song choosing times in the historical song choosing list;

determining the priority of the songs in the recommended song list according to the song choosing times in the recommended song list;

wherein the priority of the songs in the historical song ordering list is higher than the priority of the songs in the recommended song list.

Further, the song recommendation method further comprises the following steps: and displaying the recommended song list in a display interface of the singing ordering device.

In a second aspect, an embodiment of the present application provides a song recommendation system, including:

the acquisition module is used for acquiring a target image;

the extraction module is used for extracting the characteristic information of the object to be detected according to the target image;

and the recommending module is used for determining a recommended song list according to the characteristic information and pushing the recommended song list to the singing ordering device.

In a third aspect, an embodiment of the present application provides a server, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the song recommendation method according to the first aspect when executing the computer program.

In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the song recommendation method according to the first aspect.

In a fifth aspect, an embodiment of the present application provides a computer program product, which, when run on a terminal device, causes the terminal device to execute the song recommendation method according to any one of the first aspect.

It is understood that the beneficial effects of the second aspect to the fifth aspect can be referred to the related description of the first aspect, and are not described herein again.

Compared with the prior art, the embodiment of the application has the advantages that: by acquiring the characteristic information of the user and recommending songs according to the characteristic information of the user, a customized recommended song-ordering interface can be provided according to the characteristics (age, sex and number of people) of the user, the user can conveniently select songs to be ordered, and the problem that the conventional song recommending method cannot provide the customized recommended song-ordering interface for a specific user is effectively solved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

Fig. 1 is a schematic diagram of an application scenario in which a song recommendation method according to an embodiment of the present application is applied;

fig. 2 is a flowchart illustrating a song recommendation method according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a set of display interfaces provided by embodiments of the present application;

fig. 4 is a detailed flowchart of S102 of a song recommendation method according to another embodiment of the present application;

FIG. 5 is a schematic diagram of another set of display interfaces provided by embodiments of the present application;

FIG. 6 is a block diagram of a song recommendation system according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a server according to another embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".

Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.

Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.

The song recommendation method provided by the embodiment of the application can be applied to server equipment, the server can be in communication connection with the ordering equipment, and the ordering equipment can be ordering equipment in a mini KTV box or conventional KTV (e.g. volume format).

Illustratively, the above-mentioned singing equipment may include a tuning control platform, a sound box system, a microphone, a hard disk (for storing a local song), a singing control platform, a display interface, and the like.

Referring to fig. 1, a schematic diagram of an application scenario to which the song recommendation method shown in fig. 1 is applied includes a jukebox device 10, a server 20, and a camera 30. The server 20 may communicate with the chorusing device 10, and the camera 30 may communicate with the server 20.

The camera 30 can take pictures or videos in the box and transmit the acquired target image to the server 20, and the server 20 can extract feature information of an object to be detected (i.e., a user) included in the target image, where the feature information includes, but is not limited to, an age feature, a number of people feature, a gender feature, an identity feature, and the like. It should be noted that one or more objects to be detected may be used. The server 20 determines the user identification information according to the characteristic information of the object to be detected, and obtains the historical song-singing list of the user based on the user identification information. The server can also determine the gender of the user and the age interval of the user according to the characteristic information of the object to be detected, so as to recommend songs with higher song ordering times based on big data as a recommended song list, then combine the historical song ordering list and the recommended song list to generate a recommended song list, and push the recommended song list to the song ordering device 10 of the box, and display the recommended song list recommended based on the characteristic information of the user through the display interface of the song ordering device 10, thereby achieving the purpose of providing a customized recommended song ordering interface for a specific user.

Referring to fig. 2, an embodiment of the present application provides a song recommendation method applied to the server 20, where the song recommendation method includes:

s101: and acquiring a target image.

Specifically, a target image containing an object to be detected is acquired by a camera provided in the box.

Specifically, when a user enters the box, the camera is controlled to collect images of all corners of the whole box, and then the images of all the corners are spliced to obtain a target image, so that the target image is ensured to contain all the objects to be detected.

Specifically, the internal environment of the box is recorded through a camera arranged in the box, an image frame containing all objects to be detected is intercepted from video data obtained through recording, and the image frame is used as a target image.

It should be noted that the number of the objects to be detected may be one or multiple, and is not limited herein. The camera may be a network camera, a 2D visual recognition camera, or other types of cameras, which is not limited herein.

S102: and extracting the characteristic information of the object to be detected according to the target image.

