Patent Publication Number: US-2022217104-A1

Title: Content suggestion system

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation of U.S. patent application Ser. No. 15/952,859, filed Apr. 13, 2018, which is incorporated by reference herein in its entirety. 
    
    
     TECHNICAL FIELD 
     Embodiments of the present disclosure relate generally to mobile computing technology and, more particularly, but not by way of limitation, to systems for managing content of chat sessions between users. 
     BACKGROUND 
     Mobile devices (such as smart phones, personal digital assistants, computer tablets, smart watches, and so on) are ubiquitous. Mobile devices provide advanced computing capabilities and services to users, such as voice communications, text and other messaging communications, video and other multimedia communications, streaming services, and so on. Often, users send and receive data (e.g., messages), and otherwise communicate with one another via mobile devices. 
     Existing text-based communication applications (e.g., text messaging, instant messaging, chats, email, and so on) provide users with user selectable options for supplementing input text with pictorial elements, such as emojis and other ideograms, pictograms, images, GIFs, animations, videos, and other multimedia content. Users may search for and select various elements into their message to provide additional context to text-based content. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
       To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced. 
         FIG. 1  is a block diagram showing an example messaging system for exchanging data (e.g., messages and associated content) over a network in accordance with some embodiments, wherein the messaging system includes a content suggestion system. 
         FIG. 2  is block diagram illustrating further details regarding a messaging system, according to example embodiments. 
         FIG. 3  is a block diagram illustrating various modules of a content suggestion system, according to certain example embodiments. 
         FIG. 4  is a flowchart illustrating a method for ranking chat suggestions, according to certain example embodiments. 
         FIG. 5  is a flowchart illustrating a method for presenting chat suggestions, according to certain example embodiments. 
         FIG. 6  is a flowchart illustrating a method for presenting chat suggestions, according to certain example embodiments. 
         FIG. 7  is a diagram illustrating a method for ranking chat content to be presented as a chat suggestion, according to certain example embodiments. 
         FIG. 8  is an illustration of an interface to display a chat suggestion, according to certain example embodiments. 
         FIG. 9  is an illustration of an interface to display a chat suggestion, according to certain example embodiments. 
         FIG. 10  is a block diagram illustrating a representative software architecture, which may be used in conjunction with various hardware architectures herein described and used to implement various embodiments. 
         FIG. 11  is a block diagram illustrating components of a machine, according to some example embodiments, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. 
     
    
    
     DETAILED DESCRIPTION 
     Conventional chat systems often provide certain “chat suggestions” based on explicit (or implicit) inputs received from a user, wherein the chat suggestions typically comprise a subsequent text element (e.g., a word, a letter, a punctuation, etc.). These conventional chat systems are able to (at best) provide a suggestion based on an input received at the client device (e.g., the user of the client device begins to draft a response), or based on an existing dictionary or lexicon of common words or phrases. More recently, chat systems have been developed which enable users to communicate with one another through unconventional message content that do not fit within the existing chat suggestion frameworks, due in part to the abstract nature of the content and a constantly changing contextual meaning of the content itself. 
     For example, some platforms enable individuals to communicate with one another by generating and sharing content such as pictograms and ideograms through a chat interface, wherein a meaning or context of the pictogram or ideogram is not immediately obvious. As a result, generating chat and messaging suggestions that include such content is challenging, and may currently require a significant amount of frontend work to categorize and define content within database. While this may be a sufficient solution in the short term, such databases would require a great deal of maintenance and administrator input in order to add or update the content on a regular basis. 
     Embodiments described herein relate to a content suggestion system to generate and cause display of a set of chat suggestions based on messages received at a client device. The content suggestions system is configured to display messages that include message content at a client device, and identify content selected by a user of the client device to be included in a response to the messages received at the client device. The content suggestion system tracks and stores a number of times in which a particular pair of content appear in succession in a chat context, and calculates a ranking of the content among a set of available content. When subsequent messages that include the content of the content pair are displayed at the client device, the content suggestion system retrieves and presents a set of content as suggestions, based on the corresponding ranks. 
