Music recommendation via camera system

Abstract

A system includes one or more hardware processors and at least one memory storing instructions that cause the one or more hardware processors to perform operations that include receiving, via a client device, a selection of a photographic filter or a virtual lens. The operations additionally include deriving a music recommendation, a sound recommendation, or a combination thereof for the selection of the photographic filter or the virtual lens via the model, the date, or a combination thereof, and providing the music recommendation, the sound recommendation, or a combination thereof to the client device.

Description

[0001] Priority Claim

[0002] This patent application claims the benefit of priority to U.S. Application No. 63 / 386,916, filed on December 11, 2022, which is hereby incorporated by reference in its entirety. Background Art

[0003] Camera device systems (such as camera devices provided on mobile devices) can capture various electronic images and videos. Image and video capture are becoming increasingly popular. Users increasingly share media content items such as electronic images and videos with each other. Users also increasingly use their mobile devices to communicate with each other using messaging programs. For example, a user can create media content and share it via a messaging program.

[0004] Brief Description of the Several Views of the Drawings

[0005] In the drawings (which are not necessarily drawn to scale), like reference numerals may describe similar components in different views. To easily identify the discussion of any particular element or action, one or more of the most significant digits in the reference numeral refer to the figure number in which the element was first introduced. Some non-limiting examples are shown in the figures of the drawings, in which: Description of the Drawings

[0006] Figure 1 is a graphical representation of a networked environment in which the present disclosure may be deployed, according to some examples.

[0007] Figure 2 is a graphical representation of a messaging system having both client-side and server-side functionality, according to some examples.

[0008] Figure 3 is a graphical representation of a data structure maintained in a database, according to some examples.

[0009] Figure 4 is a graphical representation of a message, according to some examples.

[0010] Figure 5 illustrates a system of a head wearable device, according to some examples.

[0011] Figure 6 illustrates a process for music and sound recommendations for providing suggestions for photographic filters and visual lenses, according to some examples.

[0012] Figure 7 illustrates a machine learning engine for creating and training a machine learning (ML) model, according to some examples.

[0013] Figure 8Music and sound recommendations for photographic filters and visual lenses based on some examples.

[0014] Figure 9 Is a screenshot of the display of a client device based on some examples.

[0015] Figure 10 Is a graphical representation of a machine in the form of a computer system within which a set of instructions can be executed to cause the machine to perform any one or more of the methods discussed herein.

[0016] Figure 11 Is a block diagram showing a software architecture in which examples may be implemented. Detailed Description

[0017] Camera device systems are included in various devices such as mobile devices, smartwatches, drones, etc. The camera device system enables a user to capture images and videos and is communicatively and / or operably coupled to certain applications such as messaging applications. In some examples, the messaging application enables the user to apply photographic filters and / or virtual lenses to transform images and / or videos with media overlays, augmented reality (AR) content, and / or virtual reality (VR) content. An AR experience includes applying virtual content to a real-world environment, either by presenting virtual content through a transparent display through which the real-world environment can be seen or by enhancing image data to include virtual content superimposed on the real-world environment depicted therein. A VR experience is also provided, where a fully simulated or virtual view of the world is presented through a display device. For example, when taking a selfie photo or video, the user selects a filter or virtual lens from a "dial" with options for photographic filters and virtual lenses. The messaging application then displays certain media overlays, AR content, and / or VR content based on the selected photographic filter or virtual lens, thereby adding or modifying the user's image or video.

[0018] As used herein, a photographic filter provides an image overlay, including a static overlay. For example, a user can take a photo of the Eiffel Tower and overlay a geographical location tag, such as text indicating the country (e.g., France) and the French flag. A virtual lens can provide AR content overlaid on the real world. For example, a user can take a selfie video, and the virtual lens can apply virtual cat ears overlaid on the user's head. The virtual lens can also provide the display of an avatar in both AR and VR examples. For example, the user's avatar can be displayed as dancing overlaid on the video capture of the current imaging device, such as the avatar dancing on the user's table. Both photographic filters and virtual lenses use an imaging device system to capture an image and transform the image via the added overlay and / or image transformation (e.g., aging the user's face).

[0019] The techniques described herein provide improved content creation and viewing by automatically recommending music and sounds to media content generated via a photographic filter and / or a virtual lens based on a selected filter or virtual lens and one or more contexts and, in some embodiments, automatically adding music and sounds. The context can include machine learning model context, date / time context, media interrelationship context, and other model contexts. For example, certain machine learning (ML) models are trained and continuously updated to identify the correlation (e.g., a correlation metric) between a selected filter or virtual lens and the sounds being used to create or present the media content generated by the selected filter or virtual lens.

[0020] In an example of an ML context, members of a social group (e.g., a group of friends) create media content by adding certain specific sounds (e.g., a song or a playlist) to media content generated by a cat ear filter. The ML model detects an increase in the use of the same song with the cat ear filter and presents the same song when the user selects the cat ear filter. The ML model can additionally detect that user A prefers content X more than user B and can further customize recommendations based on user tastes. In some date / time context examples, certain dates and / or times are used to present a selection of sounds when a selected filter or virtual lens is used. For example, various dog-related songs, such as "Who Let the Dogs Out", are presented to certain filters during National Puppy Day. Similarly, a selection of holiday music is presented within certain data ranges around holidays. In some media correlation context examples, a correlation between media content and sounds is used. For example, when a superhero filter (e.g., Batman) is used, sounds or music associated with the superhero (e.g., the Dark Knight soundtrack) are presented. Similarly, when a dancing rapper avatar created via a virtual lens is used, music associated with the rapper is presented. In other model contexts, non-ML models (such as heuristic (e.g., probabilistic) models, linear regression models, etc.) can be used to predict the popular relationship between filters / virtual lenses and certain music. By obtaining the relationship between sounds and filters / virtual lenses in the above context, the techniques described herein provide a more efficient and engaging presentation of media content.

[0021] Networked computing environment

[0022] It may be beneficial to describe certain systems that implement the techniques described herein. Turning now to Figure 1 , the figure is a block diagram illustrating an example interaction system 100 for facilitating interactions over a network (e.g., exchanging text messages, making text, audio, and video calls, creating media content, or playing games). The interaction system 100 includes a plurality of client systems 102, each of which hosts a plurality of applications including an interaction client 104 and other applications 106. Each interaction client 104 is communicatively coupled via one or more communication networks including a network 108 (e.g., the Internet) to other instances of the interaction client 104 (e.g., hosted on corresponding other user systems 102), an interaction server system 110, and a third-party server 112). The interaction client 104 can also communicate with the locally hosted applications 106 using an application programming interface (API).

[0023] Each user system 102 may include a plurality of user devices, such as mobile devices 114, head-worn devices 116, drones 118, and computer client devices 120, which are communicatively connected to exchange data and messages. The interaction client 104 interacts via the network 108 with other interaction clients 104 and with the interaction server system 110. Data exchanged between interaction clients 104 (e.g., interaction 122) and between the interaction client 104 and the interaction server system 110 includes functionality (e.g., commands for activating functionality) and payload data (e.g., text, audio, video, or other multimedia data).

[0024] The interaction server system 110 provides server-side functionality to the interaction client 104 via the network 108. While certain functions of the interaction system 100 are described herein as being performed by the interaction client 104 or by the interaction server system 110, the location of certain functions within the interaction client 104 or within the interaction server system 110 can be a design choice. For example, it may be technically preferable to initially deploy a particular technology and functionality within the interaction server system 110, but later migrate the technology and functionality to the interaction client 104 where the user system 102 has sufficient processing power.

[0025] The interaction server system 110 supports various services and operations provided to the interaction client 104. Such operations include sending data to the interaction client 104, receiving data from the interaction client 104, and processing data generated by the interaction client 104. The data may include message content, client device information, geographical location information, media enhancements and overlays, message content persistence conditions, social network information, and live event information. Data exchange within the interaction system 100 is activated and controlled by functions available via the user interface (UI) of the interaction client 104.

[0026] Now turning specifically to the interaction server system 110, the application programming interface (API) server 124 is coupled to the interaction server 126 and provides it with a programming interface, making the functions of the interaction server 126 accessible to the interaction client 104, other applications 106, and the third-party server 112. The interaction server 126 is communicatively coupled to the database server 128, thereby facilitating access to the database 130, which stores data associated with the interactions processed by the interaction server 126. Similarly, the web server 132 is coupled to the interaction server 126 and provides a web-based interface to the interaction server 126. To this end, the web server 132 processes incoming network requests via the Hypertext Transfer Protocol (HTTP), remote procedure calls (RPC), and several other related protocols.

[0027] The application programming interface (API) server 124 receives and sends interaction data (e.g., commands and message payloads) between the interaction server 126 and the client system 102 (and, for example, the interaction client 104 and other applications 106) as well as the third-party server 112. Specifically, the application programming interface (API) server 124 provides a set of interfaces (e.g., routines and protocols) that the interaction client 104 and other applications 106 can call or query to activate the functions of the interaction server 126. The application programming interface (API) server 124 exposes various functions supported by the interaction server 126, including account registration; login functionality; sending interaction data from a specific interaction client 104 to another interaction client 104 via the interaction server 126; transmitting media files (e.g., images or videos) from the interaction client 104 to the interaction server 126; setting a collection of media data (e.g., a story); retrieving a friend list of the user of the user system 102; retrieving messages and content; adding and deleting entities (e.g., friends) to / from an entity graph (e.g., a social graph); locating friends within the entity graph; and opening an application event (e.g., related to the interaction client 104).