Specifically, the characteristic information of the object to be detected includes, but is not limited to: age characteristics, population characteristics, gender characteristics, identity characteristics, and the like. The age characteristic is used for identifying the age of the objects to be detected, the number characteristic is used for identifying the number of the objects to be detected, the gender characteristic is used for identifying the gender of the objects to be detected, and the identity characteristic is used for detecting and determining user identification information.

Specifically, a trained neural network model is operated in a Python 3.5 operating environment, and a target image is input into the neural network model for processing, so that the feature information (age feature, gender feature and number feature) of each object to be detected in the target image can be automatically output.

Specifically, for the detection of the age characteristic and the people number characteristic, firstly, an image (namely a target image) is cut from a real-time video stream of a network camera by using a cv2 module, then the image is converted into a gray scale image, a Cascade Classifier class of the cv2 module is used for detecting a face in the image and obtaining face coordinates, after the face coordinates are obtained, a face area is cut out, the image comprises several face areas and is the people number characteristic of the image, the cut image must comprise the whole head, then the cut face areas are input into a model, for the age prediction, the output of the model is the probability distribution of 101 values (the age range is from 0 to 100), and the probability of all the 101 values is added to be 1. Therefore, we multiply each age value by its probability and then add up to get the final predicted age.

For the gender characteristics, since gender prediction is a binary task, after a target image is acquired, an image data generator is used for normalizing and randomly rotating a picture, and then a flow _ from _ direction is used for automatically generating a picture label, the output value of a model is between 0 and 1, the higher the output value is, the higher the probability that the face is a male is, and when the output value is higher than 0.5, the label of the face is output as a male.

For the identity features, the identity features are extracted through the model based on 274 feature points, the obtained feature values are compared with feature values of faces in a preset face library, a user corresponding to the face in the face library closest to the feature values of the object to be detected is determined as the object to be detected, user identification information of the user corresponding to the face is obtained, and the user identification information corresponding to the face is determined as the user identification information of the object to be detected.

And respectively acquiring the characteristic information of each object to be detected under the condition that a plurality of objects to be detected exist.

S103: and determining a recommended song list according to the characteristic information, and pushing the recommended song list to a singing ordering device.

Specifically, after the characteristic information of the object to be detected in the box is determined, the recommended song list according with the user characteristic can be determined according to the characteristic information of the object to be detected.

In one embodiment, the step S103 includes the following steps:

Specifically, the user identification information of the user is determined according to the identity characteristics of the object to be detected, and then the historical song-singing-clicking list of the user is determined based on the user identification information, it should be noted that the server establishes the user identification information uniquely corresponding to the user for each user, and the song that the user performs singing at each time enters the historical song-singing-clicking list of the user, so that the song that the user performs sings can be inquired through the server, namely the historical song-singing-clicking list, as long as the user identification information of the object to be detected in the target image is determined.

It should be noted that, the songs in the history song-order list may also be prioritized according to the number of songs ordered in the history song-order list, the song with the highest order of songs may be placed at the head of the priority queue, and the song with the lowest order of songs may be placed at the tail of the priority queue, so as to determine the priority order of each song in the history song-order list.

After the historical song ordering list is obtained, determining the user age interval of the object to be detected according to the age characteristics of the object to be detected, and obtaining the first N songs with the highest song ordering frequency in the user age interval through the server based on the big data platform and adding the first N songs into the recommended song list corresponding to the user age interval.

It should be noted that, priority ordering may also be performed according to the number of singing times of songs in the recommended song list corresponding to the user age interval, a song with the highest number of singing times is placed at the head of the priority queue, and a song with the lowest number of singing times is placed at the tail of the priority queue, so as to determine the priority order of each song in the recommended song list corresponding to the user age interval.

Illustratively, when the age of an object to be detected is 2-6 years, determining the age interval of a user as a child, acquiring a record of the object to be detected for ordering a song of the child in the past, performing priority ordering according to the song ordering times of the song of the child, determining a recommended song list according to big data of the song of the child, performing priority ordering according to the song ordering times, preferentially displaying the song with high priority, wherein the song with high priority can be set to be preferentially displayed in a historical song ordering list, and then displaying the song in the recommended song list; when the age of an object to be detected is 7-12 years old, determining the age interval of a user as a pupil, acquiring the record of songs of the pupil to be detected, performing priority sequencing according to the song singing order, determining the recommended song category according to the big data of the songs of the pupil, performing priority sequencing according to the song singing order, and preferentially displaying the songs with high priority, wherein the song can be set to preferentially display the songs in a historical song singing order list, and then displaying the songs in the recommended song list; when the age of the object to be detected is 13-24, positioning the age interval of the user as a teenager, and determining the recommended song list according to the method; when the age of the user is more than 24, obtaining past song requesting records of the object to be detected according to the identified age of the user, if the age of the user is 40, determining the priority order of songs according to the song requesting times, recommending the 7080 back jinqu, determining the priority order of the songs according to the song requesting times of the 7080 back jinqu in the recommended song list, preferentially displaying the songs with high priority, wherein it needs to be stated that the songs in the historical song requesting list can be preferentially displayed, then the songs in the recommended song list are displayed, the same recommending mode is also adopted for the object to be detected which is 28 years old, and the recommended songs can be 90 back jinqu.