     “Message content,” as discussed herein may refer to various types of media items that may be included within messages (e.g., text messages, ephemeral message, e-mails, private messages, direct messages, forum posts, etc.) displayed at a client devices. For example, message content may include a text string, pictograms or ideograms (e.g., emoji), images, audio data, video data, as well as personalized avatars (e.g., Bitmoji). Content pairs may comprise any combination of the various types of message content discussed above. 
     The content suggestion system is configured to cause display of a message that includes message content (e.g., first content) at a client device, and receive a selection of second content from a selection of content options. In response to receiving the selection of the second chat content, the content suggestion system indexes and stores a content pair that comprises the first content and the second content, and increments a usage counter that corresponds to the content pair and indicates a number of times in which the content pair occurred in a message context (i.e., when the second content was used in a response to a message that included the first content). The content suggestion system ranks the second content among a set of content based on the usage metric of the content pair. 
     In response to receiving a subsequent message that includes the first content at the client device, the content suggestion system retrieves content from a content database, based on rankings corresponding to content pairs that include the first content. For example, the content suggestion system may retrieve the second content from the database, based on the usage metric of the content pair that comprises the first content and the second content. The content suggestion system generates a presentation of the retrieved content, wherein a ranking (i.e., a display order) of the content is based on the corresponding usage metrics. The presentation of the suggested content may be displayed in a portion of a chat interface, for example, proximate to a keyboard element. In some embodiments, the presentation of the suggested content is displayed responsive to receiving a user input to display the keyboard element. 
     Occasionally, the ranking of the content may result in identical, or nearly identical content to be displayed in a most prominent position among the suggestion content. In some embodiments, the content suggestion system identifies a top ranked portion of the content (e.g., top 6), and randomizes a display order of the top ranked portion of the content in a presentation of the content, in order to provide additional variety and a set of more interesting suggestions to a user. 
       FIG. 1  is a block diagram showing an example messaging system  100  for exchanging data (e.g., messages and associated content) over a network. The messaging system  100  includes multiple client devices  102 , each of which hosts a number of applications including a messaging client application  104 . Each messaging client application  104  is communicatively coupled to other instances of the messaging client application  104  and a messaging server system  108  via a network  106  (e.g., the Internet). 
     Accordingly, each messaging client application  104  is able to communicate and exchange data with another messaging client application  104  and with the messaging server system  108  via the network  106 . The data exchanged between messaging client applications  104 , and between a messaging client application  104  and the messaging server system  108 , includes functions (e.g., commands to invoke functions) as well as payload data (e.g., text, audio, video or other multimedia data). 
     The messaging server system  108  provides server-side functionality via the network  106  to a particular messaging client application  104 . While certain functions of the messaging system  100  are described herein as being performed by either a messaging client application  104  or by the messaging server system  108 , it will be appreciated that the location of certain functionality either within the messaging client application  104  or the messaging server system  108  is a design choice. For example, it may be technically preferable to initially deploy certain technology and functionality within the messaging server system  108 , but to later migrate this technology and functionality to the messaging client application  104  where a client device  102  has a sufficient processing capacity. 
     The messaging server system  108  supports various services and operations that are provided to the messaging client application  104 . Such operations include transmitting data to, receiving data from, and processing data generated by the messaging client application  104 . In some embodiments, this data includes, message content, client device information, geolocation information, media annotation and overlays, message content persistence conditions, social network information, and live event information, as examples. In other embodiments, other data is used. Data exchanges within the messaging system  100  are invoked and controlled through functions available via GUIs of the messaging client application  104 . 
     Turning now specifically to the messaging server system  108 , an Application Program Interface (API) server  110  is coupled to, and provides a programmatic interface to, an application server  112 . The application server  112  is communicatively coupled to a database server  118 , which facilitates access to a database  120  in which is stored data associated with messages processed by the application server  112 . 