[0028] Application 106 includes a sound (e.g., music) recommendation system 134, which may also be included on one or more servers, that can recommend certain sounds based on a user selecting a photographic filter or virtual lens. For example, application 106 may provide graphical user interface (GUI) controls such as a "turntable" or other controls (e.g., mouse controls, touch controls) that display icons or text representing photographic filters and virtual lenses. The icons are overlaid on the view of the imaging device (e.g., showing a selfie). The user can swipe to display additional icons. When an icon is selected, the sound recommendation system 134 then uses machine learning (ML) context, date / time context, media interrelationship context, and / or other model contexts to recommend sounds for the photographic filter / virtual lens selected by the user. In some examples, the ML context, date / time context, media interrelationship context, and other model contexts may be used individually or in combination. In some examples, the recommendations for each photographic filter or virtual lens have been preprocessed via the ML context, date / time context, media interrelationship context, and other model contexts. That is, the ML context, date / time context, media interrelationship context, and other model contexts may be used before the user selects a photographic filter or virtual lens to match the photographic filter or virtual lens with music and / or other sounds and have recommendations ready. For example, a daemon job or similar process may be used to execute the ML context, date / time context, media interrelationship context, and other model contexts every minute, hour, day, week, or a combination thereof to have recommendations ready for presentation when the user selects a photographic filter or virtual lens.

[0029] In some examples, the ML context will provide current data, such as "friend" data, geographical location data, and / or social network data, to the trained ML model, and the ML model will then output a recommendation for a sound to match the selected photographic filter / virtual lens. Similarly, other model contexts will provide similar or the same data used by the ML model, such as "friend" data, geographical location data, and / or social network data, to non-ML models (such as heuristic models, linear regression analysis models, etc.), and the non-ML models will then output a recommendation for a sound to match the selected photographic filter / virtual lens. In the date / time context, one or more date / time queries are executed via the database server 128 to obtain one or more sounds recommended for the selected photographic filter / virtual lens. In the media correlation context, one or more media correlation queries are executed via the database server 128 to obtain one or more sounds recommended for the selected photographic filter / virtual lens. As previously mentioned, the recommendations from the contexts can be combined and additionally used to discover which recommendation is "the best". The recommended sounds can then be incorporated into certain messages, such as the "story" that the user is creating via the camera device system. Then, for example, via the interaction server 126, the story with the recommended sounds and media overlays is distributed to other user systems 102. The interaction server 126 hosts multiple systems and subsystems, including the server-side sound recommendation system, as described in more detail below with reference to Figure 2 described in more detail.

[0030] System architecture

[0031] Figure 2 is a block diagram showing additional details regarding the interaction system 100 according to some examples. Specifically, the interaction system 100 is shown to include an interaction client 104 and an interaction server 126. The interaction system 100 includes multiple subsystems that are supported on the client side by the interaction client 104 and on the server side by the interaction server 126. The exemplary subsystems are discussed below.

[0032] The image processing system 202 provides various functions that enable the user to capture media content associated with a message and enhance it (e.g., annotate or otherwise modify or edit) using the media content captured via the camera device system 204. The camera device system 204 includes control software (e.g., in the camera device application) that interacts with and controls the hardware camera device of the user system 102 (e.g., directly or via operating system controls) to modify and enhance the real-time images captured and displayed via the interaction client 104.

[0033] The enhancement system 206 provides functionality related to generating and publishing enhancements (e.g., media overlays) for images captured in real time by the imaging device of the user system 102 or retrieved from the memory of the user system 102. For example, the enhancement system 206 operably selects (e.g., via a photographic filter or virtual lens creation) a media overlay, presents and displays it to the interactive client 104 for enhancing a real-time image received via the imaging device system 204 or a stored image retrieved from the memory 502 of the user system 102. These enhancements are selected by the enhancement system 206 based on a plurality of inputs and data, such as:

[0034] · The geographical location of the user system 102; and

[0035] · The social network information of the user of the user system 102.

[0036] Enhancements can include audio and visual content as well as visual effects. Examples of audio and visual content include pictures, text, logos, animations, and sound effects. Examples of visual effects include color overlays. The audio and visual content or visual effects can be applied at the user system 102 to a media content item (e.g., a photo or video) for transmission in a message, or to video content such as a video content stream or feed sent from the interactive client 104. As such, the image processing system 202 can interact with and support various subsystems of the communication system 208, such as the messaging system 210 and the video communication system 212.

[0037] The media overlay can include text or image data that can be superimposed over a photo taken by the user system 102 or a video stream produced by the user system 102. In some examples, the media overlay can be a location overlay (e.g., Venice Beach), the name of a live event, or a business name overlay (e.g., Beach Café). In additional examples, the image processing system 202 uses the geographical location of the user system 102 to identify a media overlay that includes the name of a business at the geographical location of the user system 102. The media overlay can include other markers associated with the business. The media overlay can be stored in the database 130 and retrieved via the database server 128.

[0038] The image processing system 202 provides a user-based publishing platform that enables a user to select a geographical location on a map and upload content associated with the selected geographical location. The user can also specify the circumstances under which a particular media overlay should be provided to other users. The image processing system 202 generates a media overlay that includes the uploaded content and associates the uploaded content with the selected geographical location.

[0039] The augmented creation system 214 supports an augmented reality developer platform and includes applications for content creators (e.g., artists and developers) to create and publish enhanced (e.g., augmented reality experiences) interactive clients 104. The augmented creation system 214 provides content creators with a library of built-in features and tools, including, for example, custom shaders, tracking techniques, and templates.

[0040] In some examples, the augmented creation system 214 provides a merchant-based publishing platform that enables merchants to select specific augmentations associated with a geographical location via a bidding process. For example, the augmented creation system 214 associates the media overlay of the highest-bidding merchant with the corresponding geographical location for a predefined amount of time.

[0041] The communication system 208 is responsible for enabling and handling various forms of communication and interaction within the interactive system 100 and includes a messaging system 210, an audio communication system 216, and a video communication system 212. The messaging system 210 is responsible for enforcing temporary or time-limited access to content by the interactive client 104. The messaging system 210 includes multiple timers (e.g., within the short-lived timer system 218) that selectively enable access (e.g., for rendering and display) to messages and associated content via the interactive client 104 based on the duration and display parameters associated with the message or a collection of messages (e.g., a story). Additional details regarding the operation of the short-lived timer system 218 are provided below. The audio communication system 216 enables and supports audio communication (e.g., real-time audio chat) between multiple interactive clients 104. Similarly, the video communication system 212 enables and supports video communication (e.g., real-time video chat) between multiple interactive clients 104.

[0042] The user management system 220 is operationally responsible for managing user data and profiles and includes a social networking system 222 that maintains information regarding the relationships between users of the interactive system 100.

[0043] The collection management system 224 is operationally responsible for managing collections or sets of media (e.g., collections of text, image, video, and audio data). Collections of content (e.g., messages, including images, videos, text, and audio) can be organized into an "event library" or "event story". Such collections can be made available for a specified period of time, such as during the duration of an event related to the content. For example, content related to a concert can be made available as a "story" during the duration of that concert. The collection management system 224 can also be responsible for publishing an icon that provides a notification of a particular collection to the user interface of the interactive client 104. The collection management system 224 includes a curation function that enables a collection manager to manage and curate a particular content collection. For example, the curation interface enables an event organizer to curate a collection of content related to a particular event (e.g., delete inappropriate content or redundant messages). Additionally, the collection management system 224 employs machine vision (or image recognition technology) and content rules to automatically curate content collections. In some examples, compensation can be paid to users for including user-generated content in a collection. In such cases, the collection management system 224 operates to automatically pay such users for the use of their content.

[0044] The map system 226 provides various geolocation functions and supports the rendering of map-based media content and messages by the interactive client 104. For example, the map system 226 enables the display on a map of user icons or avatars (e.g., stored in the profile data 304) to indicate the current or past locations of a user's "friends" within the context of the map, as well as media content (e.g., a collection of messages including photos and videos) generated by such friends. For example, a message posted by a user from a particular geographic location to the interactive system 100 can be displayed to the "friends" of that particular user within the context of that particular location on the map in the map interface of the interactive client 104. A user can also share his or her location and status information with other users of the interactive system 100 via the interactive client 104 (e.g., using an appropriate status avatar), where such location and status information is similarly displayed to the selected users within the context of the map interface of the interactive client 104.

[0045] The external resource system 228 provides an interface for the interaction client 104 to communicate with a remote server (e.g., a third-party server 112) to initiate or access external resources (i.e., applications or applets). Each third-party server 112 hosts an application or a scaled-down version of an application (e.g., a game application, a utility application, a payment application, or a ride-sharing application) based on a markup language (e.g., HTML5), for example. The interaction client 104 can initiate a web-based resource (e.g., an application) by accessing an HTML5 file from a third-party server 112 associated with the web-based resource. The applications hosted by the third-party server 112 are programmed in JavaScript using a software development kit (SDK) provided by the interaction server 126. The SDK includes application programming interfaces (APIs) having functions that can be called or activated by web-based applications. The interaction server 126 hosts a JavaScript library that provides access to given external resources for specific user data of the interaction client 104. HTML5 is an example of a technology used to program games, but applications and resources programmed based on other technologies can be used.

[0046] As described above, the music recommendation system 134 provides sound (e.g., music) recommendations via various contexts. For example, the ML context will provide current data, such as "friend" data, geographical location data, and / or social network data, to a trained ML model, and the ML model will then output a recommendation for sound to match the selected photographic filter / virtual lens. Similarly, other model contexts will provide similar or the same data used by the ML model, such as "friend" data, geographical location data, and / or social network data, to non-ML models (such as heuristics (e.g., probability models), linear regression analysis models, etc.), and the non-ML models will then output a recommendation for sound to match the selected photographic filter / virtual lens. In the date / time context, one or more date / time queries are executed via the database server 128 to obtain one or more sounds recommended for the selected photographic filter / virtual lens. In the media correlation context, one or more media correlation queries are executed via the database server 128 to obtain one or more sounds recommended for the selected photographic filter / virtual lens.