It should be noted that the server may also compare the songs in the history song-order list with the songs in the recommended song list, and delete the repeated songs.

In an embodiment, the determining a recommended song list according to the history song-singing list and the recommended song list corresponding to each user age interval includes the following steps:

In one embodiment, the song recommendation method further includes the following steps:

and displaying the recommended song list in a display interface of the singing ordering device.

Specifically, a recommended song list is determined according to the historical song order list and the recommended song list, and then the recommended song list is pushed to the order equipment for the user to select.

For example, fig. 4 shows a schematic diagram of a singing interface of a singing clicking device provided by the present embodiment, a recommended song list may be displayed in a presentation sub-window, and a user may click a song in the presentation sub-window to select.

The song recommendation method provided by the embodiment can provide a customized recommended song-ordering interface according to the characteristics (age, gender and number) of the user by acquiring the characteristic information of the user and recommending songs according to the characteristic information of the user, so that the user can conveniently select songs to be ordered, and the problem that the conventional song recommendation method cannot provide the customized recommended song-ordering interface for a specific user is effectively solved.

Referring to fig. 3, fig. 3 is a flowchart illustrating an implementation of S102 in a song recommendation method according to another embodiment of the present application. The difference between the present embodiment and the previous embodiment is that when the target image includes a plurality of objects to be detected, S102 of the song updating method provided by the present embodiment includes the following steps, which are detailed as follows:

s201: and determining the user identification information of each object to be detected according to the characteristic information of each object to be detected.

Specifically, when the target image includes a plurality of objects to be detected, feature information of each user to be detected needs to be extracted, and then user identification information of each object to be detected is determined according to the feature information, such as identity features, of each object to be detected.

Specifically, the identity characteristics of the objects to be detected are acquired one by one, and then the user identification information corresponding to the identity characteristics is searched based on the server, so that the user identity characteristics of each object to be detected are determined.

S202: and acquiring a historical song-singing-clicking list according to the user identification information of each object to be detected.

Here, since the history record of each user is recorded in the server, the history song-order list of the user can be acquired by using the user identification information as an index. It should be noted that, for a case where a plurality of objects to be detected exist, the server may respectively obtain the historical song ordering list corresponding to each object to be detected, then separate a plurality of display sub-windows to respectively display the historical song ordering list of each user during display, or may merge the historical song ordering lists of a plurality of users, then perform priority ordering according to the number of times of singing of each song, and perform display only through one display sub-window.

S203: and determining the user age interval of each object to be detected according to the age characteristics of each object to be detected.

Specifically, for a plurality of objects to be detected, the user age interval of each object to be detected is determined according to the age characteristics of each object to be detected. It should be understood that if a plurality of user age intervals of the object to be detected are the same, only the recommended song list corresponding to the user age interval may be obtained.

S204: and acquiring a recommended song list corresponding to each user age area according to the user age interval of each object to be detected.

Specifically, for different user age intervals, corresponding recommended song lists are respectively obtained. For example, if the age interval of the user is children, determining a recommended song list according to the big data of the children songs; determining a recommended song list according to the big data of the schoolchild songs for the pupils in the age interval of the user; determining a recommended song list according to the big data of the teenager songs if the age interval of the user is teenagers; for a user age interval of 40 years, a list of recommended songs is determined according to 7080 postsong.

S205: and determining a recommended song list according to the historical song ordering list and the recommended song list corresponding to each user age interval.

Specifically, the recommended song list is determined according to the priorities of the songs in the historical song ordering list and the priorities of the songs in the recommended song list corresponding to each user age interval.