     Dealing specifically with the Application Program Interface (API) server  110 , this server receives and transmits message data (e.g., commands and message payloads) between the client device  102  and the application server  112 . Specifically, the Application Program Interface (API) server  110  provides a set of interfaces (e.g., routines and protocols) that can be called or queried by the messaging client application  104  in order to invoke functionality of the application server  112 . The Application Program Interface (API) server  110  exposes various functions supported by the application server  112 , including account registration, login functionality, the sending of messages, via the application server  112 , from a particular messaging client application  104  to another messaging client application  104 , the sending of media files (e.g., images or video) from a messaging client application  104  to the messaging server application  114 , and for possible access by another messaging client application  104 , the setting of a collection of media data (e.g., story), the retrieval of a list of friends of a user of a client device  102 , the retrieval of such collections, the retrieval of messages and content, the adding and deletion of friends to a social graph, the location of friends within a social graph, opening and application event (e.g., relating to the messaging client application  104 ). 
     The application server  112  hosts a number of applications and subsystems, including a messaging server application  114 , an image processing system  116 , a social network system  122 , and a content suggestion system  124 . The messaging server application  114  implements a number of message processing technologies and functions, particularly related to the aggregation and other processing of content (e.g., textual and multimedia content) included in messages received from multiple instances of the messaging client application  104 . As will be described in further detail, the text and media content from multiple sources may be aggregated into collections of content (e.g., called stories or galleries). These collections are then made available, by the messaging server application  114 , to the messaging client application  104 . Other processor and memory intensive processing of data may also be performed server-side by the messaging server application  114 , in view of the hardware requirements for such processing. 
     The application server  112  also includes an image processing system  116  that is dedicated to performing various image processing operations, typically with respect to images or video received within the payload of a message at the messaging server application  114 . 
     The social network system  122  supports various social networking functions services, and makes these functions and services available to the messaging server application  114 . To this end, the social network system  122  maintains and accesses an entity graph  304  within the database  120 . Examples of functions and services supported by the social network system  122  include the identification of other users of the messaging system  100  with which a particular user has relationships or is “following,” and also the identification of other entities and interests of a particular user. 
     The application server  112  is communicatively coupled to a database server  118 , which facilitates access to a database  120  in which is stored data associated with messages processed by the messaging server application  114 . 
       FIG. 2  is block diagram illustrating further details regarding the messaging system  100 , according to example embodiments. Specifically, the messaging system  100  is shown to comprise the messaging client application  104  and the application server  112 , which in turn embody a number of some subsystems, namely an ephemeral timer system  202 , a collection management system  204  and an annotation system  206 . 
     The ephemeral timer system  202  is responsible for enforcing the temporary access to content, such as personalized avatars (e.g., Bitmoji), permitted by the messaging client application  104  and the messaging server application  114 . To this end, the ephemeral timer system  202  incorporates a number of timers that, based on duration and display parameters associated with a message, collection of messages, or graphical element, selectively display and enable access to messages and associated content via the messaging client application  104 . Further details regarding the operation of the ephemeral timer system  202  are provided below. 
     The collection management system  204  is responsible for managing collections of media (e.g., collections of text, image video and audio data, personalized avatars). In some examples, a collection of content (e.g., messages, including images, video, text and audio) may be organized into an “event gallery” or an “event story.” Such a collection may be made available for a specified time period, such as the duration of an event to which the content relates. For example, content relating to a music concert may be made available as a “story” for the duration of that music concert. The collection management system  204  may also be responsible for publishing an icon that provides notification of the existence of a particular collection to the user interface of the messaging client application  104 . 
     The collection management system  204  furthermore includes a curation interface  208  that allows a collection manager to manage and curate a particular collection of content. For example, the curation interface  208  enables an event organizer to curate a collection of content relating to a specific event (e.g., delete inappropriate content or redundant messages). Additionally, the collection management system  204  employs machine vision (or image recognition technology) and content rules to automatically curate a content collection. In certain embodiments, compensation may be paid to a user for inclusion of user generated content into a collection. In such cases, the curation interface  208  operates to automatically make payments to such users for the use of their content. 