[0047] The recommended sounds can then be incorporated into certain messages, such as a "story" that the user is creating via the camera device system 204. In some examples, the music recommendation system 134 is included within the augmentation system 206 or is operatively coupled to the augmentation system 206. Thus, when the user selects a photographic filter / virtual lens to use via the augmentation system 206, the augmentation system 206 presents the recommended sounds / music. In some examples, the music recommendation system 134 is additionally or alternatively included within or operatively coupled to the augmentation creation system 214. Thus, content creators (e.g., artists and developers) can use sound recommendation contexts (e.g., ML models, non-ML models, date / time recommendation queries, media correlation recommendation queries) via an API and / or object calls to create and publish augmentations (e.g., augmented reality experiences) that can incorporate sound recommendations.

[0048] To integrate the functionality of the SDK into a web-based resource, the SDK is downloaded from the interaction server 126 by the third-party server 112 or is otherwise received by the third-party server 112. Once downloaded or received, the SDK is included as part of the application code of the web-based external resource. The code of the web-based resource can then call or activate certain functions of the SDK to integrate the features of the interaction client 104 into the web-based resource.

[0049] The SDK stored on the interaction server system 110 effectively provides a bridge between an external resource (e.g., app 106 or applet) and the interaction client 104. This gives the user a seamless experience of communicating with other users on the interaction client 104 while also preserving the look and feel of the interaction client 104. To bridge the communication between the external resource and the interaction client 104, the SDK facilitates communication between the third-party server 112 and the interaction client 104. The WebView JavaScript Bridge running on the user system 102 establishes two one-way communication channels between the external resource and the interaction client 104. Messages are sent asynchronously between the external resource and the interaction client 104 via these communication channels. Each SDK function activation is sent as a message and a callback. Each SDK function is implemented by constructing a unique callback identifier and sending a message with that callback identifier.

[0050] By using the SDK, not all information from the interaction client 104 is shared with the third-party server 112. The SDK restricts which information is shared based on the requirements of the external resources. Each third-party server 112 provides an HTML5 file corresponding to the web-based external resource to the interaction server 126. The interaction server 126 can add a visual representation (such as a box design or other graphics) of the web-based external resource in the interaction client 104. Once the user selects the visual representation through the GUI of the interaction client 104 or instructs the interaction client 104 to access the features of the web-based external resource, the interaction client 104 obtains the HTML5 file and instantiates the resources for accessing the features of the web-based external resource.

[0051] The interaction client 104 presents a graphical user interface for the external resource (e.g., a landing page or a splash screen). During, before, or after presenting the landing page or splash screen, the interaction client 104 determines whether the launched external resource has been previously authorized to access the user data of the interaction client 104. In response to determining that the launched external resource has been previously authorized to access the user data of the interaction client 104, the interaction client 104 presents another graphical user interface of the external resource that includes the functions and features of the external resource. In response to determining that the launched external resource has not been previously authorized to access the user data of the interaction client 104, after a threshold period (e.g., 3 seconds) of displaying the login page or splash screen of the external resource, the interaction client 104 slides up a menu (e.g., animates the menu to emerge from the bottom of the screen to the middle or other part of the screen) for authorizing the external resource to access the user data. The menu identifies the types of user data that the external resource will be authorized to use. In response to receiving a user selection of the accept option, the interaction client 104 adds the external resource to the list of authorized external resources and allows the external resource to access the user data from the interaction client 104. The external resource is authorized by the interaction client 104 to access the user data under the OAuth 2 framework.

[0052] The interactive client 104 controls the type of user data shared with an external resource based on the type of the authorized external resource. For example, access to a first type of user data (e.g., a two-dimensional avatar of a user with or without different avatar characteristics) is provided to an external resource including a full-scale application (e.g., application 106). As another example, access to a second type of user data (e.g., payment information, a two-dimensional avatar of the user, a three-dimensional avatar of the user, and avatars with various avatar characteristics) is provided to an external resource including a small-scale version of the application (e.g., a web-based version of the application). Avatar characteristics include different ways of customizing the appearance and feel of the avatar (such as different poses, facial features, clothing, etc.). The advertising system 230 operates to enable third parties to purchase advertisements for presentation to end users via the interactive client 104 and also processes the delivery and presentation of these advertisements.

[0053] Data architecture

[0054] Figure 3 is a schematic diagram showing a data structure 300 that can be stored in the database 302 of the interactive server system 300 according to some examples. Although the contents of the database 302 are shown as including multiple tables, it will be appreciated that the data can be stored in other types of data structures (e.g., an object-oriented database).

[0055] The database 302 includes message data stored within a message table 306. For any particular message, this message data includes at least message sender data, message recipient (or receiver) data, and a payload. Additional details regarding information that can be included in a message and that is included within the message data stored in the message table 306 are described below with reference to Figure 3 Describe additional details about the information that can be included in a message and that is included within the message data stored in the message table 306.

[0056] The entity table 308 stores entity data and is linked (e.g., in a reference manner) to an entity graph 310 and profile data 304. Entities whose records are maintained within the entity table 308 can include individuals, corporate entities, organizations, objects, locations, events, etc. Regardless of the entity type, any entity for which the interactive server system 110 stores data about it can be an identified entity. Each entity is set with a unique identifier and an entity type identifier (not shown).

[0057] The entity graph 310 stores information about the relationships and associations between entities. By way of example only, such relationships can be social, professional (e.g., working in a common company or organization), interest-based, or activity-based. Some relationships between entities can be one-way, such as a personal user's subscription to digital content of a business or publishing user (e.g., a newspaper or other digital media organization or brand). Other relationships can be two-way, such as a "friend" relationship between individual users of the interaction system 100.

[0058] Certain permissions and relationships can be attached to each relationship and also to each direction of the relationship. For example, a two-way relationship (e.g., a friend relationship between individual users) can include authorization for the publication of digital content items between the individual users, but certain restrictions or filters can be imposed on the publication of these digital content items (e.g., based on content characteristics, location data, or time-of-day data). Similarly, the subscription relationship between a personal user and a business user can impose different degrees of restrictions on the publication of digital content from the business user to the personal user and can significantly restrict or prevent the publication of digital content from the personal user to the business user. A particular user, as an example of an entity, can record certain restrictions (e.g., in the form of privacy settings) in the record for that entity within the entity table 308. Such privacy settings can be applied to all types of relationships within the context of the interaction system 100 or can be selectively applied to certain types of relationships.

[0059] The profile data 304 stores various types of profile data about a particular entity. Based on the privacy settings specified by the particular entity, the profile data 304 can be selectively used and presented to other users of the interaction system 100. In the case where the entity is a person, the profile data 304 includes, for example, a username, a phone number, an address, settings (e.g., notification and privacy settings), and an avatar representation (or a set of such avatar representations) selected by the user. Then, a particular user can selectively include one or more of these avatar representations in the content of messages transmitted via the interaction system 100 and on a map interface displayed by the interaction client 104 to other users. The set of avatar representations can include "status avatars" that present graphical representations of states or activities that the user can select to communicate at a particular time.

[0060] In the case where the entity is a group, in addition to the group name, members, and various settings for the relevant group (e.g., notifications), the profile data 304 for the group can similarly include one or more avatar representations associated with the group. The database 302 also stores enhancement data, such as overlays or filters, in the enhancement table 312. The enhancement data is associated with videos (the data of which is stored in the video table 314) and images (the data of which is stored in the image table 316) and is applied to the videos and images.

[0061] In some examples, filters are overlays that are displayed as being superimposed on an image or video during presentation to the receiving user. Filters can be of various types, including a filter selected by the user from a set of filters presented to the sending user by the interaction client 104 when the sending user is composing a message. Other types of filters include location-based filters (also known as geo-filters), which can be presented to the sending user based on a geographical location. For example, based on geographical location information determined by the global positioning system (GPS) unit of the user system 102, the interaction client 104 can present location-based filters specific to a nearby or special location within the user interface.

[0062] Another type of filter is a data filter, which can be selectively presented to the sending user by the interaction client 104 based on other input or information collected by the user system 102 during the message creation process. Examples of data filters include the current temperature at a specific location, the current speed at which the sending user is traveling, the battery life of the user system 102, or the current time.

[0063] Other enhancement data that can be stored in the image table 316 includes augmented reality content items (e.g., corresponding to an applied lens or augmented reality experience). Augmented reality content items can be real-time special effects and / or sounds that can be added to an image or video.

[0064] The story table 318 stores data about a collection of messages and associated image, video, or audio data, which are compiled into a collection (e.g., a story or gallery). The creation of a specific collection can be initiated by a specific user (e.g., each user whose record is maintained in the entity table 308). A user can create a "personal story" in the form of a collection of content that has already been created and sent / broadcast by that user. To this end, the user interface of the interaction client 104 can include user-selectable icons to enable the sending user to add specific content to his or her personal story.

[0065] The collection can also form a "Live Story" that is a collection of content from multiple users, which is created manually, automatically, or using a combination of manual and automatic techniques. For example, a "Live Story" can form a curated stream of user-submitted content from various locations and events. Users whose client devices have location services enabled and are at a common location event at a particular time can be presented, for example, via the user interface of the interactive client 104, with the option to contribute content to a particular Live Story. The interactive client 104 can identify the Live Story to him or her based on the user's location. The end result is a "Live Story" told from a community perspective.

[0066] Another type of content collection is called a "Location Story" that enables users whose user system 102 is located within a particular geographical location (e.g., on a college or university campus) to contribute to a particular collection. In some examples, contributions to a Location Story can use secondary authentication to verify that the end user belongs to a particular organization or other entity (e.g., is a student on a university campus).

[0067] As mentioned above, the video table 314 stores video data that, in some examples, is associated with messages whose records are maintained in the message table 306. Similarly, the image table 316 stores image data associated with messages whose message data is stored in the entity table 308. The entity table 308 can associate various enhancements from the enhancement table 312 with the various images and videos stored in the image table 316 and the video table 314.