Illustratively, as shown in fig. 5, the number of presentation sub-windows is determined based on each user age interval, and the recommended song list is presented through a plurality of presentation sub-windows. When the age intervals of the user are identified as children, 90 th and 70 th, the display interface of the singing clicking device can be divided into 3 display sub-interfaces, which are respectively: 7080 post golden koji, 90 post classical and children golden koji. It can be understood that recommended songs of a plurality of user age intervals are only displayed in one display sub-interface, and songs in the past song-ordering records are preferentially displayed by acquiring the past song-ordering records of the users. And then, songs which are in accordance with the three user age intervals and counted by the big data can be sorted according to the song singing times.

It should be noted that the track threshold of the recommended song list may be set, for example, the recommended song list may be set to include one hundred songs.

In an embodiment, the step S102 further includes the following steps:

Specifically, whether the sexes of a plurality of objects to be detected of the target image are the same or not is determined through the gender characteristics, if so, whether the plurality of objects to be detected are males or females is judged, songs with brother and deep emotion are recommended for males, and songs with sister and long emotion are recommended for females.

In one embodiment, the step S102 further includes the following steps:

Specifically, if there are male and female subjects to be detected (i.e., the sex of the plurality of subjects to be detected is different), and there are male subjects whose ages are greater than the preset age threshold and female subjects whose ages are greater than the preset age threshold, the male and female chorus songs are directly pushed to the user. If the ages of the objects to be detected of a certain sex are all smaller than or equal to a preset age threshold (for example, 12 years old), the male and female chorus songs are not pushed. For example, if 4 persons (objects to be detected) in the box are detected, wherein the 4 persons include a female a with the age of 27 years, a female B with the age of 12 years, a female C with the age of 30 years and a male D with the age of 28 years, and the preset age threshold is 12 years, the server pushes a male and female chorus song to the singing device at the moment; if the 4 objects to be detected comprise a female A with the age of 27 years, a female B with the age of 12 years, a male C with the age of 7 years and a male D with the age of 6 years, the server does not push a male and female chorus song to the singing ordering device at the moment.

If the age interval of the object to be detected is larger than the preset age gap (for example, 20 years), the object to be detected is indicated to be possibly in a paternity relationship, and the paternity song of the thanksgiving parents is recommended. It should be noted that the gender of the older object to be detected can be further detected, and if the older object is a woman, the song of the thanksgiving mother is pushed; if the song is male, the song of the father of Thanksgiving is pushed. It should be noted that the preset age threshold and the preset age gap may be set according to actual situations, and are not limited herein.

Fig. 6 shows a block diagram of a song recommendation system provided in an embodiment of the present application, which corresponds to the song recommendation method described in the above embodiment, and only shows portions related to the embodiment of the present application for convenience of explanation.

Referring to fig. 6, the song recommendation system includes an acquisition module 101, an extraction module 102, and a recommendation module 103.

The acquisition module 101 is used for acquiring a target image;

the extraction module 102 is configured to extract feature information of an object to be detected according to the target image;

the recommending module 103 is configured to determine a recommended song list according to the feature information, and push the recommended song list to a singing requesting device.

Optionally, the recommending module includes an information determining unit, a history list acquiring unit, a recommended song acquiring unit, and a recommended song list determining unit.

The information determining unit is used for determining user identification information and a user age interval according to the characteristic information;

the history list acquiring unit is used for acquiring a history song order list according to the user identification information;

the recommended song acquiring unit is configured to acquire a recommended song list corresponding to the user age interval according to the user age interval;

the recommended song list determining unit is used for determining the recommended song list according to the historical song order list and the recommended song list.

Optionally, the information determining unit is further configured to determine user identification information of each object to be detected according to the feature information of each object to be detected;

the history list acquisition unit is further used for acquiring a history song-singing-clicking list according to the user identification information of each object to be detected.

The information determining unit is further configured to determine the user age interval of each object to be detected according to the age characteristics of each object to be detected.

The recommended song obtaining unit is further configured to obtain a recommended song list corresponding to each user age area according to the user age interval of each object to be detected.

The recommended song list determining unit is further used for determining the recommended song list according to the historical song order list and the recommended song lists corresponding to the age intervals of the users.

Optionally, the recommending module further includes a gender detecting unit, a gender singing list recommending unit, a number of people detecting unit, a judging unit, and a chorus pushing unit.