     The annotation system  206  provides various functions that enable a user to annotate or otherwise modify or edit media content associated with a message. For example, the annotation system  206  provides functions related to the generation and publishing of media overlays for messages processed by the messaging system  100 . The annotation system  206  operatively supplies a media overlay to the messaging client application  104  based on a geolocation of the client device  102 . In another example, the annotation system  206  operatively supplies a media overlay to the messaging client application  104  based on other information, such as, social network information of the user of the client device  102 . A media overlay may include audio and visual content and visual effects. Examples of audio and visual content include pictures, texts, logos, animations, and sound effects, as well as animated facial models, such as those generated by the content suggestion system  124 . An example of a visual effect includes color overlaying. The audio and visual content or the visual effects can be applied to a media content item (e.g., a photo) at the client device  102 . For example, the media overlay including text that can be overlaid on top of a photograph generated taken by the client device  102 . In another example, the media overlay includes an identification of a location overlay (e.g., Venice beach), a name of a live event, or a name of a merchant overlay (e.g., Beach Coffee House). In another example, the annotation system  206  uses the geolocation of the client device  102  to identify a media overlay that includes the name of a merchant at the geolocation of the client device  102 . The media overlay may include other indicia associated with the merchant. The media overlays may be stored in the database  120  and accessed through the database server  118 . 
     In one example embodiment, the annotation system  206  provides a user-based publication platform that enables users to select a geolocation on a map, and upload content associated with the selected geolocation. The user may also specify circumstances under which a particular media overlay should be offered to other users. The annotation system  206  generates a media overlay that includes the uploaded content and associates the uploaded content with the selected geolocation. 
     In another example embodiment, the annotation system  206  provides a merchant-based publication platform that enables merchants to select a particular media overlay associated with a geolocation via a bidding process. For example, the annotation system  206  associates the media overlay of a highest bidding merchant with a corresponding geolocation for a predefined amount of time 
       FIG. 3  is a block diagram illustrating components of the content suggestion system  124  that configure the content suggestion system  124  to perform operations that include: causing display of a message within a chat interface at a client device (e.g., client device  102 A), wherein the message includes first content, such as a particular personalized avatar (e.g., a Bitmoji); receiving a selection of second content from the client device  102 A, wherein the second content may include a different personalized avatar to be assigned to a response to the message; incrementing a usage metric corresponding to a content pair that includes the first content and the second content in response to receiving the selection of the second content from the client device  102 A; and ranking the second content among a set of content based on the usage metric of the corresponding content pair, according to some example embodiments. The content suggestion system  124  is shown as including a presentation module  302 , a ranking module  304 , a content selection module  306 , and a communication module  308 , all configured to communicate with each other (e.g., via a bus, shared memory, or a switch). Any one or more of these modules may be implemented using one or more processors  310  (e.g., by configuring such one or more processors to perform functions described for that module) and hence may include one or more of the processors  310 . 
     The presentation module  302  is configured to generate and cause display of presentations of notifications and messages that include content at client device (e.g., the client device  102 A and the client device  102 B), according to some example embodiments. 
     The ranking module  304  is configured to calculate usage metrics of corresponding content pair based on user activity that includes a selection of content via a client device, according to some example embodiments. 
     The content selection module  306  is configured to select and curate a set of content to be presented (e.g., by the presentation module  302 ) as a chat suggestion, based on the ranking by the ranking module  304 , according to some example embodiments. 
     The communication module  308  is configured to facilitate the exchange of messages and communication between client devices and the network  106 , according to certain example embodiments. 