[0068] The database 302 also includes a music / sound table 320 that stores licensed music and other sounds. Music can include vocal and / or instrumental songs, parts of songs (e.g., song clips), etc. Sounds include natural sounds, white noise sounds, or any other vibrational noise that can be captured via a microphone. The music / sound table 320 includes the name of the music and sound, a description of the music and sound, and the actual music / sound or a link to the music / sound.

[0069] A usage log 322 is also depicted. The usage log 322 captures anonymous information (e.g., information with user identification removed, e.g., to comply with governing laws and regulations) regarding the music / sound being played and any filters / virtual lenses being used during the music / sound playback. The usage log 322 also captures anonymous geographical location data of the location where the music / sound playback occurred, the number of times the music / sound playback occurred, etc.

[0070] Data communication architecture

[0071] Figure 4FIG. is a schematic diagram showing the structure of a message 400 according to some examples, the message 400 being generated by an interactive client 104 for transmission via an interactive server 126 to another interactive client 104. The content of a particular message 400 is used to populate a message table 306 stored in a database 302 accessible by the interactive server 126. Similarly, the content of the message 400 is stored in memory as "in-transit" or "in-flight" data of the user system 102 or the interactive server 126. The message 400 is shown as including the following example components:

[0072] · Message identifier 402: A unique identifier that identifies the message 400.

[0073] · Message text payload 404: Text to be generated by the user via the user interface of the user system 102 and included in the message 400.

[0074] · Message image payload 406: Image data captured by a camera device component of the user system 102 or retrieved from a memory component of the user system 102 and included in the message 400. The image data for the message 400 being sent or received can be stored in an image table 316.

[0075] · Message video payload 408: Video data captured by a camera device component or retrieved from a memory component of the user system 102 and included in the message 400. The video data for the message 400 being sent or received can be stored in an image table 316.

[0076] · Message audio payload 410: Audio data captured by a microphone or retrieved from a memory component of the user system 102 and included in the message 400.

[0077] · Message enhancement data 412: Enhancement data (e.g., filters, stickers, or other annotations or enhancements) representing an enhancement to be applied to the message image payload 406, the message video payload 408, or the message audio payload 410 of the message 400. The enhancement data for the message 400 being sent or received can be stored in an enhancement table 312.

[0078] · Message duration parameter 414: A parameter value indicating, in seconds, the amount of time for which the content of the message (e.g., the message image payload 406, the message video payload 408, the message audio payload 410) is to be presented to the user or made accessible to the user via the interactive client 104.

[0079] · Message geographic location parameter 416: Geographic location data (e.g., latitude coordinates and longitude coordinates) associated with the content payload of the message. Multiple message geographic location parameter 416 values may be included in the payload, and each of these parameter values is associated with a content item included in the content (e.g., a specific image within the message image payload 406, or a specific video within the message video payload 408).

[0080] · Message story identifier 418: An identifier value that identifies one or more content collections (e.g., "stories" identified in the story table 318) associated with a specific content item in the message image payload 406 of the message 400. For example, multiple images within the message image payload 406 may each be associated with multiple content collections using the identifier value.

[0081] · Message music identifier 420: An identifier value that identifies one or more music or sounds to be recommended and / or played with certain message enhancement data 412 (e.g., photographic filters, stickers, or other annotations or enhancements).

[0082] · Message tag 422: Each message 400 may be tagged with multiple tags, and each of the multiple tags indicates a theme of the content included in the message payload. For example, in the case where a specific image included in the message image payload 406 depicts an animal (e.g., a lion), a tag value may be included within the message tag 422 indicating the relevant animal. The tag value may be generated manually based on user input or may be generated automatically using, for example, image recognition.

[0083] · Message sender identifier 424: An identifier (e.g., a messaging system identifier, an email address, or a device identifier) of the user of the user system 102 on which the message 400 is generated and from which the message 400 is sent.

[0084] · Message recipient identifier 426: An identifier (e.g., a messaging system identifier, an email address, or a device identifier) of the user of the user system 102 to which the message 400 is addressed.

[0085] The content (e.g., value) of each component of message 400 can be a pointer to a location in a table that stores content data values. For example, the image value in message image payload 406 can be a pointer to a location within image table 316 (or the address of a location within image table 316). Similarly, the value within message video payload 408 can point to data stored within image table 316, the value stored within message enhancement data 412 can point to data stored within enhancement table 312, the value stored within message story identifier 418 can point to data stored within story table 318, and the values stored within message sender identifier 424 and message receiver identifier 426 can point to user records stored within entity table 308.

[0086] System with a head-mounted device

[0087] Figure 5 FIG. 500 shows a system 500 including a head-mounted device 116 having a selector input device according to some examples. Figure 5 is a high-level functional block diagram of an example head-mounted device 116 communicatively coupled to a mobile device 114 and various server systems 504 (such as an interaction server system 110) via various networks 108.

[0088] The head-mounted device 116 includes one or more imaging devices, each of which can be, for example, a visible light imaging device 506, an infrared emitter 508, and an infrared imaging device 510.

[0089] The mobile device 114 is connected to the head-mounted device 116 using a low-power wireless connection 512 and a high-speed wireless connection 514. The mobile device 114 is also connected to the server system 504 and the network 516.

[0090] The head-mounted device 116 also includes two image displays in an image display 518 of an optical component. The two image displays of the optical component 518 include an image display associated with the left lateral side of the head-mounted device 116 and an image display associated with the right lateral side of the head-mounted device 116. The head-mounted device 116 also includes an image display driver 520, an image processor 522, a low-power circuitry 524, and a high-speed circuitry 526. The image display 518 of the optical component is used to present images and videos to a user of the head-mounted device 116, including images that can include a graphical user interface.

[0091] The image display driver 520 commands and controls the image display 518 of the optical component. The image display driver 520 can deliver image data directly to the image display 518 of the optical component for presentation or can convert the image data into a signal or data format suitable for delivery to an image display device. For example, the image data can be video data formatted according to a compression format such as H.264 (MPEG-4 Part 10), HEVC, Theora, Dirac, RealVideo RV40, VP8, VP9, etc., and the still image data can be formatted according to a compression format such as Portable Network Graphics (PNG), Joint Photographic Experts Group (JPEG), Tagged Image File Format (TIFF), or Exchangeable Image File Format (EXIF).

[0092] The head-wearable device 116 includes a frame and a stem (or temple) extending from a lateral side of the frame. The head-wearable device 116 also includes a user input device 528 (e.g., a touch sensor or a push button) including an input surface on the head-wearable device 116. The user input device 528 (e.g., a touch sensor or a push button) is used to receive an input selection from a user to manipulate a graphical user interface of the presented image.

[0093] Figure 5 The components shown for the head-wearable device 116 in are located on one or more circuit boards (e.g., a PCB or a flexible PCB) in the frame or the temple. Alternatively or additionally, the depicted components can be located in chunks, the frame, a hinge, or a nose bridge of the head-wearable device 116. The left visible light imaging device 506 and the right visible light imaging device 506 can include digital imaging device elements such as complementary metal-oxide-semiconductor (CMOS) image sensors, charge-coupled devices, imaging device lenses, or any other corresponding visible light or light-capturing elements that can be used to capture data including an image of a scene with an unknown object. The head-wearable device 116 includes a memory 502 that stores instructions for performing a subset or all of the functions described herein. The memory 502 can also include a storage device.

[0094] As Figure 5As shown, the high-speed circuit system 526 includes a high-speed processor 530, a memory 502, and a high-speed wireless circuit system 532. In some examples, the image display driver 520 is coupled to the high-speed circuit system 526 and is operated by the high-speed processor 530 to drive the left and right image displays of the image display 518 of the optical component. The high-speed processor 530 can be any processor capable of managing high-speed communication and operation of any general computing system required for the head-mounted device 116. The high-speed processor 530 includes processing resources required to manage high-speed data transmission over the high-speed wireless connection 514 to a wireless local area network (WLAN) using the high-speed wireless circuit system 532. In certain examples, the high-speed processor 530 executes an operating system (such as, the LINUX operating system) of the head-mounted device 116 or other such operating system, and the operating system is stored in the memory 502 for execution. In addition to any other duties, the high-speed processor 530 implementing the software architecture of the head-mounted device 116 is used to manage data transmission with the high-speed wireless circuit system 532. In certain examples, the high-speed wireless circuit system 532 is configured to implement the Institute of Electrical and Electronics Engineers (IEEE) 802.11 communication standard, which is also referred to as WiFi herein. In some examples, other high-speed communication standards can be implemented by the high-speed wireless circuit system 532.

[0095] The low-power wireless circuit system 534 and the high-speed wireless circuit system 532 of the head-mounted device 116 can include a short-range transceiver (Bluetooth TM ) and a wireless wide area network, local area network, or wide area network transceiver (e.g., cellular or WiFi). The mobile device 114, including transceivers communicating via the low-power wireless connection 512 and the high-speed wireless connection 514, can be implemented using the details of the architecture of the head-mounted device 116, and so can the other elements of the network 516.

[0096] The memory 502 includes any storage device capable of storing various data and applications, including camera device data generated by the left visible light camera device 506, the right visible light camera device 506, the infrared camera device 510, and the image processor 522, and images generated by the image display driver 520 for display on the image display of the optical component's image display 518. Although the memory 502 is shown integrated with the high-speed circuitry 526, in some examples, the memory 502 can be a separate stand-alone element of the head-wearable device 116. In certain such examples, electrical wiring can provide a connection from the image processor 522 or the low-power processor 536 to the memory 502 through a chip including the high-speed processor 530. In some examples, the high-speed processor 530 can manage the addressing of the memory 502 such that the low-power processor 536 will initiate the high-speed processor 530 whenever a read or write operation involving the memory 502 is needed.