The gender detection unit is used for detecting whether the genders of the plurality of objects to be detected are the same;

the gender song list recommending unit is used for determining a recommended song list according to gender characteristics if the genders of the objects to be detected are the same;

the number of people detecting unit is used for detecting the ages of the objects to be detected with different sexes if the sexes of the objects to be detected are different;

the chorus pushing unit is used for pushing a male chorus song and a female chorus song to the chorus equipment if the ages of the objects to be detected with different sexes are larger than a preset age threshold value;

the age detection unit is used for not pushing the chorus songs of the male and the female if the ages of the objects to be detected of a certain sex are smaller than or equal to a preset age threshold value;

and the age gap detection unit is used for pushing the familiarity golden koji to the singing ordering equipment if the age interval of each object to be detected is greater than a preset age gap.

Optionally, the pushed song list determining unit further includes a first priority unit and a second priority unit.

The first priority unit is used for determining the priority of the songs in the historical song choosing list according to the song choosing times in the historical song choosing list;

the second priority unit is used for determining the priority of the songs in the recommended song list according to the song singing times in the recommended song list; wherein the priority of the songs in the historical song ordering list is higher than the priority of the songs in the recommended song list.

Optionally, the song recommendation system further comprises a display module.

And the display module is used for displaying the recommended song list in a display interface of the singing ordering device.

It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

Therefore, the song recommendation system provided by the embodiment can also provide a customized song recommendation interface according to the characteristics (age, gender and number) of the user by acquiring the characteristic information of the user and recommending songs according to the characteristic information of the user, so that the user can conveniently select songs to be sung, and the problem that the conventional song recommendation method cannot provide the customized song recommendation interface for a specific user is effectively solved.

Fig. 7 is a schematic structural diagram of a server according to an embodiment of the present application. As shown in fig. 7, the server 7 of this embodiment includes: at least one processor 70 (only one shown in fig. 7), a memory 71, and a computer program 72 stored in the memory 71 and executable on the at least one processor 70, the processor 70 implementing the steps in any of the various song update method embodiments described above when executing the computer program 72.

The server 7 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The server may include, but is not limited to, a processor 70, a memory 71. Those skilled in the art will appreciate that fig. 7 is merely an example of the server 7, and does not constitute a limitation of the server 7, and may include more or less components than those shown, or combine certain components, or different components, such as input output devices, network access devices, etc.

The Processor 70 may be a Central Processing Unit (CPU), and the Processor 70 may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 71 may in some embodiments be an internal storage unit of the server 7, such as a hard disk or a memory of the server 7. The memory 71 may also be an external storage device of the server 7 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the server 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the server 7. The memory 71 is used for storing an operating system, an application program, a Boot Loader (Boot Loader), data, and other programs, such as program codes of the computer programs. The memory 71 may also be used to temporarily store data that has been output or is to be output.

Illustratively, the computer program 72 may be divided into one or more units, which are stored in the memory 71 and executed by the processor 70 to accomplish the present application. The one or more units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 72 in the server 7. For example, the computer program 72 may be divided into an acquisition module, an extraction module, and a recommendation module, each module having the following specific functions:

the acquisition module is used for acquiring a target image;

The list determining module is used for acquiring a first push song list and determining a missing song list according to the first push song list, wherein the first push song list is generated by the server according to a server song list;

the song determining module is used for determining songs to be downloaded according to the missing song list and the residual flow;

the request module is used for generating a downloading request according to the song to be downloaded and uploading the downloading request to a server, and the downloading request is used for indicating the server to generate a downloading task according to the downloading request;

and the downloading module is used for acquiring the downloading task and downloading the songs according to the downloading task.

An embodiment of the present application further provides a network device, where the network device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, the processor implementing the steps of any of the various method embodiments described above when executing the computer program.

The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps in the above-mentioned method embodiments.

The embodiments of the present application provide a computer program product, which when running on a mobile terminal, enables the mobile terminal to implement the steps in the above method embodiments when executed.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/server, a recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims

1. A song recommendation method, comprising:

acquiring a target image;

2. The song recommendation method of claim 1, wherein the determining a recommended song list according to the characteristic information and pushing the recommended song list to a singing ordering device comprises:

3. The song recommendation method of claim 1, wherein when the target image contains a plurality of objects to be detected, the determining a recommended song list according to the user characteristics and pushing the recommended song list to a singing ordering device comprises:

4. The song recommendation method of claim 3, further comprising:

5. The song recommendation method of claim 4, further comprising:

6. The song recommendation method of claim 2, wherein determining a recommended song list based on the historical ordered song list and the recommended song list comprises:

7. The song recommendation method according to any one of claims 1 to 6, further comprising:

8. A song recommendation system, comprising:

the acquisition module is used for acquiring a target image;

9. A server comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the song update method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out a song update method according to any one of claims 1 to 7.