     Any one or more of the modules described may be implemented using hardware alone (e.g., one or more of the processors  310  of a machine) or a combination of hardware and software. For example, any module described of the content suggestion system  124  may physically include an arrangement of one or more of the processors  310  (e.g., a subset of or among the one or more processors of the machine) configured to perform the operations described herein for that module. As another example, any module of the content suggestion system  124  may include software, hardware, or both, that configure an arrangement of one or more processors  310  (e.g., among the one or more processors of the machine) to perform the operations described herein for that module. Accordingly, different modules of the content suggestion system  124  may include and configure different arrangements of such processors  310  or a single arrangement of such processors  310  at different points in time. Moreover, any two or more modules of the content suggestion system  124  may be combined into a single module, and the functions described herein for a single module may be subdivided among multiple modules. Furthermore, according to various example embodiments, modules described herein as being implemented within a single machine, database, or device may be distributed across multiple machines, databases, or devices. 
       FIG. 4  is a flowchart illustrating a method  400  for ranking chat suggestions, according to certain example embodiments. Operations of the method  400  may be performed by the modules described above with respect to  FIG. 3 . As shown in  FIG. 4 , the method  400  includes one or more operations  402 ,  404 ,  406 , and  408 . 
     At operation  402 , the presentation module  302  causes display of a message within a chat interface at a client device  102 A, wherein the message includes first content. For example, the message may be generated by a client device  102 B and transmitted through the network  106  to the client device  102 A. The first content of the message includes media content such as personalized avatar, like a Bitmoji. 
     At operation  404 , the communication module  308  receives a selection of second content at the client device  102 A, wherein the second content is to be assigned to a response to the message displayed at the client device  102 A. For example, a user of the client device  102 A may draft a response to the message by selecting or generating a personalized avatar from among a selection of personalized avatars. 
     At operation  406 , the ranking module  304  increments a usage metric associated with a content pair that includes the first content and the second content in response to receiving the selection of the second content from the client device  102 A. In some embodiments, the database  120  may comprise a set of content pairs based on selections of content. The ranking module  304  may index and store content pairs within the database  120  based on selections of content made by users. For example, a user of the client device  102 A may receive a message that includes first content (e.g., “Bitmoji A”) and in drafting a response, the user of the client device  102 B selects second content (e.g., “Bitmoji B”). In response to the user selecting the second content, the ranking module  304  indexes and stores a content pair that comprises the first content and the second content, and increments a usage metric that defines a number of times in which “Bitmoji B” is sent in response to “Bitmoji A.” At operation  408 , the ranking module  304  ranks the content pair among a set of content pairs based on the corresponding usage metric. 
       FIG. 5  is a flowchart illustrating a method  500  for presenting chat suggestions, according to certain example embodiments. Operations of the method  500  may be performed by the modules described above with respect to  FIG. 3 . The method  500  may be performed as a part of or subsequent to one or more of the operations of the method  400 . As shown in  FIG. 5 , the method  500  includes one or more operations  502 ,  504 , and  506 . 
     At operation  502 , the presentation module  302  generates and causes display of a second message (e.g., a message subsequent to the message displayed in operation  402  of the method  400 ) within the chat interface of the client device  102 A, wherein the second message includes content such as the first content described in the method  400 . 
     In response to displaying the presentation of the second message at the client device  102 A, the content selection module  306  generates a presentation of a set of suggested content based on the content displayed within the second message. The presentation of the set of suggested content includes a display of the second content at a position among the set of suggested content, wherein the position of the second content is based on the ranking of the second content. At operation  506 , the presentation module  302  causes display of the presentation of the set of suggested content within a portion of the chat interface at the client device  102 A. 
       FIG. 6  is a flowchart illustrating a method  600  for presenting chat suggestions, according to certain example embodiments. Operations of the method  600  may be performed by the modules described above with respect to  FIG. 3 . The method  600  may be performed as a part of the method  400  (e.g., a precursor, or subroutine of one of the operations). As shown in  FIG. 6 , the method  600  includes one or more operations  602 ,  604 ,  608 , and  610 . 