[0097] As Figure 5 shown, the low-power processor 536 or the high-speed processor 530 of the head-wearable device 116 can be coupled to a camera device (visible light camera device 506, infrared emitter 508, or infrared camera device 510), an image display driver 520, a user input device 528 (e.g., a touch sensor or a push button), and the memory 502. The head-wearable device 116 is connected to a host computer. For example, the head-wearable device 116 is paired with the mobile device 114 via a high-speed wireless connection 514 or connected to the server system 504 via a network 516. The server system 504 can be one or more computing devices that are part of a service or network computing system, e.g., including a processor, a memory, and a network communication interface to communicate with the mobile device 114 and the head-wearable device 116 via the network 516.

[0098] The mobile device 114 includes a processor and a network communication interface coupled to the processor. The network communication interface enables communication via the network 516, a low-power wireless connection 512, or a high-speed wireless connection 514. The mobile device 114 can also store at least a portion of the instructions for generating stereo audio content in the memory of the mobile device 114 to implement the functions described herein.

[0099] The output components of the head-mounted device 116 include visual components such as a display, such as a liquid crystal display (LCD), a plasma display panel (PDP), a light emitting diode (LED) display, a projector, or a waveguide. The image display of the optical component is driven by an image display driver 520. The output components of the head-mounted device 116 also include acoustic components (e.g., speakers), tactile components (e.g., vibration motors), other signal generators, and the like. The input components (such as the user input device 528) of the head-mounted device 116, the mobile device 114, and the server system 504 may include alphanumeric input components (e.g., keyboards, touchscreens configured to receive alphanumeric input, optoelectronic keyboards, or other alphanumeric input components), pointing-based input components (e.g., mice, touchpads, trackballs, joysticks, motion sensors, or other pointing instruments), tactile input components (e.g., physical buttons, touchscreens that provide the location and force of a touch or touch gesture, or other tactile input components), audio input components (e.g., microphones), and the like.

[0100] The head-mounted device 116 may also include additional peripheral device elements. Such peripheral device elements may include biometric sensors, additional sensors, or display elements integrated with the head-mounted device 116. For example, the peripheral device elements may include any I / O components, which include output components, motion components, positioning components, or any other such elements described herein.

[0101] For example, biometric components include components for detecting expressions (e.g., hand expressions, facial expressions, voice expressions, body postures, or eye tracking), measuring biometric signals (e.g., blood pressure, heart rate, body temperature, sweating, or brain waves), identifying people (e.g., voice recognition, retina recognition, facial recognition, fingerprint recognition, or electroencephalogram-based recognition), and the like. Motion components include acceleration sensor components (e.g., accelerometers), gravity sensor components, rotational sensor components (e.g., gyroscopes), and the like. Positioning components include position sensor components for generating position coordinates (e.g., global positioning system (GPS) receiver components), Wi-Fi or Bluetooth TM transceivers for generating positioning system coordinates, altitude sensor components (e.g., altimeters or barometers that detect air pressure, from which altitude can be obtained), orientation sensor components (e.g., magnetometers), and the like. Such positioning system coordinates may also be received from the mobile device 114 via the low-power radio circuitry 534 or the high-speed radio circuitry 532 through the low-power wireless connection 512 and the high-speed wireless connection 514. The head-mounted device 116 is used to capture and / or display media content, including media created by the enhancement system 206 and music / sound recommendations provided by the music recommendation system 134.

[0102] Figure 6 Processing 600 for creating certain machine - executable contexts 602 that can provide music and sound recommendations according to an example is shown. In the depicted example, processing 600 collects certain context data at block 604. For example, machine - learning (ML) context data 606 can include data suitable for training one or more ML models 610 at block 608 to output music / sound recommendations based on using a photographic filter or virtual lens as input. For example, for each use of a photographic filter and virtual lens, ML context data 606 includes the music or sound selection (if any) that the user has chosen to pair with the photographic filter or virtual lens. ML context data 606 can include the date / time for the pairing of the virtual lens or photographic filter with the music or sound selection, the number of times the music or sound has been selected, the users who selected the music or sound, geographical location information, the type of imaging device used (e.g., mobile - phone imaging device, webcam), the type of device used (e.g., mobile phone, smartwatch), friends who have used the pairing, etc. Further details regarding Figure 7 the creation and training of the trained ML model 610 are described below.

[0103] At block 614, processing 600 also uses date / time context data 612 to create one or more date / time recommendation queries 616. For example, date / time context data 612 includes a holiday calendar, a national commemorative day calendar (e.g., October 28th of each year is National Kitten Day), an international commemorative day calendar (e.g., International Friendship Day is July 30th), and an event calendar (e.g., local festivals, including music festivals, concerts, local celebrations, parades, etc.) stored in database 130. In some examples, at block 614, the date / time recommendation queries 616 can be created by determining the date / time of interest and querying database 130 for the corresponding holidays, national commemorative days, international commemorative days, and events. Then, a second date / time recommendation query 616 can be created to use the unique ID (or name) of the corresponding holidays, national commemorative days, international commemorative days, and events as query terms. Then, the second date / time recommendation query 616 can find the music and sounds associated with holidays, national commemorative days, international commemorative days, and events via music / sound table 320. In fact, music / sound table 320 (or a related table) can include a searchable column that maps each stored music or song to one or more holidays, national commemorative days, international commemorative days, and events.

[0104] Media interrelationship context data 618 includes data that correlates photographic filters or virtual lenses with certain associated music and sounds. For example, a superhero such as Batman can be associated with the Batman movie soundtrack, bat noises, cave echo noises, etc. Thus, the music / sound table 320 (and associated tables) can store columns that map each photographic filter or virtual lens to one or more music and sounds. At block 620, an interrelationship recommendation query 622 is created to use the unique ID of the photographic filter or virtual lens as a query term to retrieve the media-interrelated music and sounds.

[0105] Other model context data 624 includes data for creating other recommendation models 628 at block 626, such as non-ML models using linear regression, heuristic derivation (e.g., Bayesian inference), etc. In some examples, other model context data 624 includes the same or similar data as the ML context data 606. For example, for each use of a photographic filter and virtual lens, the user has selected a music or sound choice (if any) paired with the photographic filter or virtual lens. Other model context data 624 can also include the date / time for the pairing of the virtual lens or photographic filter with the music or sound choice, the number of times the music or sound has been selected, geographical location information, the type of camera device used (e.g., mobile phone camera device, webcam), the type of device used (e.g., mobile phone, smartwatch), friends who have used the pairing, etc. At block 626, an other recommendation model 628 can be created by linear regression analysis of the other model context data 624 (e.g., setting the dependent variable to the photographic filter and virtual lens) to obtain one or more equations that take the selected photographic filter or virtual lens as input and produce the songs, song segments, and sounds to be recommended as output. Similarly, heuristic analysis via, for example, Bayesian probability analysis (e.g., using the prior probability distribution of photographic and virtual lens selections) can be used to obtain one or more equations that take the selected photographic filter or virtual lens as input and produce the songs, song segments, and sounds to be recommended as output.

[0106] As previously described, each of the contexts 602 can be used alone or in combination to provide music and / or sound recommendations. That is, recommendations from the contexts 602 can be combined and further used to discover which recommendation is the "best". In some examples, the music and / or sound recommendations are ranked, for example, from most recommended to least recommended. As described further below, ML recommendations can be ranked via "weights". For the date / time recommendation query 616 and the media correlation recommendation query 622, the popularity ranking field in the music / sound table 320 can be used to determine the most popular holiday music, national day music, etc. For the other models 628, each model can include a metric for ranking the predicted outputs (e.g., the recommended music and sounds), such as multiple R-squared metrics, adjusted R-squared metrics, etc. Similarly, statistical models, such as Bayesian-based models, include metrics such as relative probabilities, which can then be used for ranking. It should also be noted that the contexts 602 can be used to rank recommendations such that the preferences of an individual user are taken into account. The model 610 can be trained to identify that user A prefers content X more than user B, and / or prefers content X more than context Y. Similarly, queries 616, 622, and the other models 628 can be created to further customize the recommendations based on the individual user's taste.

[0107] Figure 7 A machine learning engine for creating and training the trained ML model 610 according to some embodiments is shown. The machine learning engine can be deployed to execute at a computing system such as the interactive server 126, the server system 504, and / or the third-party server 112. In fact, various computing systems can create and train the ML model 610, as described further below.

[0108] The machine learning engine 700 uses a training engine 702 and a prediction engine 704. The training engine 702 uses, for example, a subset of the ML context data 606 as the input data 706. That is, the ML context data 606 is used to provide the training input data 706. As previously described, for each use of a photographic filter and a virtual lens, the ML context data 606 can include the music or sound selection (if any) that the user has selected to pair with the photographic filter or virtual lens. The ML context data 606 can also include the date / time, geographical location information, the type of the imaging device used (e.g., a mobile phone imaging device, a webcam), the type of the device used (e.g., a mobile phone, a smartwatch), etc. for the pairing as part of the input data 706.

[0109] The input data 706 is preprocessed via a preprocessing component 708 to determine one or more features 710. For example, the preprocessing component 708 may select a subset of relevant attributes or features from the input data 706 for predictive modeling. In one example, the features 710 that may be selected include a given photographic filter or virtual lens, music or sound previously used with the photographic filter or virtual lens, the number of times the music or sound was used with the photographic filter or virtual lens, the usage date / time, the geographic location of each use, the type of imaging device used for each use, and / or the type of device used for each use. One or more features 710 may be used to generate an initial input model 712, which may be iteratively updated or updated using future labeled or unlabeled data (e.g., during reinforcement learning).

[0110] In the prediction engine 704, current data 714 (e.g., current ML context data 606, such as data recorded on the same day as the prediction engine 704 is used, data recorded during the same week as the prediction engine 704 is used, etc.) may be input to a preprocessing component 716. In some examples, the preprocessing component 716 and the preprocessing component 708 are the same. The prediction engine 704 generates a feature vector 718 from the preprocessed current data, which is input into a model 720 to generate one or more standard weights 722. The standard weights 722 may be used to output predictions, as discussed further below.

[0111] The training engine 702 may operate in an offline manner to train the model 720 (e.g., on a server). Thus, the trained model 720 becomes the trained ML model 610. The prediction engine 704 may be designed to operate in an online manner (e.g., in real time, at a server, at a mobile device, on a wearable device, etc.). In some examples, the model 720 may be periodically updated via additional training (e.g., via updated input data 706 or based on the labeled or unlabeled data output in the weights 722) or based on identified future data, such as by using reinforcement learning to personalize a general model (e.g., the initial model 712) for a particular user. Additional input data 706 may be used to update the initial model 712 until a satisfactory model 720 is generated. The model 720 may stop generating based on a specified criterion (e.g., after using a sufficient amount of input data, such as 1,000, 10,000, 700,000 data points, etc.) or when the data converges (e.g., similar inputs produce similar outputs). The model 720 may continue to evolve by being trained with updated data on a daily, weekly, etc. basis.

[0112] The specific machine learning algorithm for training engine 702 can be selected from many different potential supervised or unsupervised machine learning algorithms. Examples of supervised learning algorithms include artificial neural networks, Bayesian networks, instance-based learning, support vector machines, decision trees (e.g., C4.5, C9.5, classification and regression trees (CART), chi-squared automatic interaction detector (CHAID), etc.), random forests, linear classifiers, quadratic classifiers, k-nearest neighbors, linear regression, logistic regression, and hidden Markov models. Examples of unsupervised learning algorithms include the expectation maximization algorithm, vector quantization, and the information bottleneck method. The unsupervised model may not have the training engine 702. In an example implementation, a regression model is used, and the model 720 is a coefficient vector corresponding to the learning importance of each of the features in the feature vectors 710, 718. Reinforcement learning models can use Q-learning, deep Q-networks, Monte Carlo techniques including policy evaluation and policy improvement, state-action-reward-state-action (SARSA), deep deterministic policy gradient (DDPG), etc.

[0113] Once trained, the model 720 receives a photographic filter or a virtual lens as input and provides music and / or sound recommendations as output. In some examples, the music and / or sound recommendations are ranked, e.g., from most recommended to least recommended. By training the model 720 into the trained ML model 610, the techniques described herein provide music and sound recommendations obtained from patterns found in the selection of music or sound to be included with certain photographic filters and virtual lenses.

[0114] Figure 8 An embodiment of a process 800 for music and sound recommendations suitable for providing advice for photographic filters and visual lenses according to some examples is depicted. In the depicted example, the process 600 receives a selection of a photographic filter or a virtual lens at block 802. For example, a user of the user system 102 can select a photographic filter or a visual lens to use via the GUI. Then, at block 804, the process 800 selects one or more contexts to apply to the selected photographic filter or virtual lens. As mentioned above, the ML model 610, the date / time recommendation query 616, the media correlation recommendation query 622, and / or other models 628 (e.g., non-ML models) can be used.

[0115] In some examples, the ML model 610 is the default selection. During certain "marked" dates, such as Diwali, New Year, Chinese New Year, Christmas, etc., the date / time recommendation query 616 is used. In some examples, when the event includes new movie releases, concerts, parades, etc. that involve certain artists, movie characters, etc., the media correlation recommendation query 622 is used. For example, during Oscar week, photo filters and virtual lenses associated with movie characters, artists, etc. can be matched with certain music / sound recommendations via the media correlation recommendation query 622. When the training data is more limited or fewer computing resources are used, other models 628 can be used. In some examples, the ML model 610, the date / time recommendation query 616, the media correlation recommendation query 622, and the other models 628 are all used.

[0116] Then, at block 806, the process 800 obtains one or more songs (e.g., vocal and instrumental), song segments, and sounds to be recommended by applying the ML model 610, the date / time recommendation query 616, the media correlation recommendation query 622, and / or the other models 628. Input to the ML model 610, the date / time recommendation query 616, the media correlation recommendation query 622, and the other models 628 is the selected photo filter or virtual lens. The output of the ML model 610, the date / time recommendation query 616, the media correlation recommendation query 622, and / or the other models 628. The input to the ML model 610, the date / time recommendation query 616, the media correlation recommendation query 622, and the other models 628 includes one or more of the recommended songs, song segments, and sounds.

[0117] Processor 800 provides the recommended music and / or sounds at block 808, e.g., songs, song segments, and sounds output via ML model 610, date / time recommendation query 616, media correlation recommendation query 622, and / or other models 628. In some examples, a single recommended piece of music or sound, e.g., a single song, song segment, or sound. The single recommended piece of music or sound is selected by determining the most highly recommended music or sound. For ML model 610, in one example, weights 722 can be used to rank the recommendations from highest to lowest. For date / time recommendation query 616 and media correlation recommendation query 622, the popularity rank field in music / sound table 320 can be used to determine the most popular holiday music, national holiday music, etc. For other models 628, each model can include a metric for ranking the predicted outputs (e.g., the recommended music and sounds), such as multiple R-squared metrics, adjusted R-squared metrics, etc. Similarly, statistical models, such as Bayesian-based models, include metrics such as relative probabilities. Then, if obtained by the server, the recommendations are sent to user system 102 for display by the GUI, as further described below.

[0118] In some examples, at block 810, the recommended music and sounds are used to create media content. For example, when the user is using a photographic filter or a virtual lens, the recommended music and sounds can be automatically played. Thus, the techniques described herein provide a more effective and engaging way to contextually match media created via photographic filters and virtual lenses with various music and sounds.

[0119] Figure 9 An example screenshot 900 created via GUI 902 is shown. In the depicted example, the turntable GUI control 904 displays a center icon 906 representing the selected virtual lens. Thus, the virtual lens is used to create an AR augmentation, in this case, a mask augmentation 908 is shown as being "worn" by user 910. User 910 can turn their head, and as the head turns at various angles and positions, mask augmentation 908 will conform to the user's head. If the user desires other virtual lenses, the user can select other virtual lenses 912, 914. The turntable control 904 can take a swipe gesture as input to present additional virtual lenses or photographic filters.

[0120] Music recommendation 916 is shown as being displayed together with center icon 906. Music recommendation 916 can be obtained by using ML model 610, date / time recommendation query 616, media interrelationship recommendation query 622, and / or other models 628. Then, the user can add music recommendation 916 to a message or story to be sent to members of a social network, for example. More specifically, when user 910 records themselves and provides the recording to members of the social network, music recommendation 916 (such as a song, song snippet, and / or sound) can be played together with the display of mask enhancement 908.

[0121] Machine architecture

[0122] Figure 10 is a pictorial representation of a machine 1000 within which instructions 1002 (e.g., software, program, application, applet, app, or other executable code) can be executed to cause the machine 1000 to perform any one or more of the methods discussed herein. For example, instructions 1002 can cause machine 1000 to perform any one or more of the methods described herein. Instructions 1002 transform a general, unprogrammed machine 1000 into a particular machine 1000 programmed to perform the described and illustrated functions in the described manner. Machine 1000 can operate as a stand-alone device or can be coupled (e.g., networked) to other machines. In a networked deployment, machine 1000 can operate as a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. Machine 1000 can include, but is not limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular phone, a smartphone, a mobile device, a wearable device (e.g., a smartwatch), a smart home device (e.g., a smart appliance), other smart devices, a web device, a network router, a network switch, a network bridge, or any machine capable of executing instructions 1002 sequentially or otherwise to perform the actions specified to be taken by machine 1000. Further, although a single machine 1000 is shown, the term "machine" shall also be taken to include a collection of machines that individually or jointly execute instructions 1002 to perform any one or more of the methods (e.g., processing 600, 800) discussed herein. For example, machine 1000 can include user system 102 or any one of the server devices forming part of interactive server system 110. In some examples, machine 1000 can also include both a client system and a server system, where certain operations of a particular method or algorithm are executed on the server side and certain operations of the particular method or algorithm are executed on the client side.

[0123] Machine 1000 may include a processor 1004, a memory 1006, and an input / output I / O component 1008 that may be configured to communicate with each other via a bus 1010. In an example, the processor 1004 (e.g., a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a radio frequency integrated circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor 1012 and a processor 1014 that execute instructions 1002. The term "processor" is intended to include multi-core processors, which may include two or more independent processors (sometimes referred to as "cores") that can execute instructions simultaneously. Although Figure 10 multiple processors 1004 are shown, machine 1000 may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiple cores, or any combination thereof.

[0124] Memory 1006 includes a main memory 1016, a static memory 1018, and a storage unit 1020, all of which may be accessed by the processor 1004 via the bus 1010. The main memory 1006, the static memory 1018, and the storage unit 1020 store instructions 1002 that implement any one or more of the methods or functions described herein. The instructions 1002 may also reside, completely or partially, within the main memory 1016, within the static memory 1018, within the storage unit 1020, within the machine-readable medium 1022 within the storage unit 1020, within at least one of the processors 1004 (e.g., within a cache memory of the processor), or any suitable combination thereof during execution by the machine 1000.

[0125] The I / O component 1008 may include various components for receiving input, providing output, generating output, transmitting information, exchanging information, capturing measurement results, etc. The specific I / O components 1008 included in a particular machine will depend on the type of the machine. For example, a portable machine such as a mobile phone may include a touch input device or other such input mechanism, while a headless server machine is less likely to include such a touch input device. It will be appreciated that the I / O component 1008 may include Figure 10Many other components not shown. In various examples, the I / O component 1008 can include a user output component 1024 and a user input component 1026. The user output component 1024 can include visual components (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), tactile components (e.g., a vibration motor, a resistance mechanism), other signal generators, etc. The user input component 1026 can include an alphanumeric input component (e.g., a keyboard, a touch screen configured to receive alphanumeric input, an optical keyboard, or other alphanumeric input components), a pointing-based input component (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instruments), a tactile input component (e.g., a physical button, a touch screen that provides the location and force of a touch or touch gesture, or other tactile input components), an audio input component (e.g., a microphone), etc.