     At operation  602 , the presentation module  302  causes display of a message at the client device  102 A, wherein the message includes message content comprising a text string. 
     At operation  604 , in response to displaying the message that comprises the text string at the client device  102 A, the content selection module  306  converts the text string to a tag. The tags may be based on the text string themselves, or may be based on a category. For example, the text string of the message may read, “Hello.” The content selection module  306  may identify a tag that corresponds with various greetings, wherein the tag is associated with one or more items of media content within the database  120 . At operation  606 , the content selection module  306  identifies media content (e.g., the first media content) based on the text string and the tag. 
     At operation  608 , in response to identifying the first content based on the presentation of the second message that includes the text string at the client device  102 A, the content selection module  306  generates a presentation of a set of suggested content based on the first content displayed within the message. The content selection module  306  retrieves the content pairs associated with the first content, and generates the presentation of the set of suggested content based on the content pairs, wherein a sort order of the set of suggested content is based on the usage metrics corresponding to each of the content pairs. 
     At operation  610 , the presentation module  302  causes display of the presentation of the set of suggested content within a portion of the chat interface at the client device  102 A. 
       FIG. 7  is a diagram  700  illustrating a method for ranking chat content to be presented as a chat suggestion, according to certain example embodiments. 
     As discussed above, with respect to the method  400 , the ranking module  304  calculates a usage metric of a content pair and ranks content based on the usage metric. According to some example embodiments, the ranking module  304  may generate one or more matrices (e.g., matrices  702  and  704 ), wherein each row of a matrix (e.g., row  706  and row  708 ) comprises usage metrics of content pairs (i.e., a number of times a particular content pair is used). In some embodiments, the ranking module  304  may generate a personalized matrix (e.g., matrix  702 ), as well as a general matrix (e.g., matrix  704 ), wherein the personalized matrix corresponds to the specific usage metrics of a particular user of the client device  102 A, whereas the general matrix corresponds to the usage metrics of a population of users. 
     The ranking module  304  identifies the highest ranking content pairs based on the usage metrics, and generates sorted index lists  710  and  712 , wherein the sorted index lists comprise a list of content pairs based on content pair identifiers, such as content pair identifier  714  (e.g., “2500”). In some embodiments, the first element (i.e., content pair identifier) in the list corresponds to the highest ranking pair based on usage metrics. 
     The ranking module removes replicates between the sorted index list  710  and  712 , and interleaves the sorted index lists to generate a final interleaved index list  716 , that comprises a set of suggested content. The presentation module  302  generates a presentation of the set of suggested content based on the final interleaved index list  716 . 
       FIG. 8  is an illustration of an interface  800  to display a set of chat suggestions  802 , according to certain example embodiments. As seen in the interface  800  is displayed at a client device  102 A, as described in the method  400  of  FIG. 4 . 
     The presentation module  302  may display a message within the interface  800 , wherein the message comprises first content  804 . As seen in  FIG. 8 , the first content  804  includes a personalized avatar, such as a Bitmoji. 
     In response to receiving the message that includes the first content  804 , the presentation module  302  generates and causes display of the set of suggested content  802 , wherein the set of suggested content  802  is based on the first content  804 . 
       FIG. 9  is an illustration of an interface  900  to display a set of chat suggestions, according to certain example embodiments. As described in the method  600  of  FIG. 6 , the presentation module  302  may generate and cause display of a message (e.g., message  904 ) that comprises first content that may include a text string. 
     In response to receiving the message  904  that includes a text string, the content selection module  306  converts the text string of the message  904  to a tag, and identifies media content (e.g., the first media content) based on the text string and the tag. 
     As explained in operation  608  of the method  600 , in response to identifying the first content based on the tag from the message  904 , the content selection module  306  generates a presentation of a set of suggested content  902  based on the first content associated with the tag. 