[0126] In additional examples, the I / O component 1008 can include a biometric component 1028, a motion component 1030, an environmental component 1032, or a positioning component 1034, as well as various other components. For example, the biometric component 1028 includes components for detecting expressions (e.g., hand expressions, facial expressions, voice expressions, body postures, or eye tracking), measuring biometric signals (e.g., blood pressure, heart rate, body temperature, sweating, or brain waves), identifying a person (e.g., voice recognition, retina recognition, facial recognition, fingerprint recognition, or electroencephalogram-based recognition), etc. The motion component 1030 includes an acceleration sensor component (e.g., an accelerometer), a gravity sensor component, a rotation sensor component (e.g., a gyroscope).

[0127] The environmental component 1032 includes, for example, one or more camera devices (with still image / photo and video capabilities), a lighting sensor component (e.g., a photometer), a temperature sensor component (e.g., one or more thermometers that detect the ambient temperature), a humidity sensor component, a pressure sensor component (e.g., a barometer), an acoustic sensor component (e.g., one or more microphones that detect background noise), a proximity sensor component (e.g., an infrared sensor that detects nearby objects), a gas sensor (e.g., a gas detection sensor that detects the concentration of a hazardous gas for safety or measures pollutants in the atmosphere), or other components that can provide an indication, measurement, or signal corresponding to the surrounding physical environment.

[0128] Regarding the imaging device, the user system 102 may have an imaging device system that includes, for example, a front imaging device on the front surface of the user system 102 and a rear imaging device on the rear surface of the user system 102. The front imaging device may be used, for example, to capture still images and videos (e.g., "selfies") of the user of the user system 102, which can then be enhanced with the enhancement data (e.g., filters) described above. The rear imaging device may be used, for example, to capture still images and videos in a more traditional imaging device mode, where these images are similarly enhanced using the enhancement data. In addition to the front imaging device and the rear imaging device, the user system 102 may also include a 360° imaging device for capturing 360° photos and videos.

[0129] In addition, the imaging device system of the user system 102 may include a dual rear imaging device (e.g., a main imaging device and a depth sensing imaging device), or even a triple, quadruple, or quintuple rear imaging device configuration on the front and rear sides of the user system 102. For example, these multi-imaging device systems may include a wide-angle imaging device, an ultra-wide-angle imaging device, a telephoto imaging device, a macro imaging device, and a depth sensor.

[0130] The positioning component 1034 includes a position sensor component (e.g., a GPS receiver component), an altitude sensor component (e.g., an altimeter or barometer that detects air pressure, from which altitude can be obtained), an azimuth sensor component (e.g., a magnetometer), etc.

[0131] Various techniques can be used to implement communication. The I / O component 1008 also includes a communication component 1036 that is operable to couple the machine 1000 to the network 1038 or the device 1040 via a respective coupling or connection. For example, the communication component 1036 may include a network interface component that docks with the network 1038 or another suitable device. In another example, the communication component 1036 may include a wired communication component, a wireless communication component, a cellular communication component, a near field communication (NFC) component, components (e.g., low power consumption), components, and other communication components that provide communication via other modalities. The device 1040 may be another machine or any of a variety of peripheral devices (e.g., a peripheral device coupled via USB).

[0132] In addition, the communication component 1036 may detect an identifier or include components operable to detect an identifier. For example, the communication component 1036 may include a radio frequency identification (RFID) tag reader component, an NFC smart tag detection component, an optical reader component (e.g., for detecting one-dimensional barcodes such as Universal Product Code (UPC) barcodes, and optical sensors for multi-dimensional barcodes such as Quick Response (QR) codes, Aztec codes, Data Matrix, Dataglyph, MaxiCode, PDF417, UltraCode, UCC RSS-2D barcodes, and other optical codes), or an acoustic detection component (e.g., a microphone for identifying a tagged audio signal). Additionally, various information such as location via Internet Protocol (IP) geolocation, location via signal triangulation, location via detecting an NFC beacon signal that may indicate a specific location, etc., may be obtained via the communication component 1036.

[0133] Various memories (e.g., main memory 1016, static memory 1018, and the memory of the processor 1004) and the storage unit 1020 may store one or more sets of instructions and data structures (e.g., software) implemented or used by any of the methods or functions described herein. These instructions (e.g., instruction 1002), when executed by the processor 1004, cause the various operations to implement the disclosed examples.

[0134] The instructions 1002 may be sent or received over the network 1038 via a network interface device (e.g., the network interface component included in the communication component 1036), using a transmission medium and using any one of several well-known transmission protocols (e.g., Hypertext Transfer Protocol (HTTP)). Similarly, the instructions 1002 may be transmitted or received using a transmission medium via an interface with the device 1040 (e.g., a peer-to-peer interface).

[0135] Software architecture

[0136] Figure 11FIG. 1100 is a block diagram showing a software architecture 1102 that can be installed on any one or more of the devices described herein. The software architecture 1102 is supported by hardware such as a machine 1104 that includes a processor 1106, a memory 1108, and I / O components 1110. In this example, the software architecture 1102 can be conceptualized as a stack of layers, where each layer provides a specific function. The software architecture 1102 includes the following layers: an operating system 1112, libraries 1114, frameworks 1116, and applications 1118. In operation, the application 1118 activates API calls 1120 through the software stack and receives messages 1122 in response to the API calls 1120.

[0137] The operating system 1112 manages hardware resources and provides common services. The operating system 1112 includes, for example, a kernel 1124, services 1126, and drivers 1128. The kernel 1124 serves as an abstraction layer between the hardware and other software layers. For example, the kernel 1124 provides functions such as memory management, processor management (e.g., scheduling), component management, networking, and security settings. The services 1126 can provide other common services for other software layers. The drivers 1128 are responsible for controlling or interfacing with the underlying hardware. For example, the drivers 1128 can include a display driver, a camera device driver, or a low-power driver, a flash driver, a serial communication driver (e.g., a USB driver), a driver, an audio driver, a power management driver, etc.

[0138] The libraries 1114 provide common low-level infrastructure used by the applications 1118. The libraries 1114 can include system libraries 1130 (e.g., the C standard library), which provide functions such as memory allocation functions, string manipulation functions, mathematical functions, etc. Additionally, the libraries 1114 can include API libraries 1132, such as media libraries (e.g., libraries for supporting the presentation and manipulation of various media formats, such as Moving Picture Experts Group-4 (MPEG4), High Efficiency Video Coding (H.264 or AVC), Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC), Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group (JPEG or JPG), or Portable Network Graphics (PNG)), graphics libraries (e.g., the OpenGL framework for 2D and 3D rendering in graphical content on a display), database libraries (e.g., SQLite, which provides various relational database functions), web libraries (e.g., WebKit, which provides web browsing functions), etc. The libraries 1114 can also include various other libraries 1134 to provide many other APIs to the applications 1118.

[0139] The framework 1116 provides a common high-level infrastructure for use by the applications 1118. For example, the framework 1116 provides various graphical user interface (GUI) functions, high-level resource management, and high-level location services. The framework 1116 can provide a wide range of other APIs that can be used by the applications 1118, some of which may be specific to a particular operating system or platform.

[0140] In an example, the applications 1118 can include a home application 1136, a contacts application 1138, a browser application 1140, a book reader application 1142, a location application 1144, a media application 1146, a messaging application 1148, a gaming application 1150, and various other applications such as third-party applications 1152. The applications 1118 are programs that execute functions defined in a program. One or more of the applications 1118 can be created using various programming languages, such as object-oriented programming languages (e.g., Objective-C, Java, or C++) or procedural programming languages (e.g., C language or assembly language). In a particular example, the third-party applications 1152 (e.g., applications developed using an ANDROID TM or IOS TM software development kit (SDK) by an entity other than the vendor of a particular platform) can be mobile software that runs on a mobile operating system such as IOS TM , ANDROID TM , Phone or another mobile operating system. In this example, the third-party applications 1152 can activate API calls 1120 provided by the operating system 1112 to facilitate the functions described herein.

[0141] Conclusion

[0142] Technical advantages include automatically obtaining music and sound recommendations by selecting a photography filter or a virtual lens. The music and sound recommendations are context-aware and provide recommendations based on date / time, based on a machine learning model, based on the interrelationship between media, based on a non-machine learning model, or a combination thereof. For example, a photography filter and a virtual lens combined with certain music may prove to be popular as part of a group of friends, and a machine learning model can detect the popularity and help users participate in new trends.

[0143] Glossary

[0144] A "carrier signal" refers, for example, to any non-tangible medium that can store, encode, or carry instructions executable by a machine and includes digital or analog communication signals or other non-tangible media that facilitate the communication of such instructions. Instructions can be sent or received over a network using a transmission medium via a network interface device.

[0145] "Client device" refers, for example, to any machine that interfaces with a communication network to obtain resources from one or more server systems or other client devices. The client device can be, but is not limited to, a mobile phone, a desktop computer, a laptop computer, a portable digital assistant (PDA), a smart phone, a tablet computer, a ultrabook, a netbook, a laptop computer, a multiprocessor system, a microprocessor-based or programmable consumer electronics product, a game console, a set-top box, or any other communication device that a user can use to access the network.

[0146] "Communication network" refers, for example, to one or more portions of a network, which can be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the public switched telephone network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a network, another type of network, or a combination of two or more such networks. For example, a network or a portion of a network can include a wireless network or a cellular network, and the coupling can be a code division multiple access (CDMA) connection, a global system for mobile communications (GSM) connection, or other types of cellular or wireless coupling. In this example, the coupling can implement any data transmission technology among various types of data transmission technologies, such as single-carrier radio transmission technology (1xRTT), evolved data optimized (EVDO) technology, general packet radio service (GPRS) technology, enhanced data rate GSM evolution (EDGE) technology, the 3rd Generation Partnership Project (3GPP) including 3G, the 4th Generation Wireless (4G) network, universal mobile telecommunications system (UMTS), high-speed packet access (HSPA), worldwide interoperability for microwave access (WiMAX), long term evolution (LTE) standard, other data transmission technologies defined by various standards-setting organizations, other long-distance protocols, or other data transmission technologies.

[0147] "Component" refers, for example, to a logical or physical entity having boundaries defined by function or subroutine calls, branch points, APIs, or other techniques that provide partitioning or modularization for a particular processing or control function. Components can be combined with other components via their interfaces to perform machine processing. A component can be a packaged functional hardware unit designed to be used with other components, as well as part of a program for a specific function that generally performs related functions. Components can constitute software components (e.g., code implemented on a machine-readable medium) or hardware components. A "hardware component" is a tangible unit capable of performing certain operations and can be configured or arranged in some physical manner. In various examples, one or more computer systems (e.g., stand-alone computer systems, client computer systems, or server computer systems) or one or more hardware components of a computer system (e.g., a processor or group of processors) can be configured by software (e.g., an application or part of an application) to operate to perform certain operations as described herein as a hardware component. A hardware component can also be implemented mechanically, electronically, or in any suitable combination thereof. For example, a hardware component can include dedicated circuitry or logic that is permanently configured to perform certain operations. A hardware component can be a dedicated processor, such as a field-programmable gate array (FPGA) or an application-specific integrated circuit (ASIC). A hardware component can also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware component can include software executed by a general-purpose processor or other programmable processor. Once configured by such software, the hardware component becomes a particular machine (or a particular component of a machine) that is uniquely customized to perform the configured function and is no longer a general-purpose processor. It will be appreciated that the decision of whether to implement a hardware component mechanically in dedicated and permanently configured circuitry or in temporarily configured (e.g., software-configured) circuitry can be made for cost and time considerations. Thus, the phrase "hardware component" (or "hardware-implemented component") should be understood to include a tangible entity, i.e., an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in some manner or perform certain operations as described herein. Considering an example where a hardware component is temporarily configured (e.g., programmed), it is not necessary to configure or instantiate each hardware component at any given time. For example, in the case where a hardware component includes a general-purpose processor that is configured by software to become a dedicated processor, the general-purpose processor can be configured at different times to be respective different dedicated processors (e.g., including different hardware components). The software accordingly configures a particular one or more processors to, for example, constitute a particular hardware component at one time and a different hardware component at a different time. Hardware components can provide information to other hardware components and receive information from other hardware components.Accordingly, the described hardware components can be considered communicatively coupled. In cases where multiple hardware components are present simultaneously, communication can be achieved through signal transmission between or among two or more hardware components (e.g., via appropriate circuitry and buses). In examples where multiple hardware components are configured or instantiated at different times, communication between such hardware components can be achieved, for example, by storing information in a memory structure accessible to the multiple hardware components and retrieving the information from the memory structure. For example, one hardware component can perform an operation and store the output of the operation in a memory device communicatively coupled to it. Then, another hardware component can access the memory device at a subsequent time to retrieve the stored output and process it. Hardware components can also initiate communication with input or output devices and can operate on resources (e.g., a collection of information). Various operations of the example methods described herein can be performed, at least in part, by one or more processors that are temporarily configured (e.g., via software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors can constitute processor-implemented components that operate to perform one or more of the operations or functions described herein. As used herein, a "processor-implemented component" refers to a hardware component implemented using one or more processors. Similarly, the methods described herein can be implemented, at least in part, by a processor, where a particular one or more processors are examples of hardware. For example, at least some of the operations of a method can be performed by one or more processors or processor-implemented components. Additionally, one or more processors can also operate to support the execution of relevant operations in a "cloud computing" environment or as a "software as a service" (SaaS) operation. For example, at least some of the operations can be performed by a group of computers (as an example of machines that include processors), where the operations can be accessed via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., APIs). The execution of certain operations can be distributed among the processors, not residing only within a single machine but deployed across multiple machines. In some examples, the processor or processor-implemented components can be located in a single geographical location (e.g., within a home environment, an office environment, or a server farm). In other examples, the processor or processor-implemented components can be distributed across multiple geographical locations.

[0148] "Computer-readable storage medium" refers to, for example, both machine storage media and transmission media. Thus, these terms include both storage devices / media and carrier / modulated data signals. The terms "machine-readable medium", "computer-readable medium", and "device-readable medium" mean the same thing and can be used interchangeably in this disclosure.

[0149] "Ephemeral message" refers, for example, to a message that is accessible within a time-limited duration. The ephemeral message can be text, image, video, etc. The access time of the ephemeral message can be set by the message sender. Alternatively, the access time can be a default setting or a setting specified by the recipient. Regardless of the setting technique, the message is temporary.

[0150] "Machine storage medium" refers, for example, to a single or multiple storage devices and media (e.g., centralized or distributed databases, and associated caches and servers) that store executable instructions, routines, and data. Thus, the term should be regarded as including, but not limited to, solid-state memory and optical and magnetic media, including memory internal or external to the processor. Specific examples of machine storage media, computer storage media, and device storage media include: non-volatile memory, including, for example, semiconductor memory devices such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), FPGA, and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The terms "machine storage medium", "device storage medium", and "computer storage medium" mean the same thing and can be used interchangeably in this disclosure. The terms "machine storage medium", "computer storage medium", and "device storage medium" expressly exclude carrier waves, modulated data signals, and other such media, at least some of which are subsumed under the term "signal medium".

[0151] "Non-transitory computer-readable storage medium" refers, for example, to a tangible medium capable of storing, encoding, or carrying instructions executable by a machine.

[0152] "Signal medium" refers, for example, to any intangible medium capable of storing, encoding, or carrying instructions executable by a machine and includes digital or analog communication signals or other intangible media that facilitate the communication of software or data. The term "signal medium" should be regarded as including any form of modulated data signal, carrier wave, etc. The term "modulated data signal" means a signal whose one or more characteristics are set or changed in such a way as to encode information in the signal. The terms "transmission medium" and "signal medium" mean the same thing and can be used interchangeably in this disclosure.

[0153] "User equipment" refers, for example, to equipment that is accessed, controlled, or owned by a user and with which the user interacts to perform actions or interact with other users or computer systems.

Claims

1. A system, comprising: one or more hardware processors; and at least one memory storing instructions that cause the one or more hardware processors to perform operations, the operations including: receiving, via a client device, a selection of a photographic filter or a virtual lens; obtaining, via a model, a date, or a combination thereof, a music recommendation, a sound recommendation, or a combination thereof for the selection of the photographic filter or the virtual lens; and providing the music recommendation, the sound recommendation, or the combination thereof to the client device.

2. The system according to claim 1, wherein, The model includes a machine learning model.

3. The system according to claim 2, wherein, The instructions include instructions that cause the one or more hardware processors to perform operations including training the machine learning model on a training data set.

4. The system according to claim 3, wherein, The training data set includes the number of times a song, a song segment, a sound, or a combination thereof is selected to be played with the photographic filter, the virtual lens, or a combination thereof.

5. The system according to claim 4, wherein, The training data set includes the geographical location where the song, the song segment, or a combination thereof is played with the photographic filter, the virtual lens, or a combination thereof.

6. The system according to claim 5, wherein, The training data set includes the number of times the song, the song segment, the sound, or a combination thereof is selected by members of a social network to be played with the photographic filter, the virtual lens, or a combination thereof.

7. The system according to claim 6, wherein, The members of the social network include a group of friends of a user of the client device.

8. The system according to claim 3, wherein, Training the machine learning model includes continuously training the machine learning model by using a current data set.

9. The system according to claim 1, wherein The model includes a linear regression model configured to apply linear regression derivation or a probability-based model configured to apply statistical probability derivation to obtain the music recommendation, the sound recommendation, or a combination thereof.

10. The system according to claim 1, wherein, Obtaining the music recommendation, the sound recommendation, or a combination thereof via a date includes: performing a first query to determine a holiday, a national memorial day, an international memorial day, an event, or a combination thereof.

11. The system according to claim 10, wherein, Obtaining the music recommendation, the sound recommendation, or a combination thereof via a date includes: using the result from the first query to perform a second query to determine music, a sound, or a combination thereof associated with the holiday, the national memorial day, the international memorial day, the event, or a combination thereof.

12. The system according to claim 1, wherein [[ID= 13. The system according to claim 12, wherein, ​ 14. The system according to claim 1, wherein, ​ 15. The system according to claim 1, wherein, ​ 16. The system according to claim 1, wherein, ​ 17. The system according to claim 16, wherein, The turntable control includes an icon that includes a visual representation of the photographic filter or the virtual filter, and wherein the music recommendation, the sound recommendation, or a combination thereof is displayed with the icon.

18. A method, comprising: Receiving, from a client device, a selection of a photographic filter or a virtual lens; Obtaining, via a model, a date, or a combination thereof, a music recommendation, a sound recommendation, or a combination thereof for the selection of the photographic filter or the virtual lens; And Providing the music recommendation, the sound recommendation, or a combination thereof to the client device.

19. The method according to claim 18, wherein, The model includes a machine learning model that is trained to receive a photographic filter and a virtual lens as inputs and provide one or more songs, song segments, sounds, or a combination thereof as outputs.

20. A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that, when executed by a computer, cause the computer to: Receive, from a client device, a selection of a photographic filter or a virtual lens; Obtain, via a model, a date, or a combination thereof, a music recommendation, a sound recommendation, or a combination thereof for the selection of the photographic filter or the virtual lens; and Provide the music recommendation, the sound recommendation, or a combination thereof to the client device.

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