     Software Architecture 
       FIG. 10  is a block diagram illustrating an example software architecture  1006 , which may be used in conjunction with various hardware architectures herein described.  FIG. 10  is a non-limiting example of a software architecture and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture  1006  may execute on hardware such as machine  1100  of  FIG. 11  that includes, among other things, processors  1104 , memory  1114 , and I/O components  1118 . A representative hardware layer  1052  is illustrated and can represent, for example, the machine  1000  of  FIG. 10 . The representative hardware layer  1052  includes a processing unit  1054  having associated executable instructions  1004 . Executable instructions  1004  represent the executable instructions of the software architecture  1006 , including implementation of the methods, components and so forth described herein. The hardware layer  1052  also includes memory and/or storage modules memory/storage  1056 , which also have executable instructions  1004 . The hardware layer  1052  may also comprise other hardware  1058 . 
     In the example architecture of  FIG. 10 , the software architecture  1006  may be conceptualized as a stack of layers where each layer provides particular functionality. For example, the software architecture  1006  may include layers such as an operating system  1002 , libraries  1020 , applications  1016  and a presentation layer  1014 . Operationally, the applications  1016  and/or other components within the layers may invoke application programming interface (API) API calls  1008  through the software stack and receive a response as in response to the API calls  1008 . The layers illustrated are representative in nature and not all software architectures have all layers. For example, some mobile or special purpose operating systems may not provide a frameworks/middleware  1018 , while others may provide such a layer. Other software architectures may include additional or different layers. 
     The operating system  1002  may manage hardware resources and provide common services. The operating system  1002  may include, for example, a kernel  1022 , services  1024  and drivers  1026 . The kernel  1022  may act as an abstraction layer between the hardware and the other software layers. For example, the kernel  1022  may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services  1024  may provide other common services for the other software layers. The drivers  1026  are responsible for controlling or interfacing with the underlying hardware. For instance, the drivers  1026  include display drivers, camera drivers, Bluetooth® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audio drivers, power management drivers, and so forth depending on the hardware configuration. 
     The libraries  1020  provide a common infrastructure that is used by the applications  1016  and/or other components and/or layers. The libraries  1020  provide functionality that allows other software components to perform tasks in an easier fashion than to interface directly with the underlying operating system  1002  functionality (e.g., kernel  1022 , services  1024  and/or drivers  1026 ). The libraries  1020  may include system libraries  1044  (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematical functions, and the like. In addition, the libraries  1020  may include API libraries  1046  such as media libraries (e.g., libraries to support presentation and manipulation of various media format such as MPREG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g., an OpenGL framework that may be used to render 2D and 3D in a graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries  1020  may also include a wide variety of other libraries  1048  to provide many other APIs to the applications  1016  and other software components/modules. 
     The frameworks/middleware  1018  (also sometimes referred to as middleware) provide a higher-level common infrastructure that may be used by the applications  1016  and/or other software components/modules. For example, the frameworks/middleware  1018  may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks/middleware  1018  may provide a broad spectrum of other APIs that may be utilized by the applications  1016  and/or other software components/modules, some of which may be specific to a particular operating system  1002  or platform. 
     The applications  1016  include built-in applications  1038  and/or third-party applications  1040 . Examples of representative built-in applications  1038  may include, but are not limited to, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, and/or a game application. Third-party applications  1040  may include an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform, and may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems. The third-party applications  1040  may invoke the API calls  1008  provided by the mobile operating system (such as operating system  1002 ) to facilitate functionality described herein. 
     The applications  1016  may use built in operating system functions (e.g., kernel  1022 , services  1024  and/or drivers  1026 ), libraries  1020 , and frameworks/middleware  1018  to create user interfaces to interact with users of the system. Alternatively, or additionally, in some systems interactions with a user may occur through a presentation layer, such as presentation layer  1014 . In these systems, the application/component “logic” can be separated from the aspects of the application/component that interact with a user. 
       FIG. 11  is a block diagram illustrating components of a machine  1100 , according to some example embodiments, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically,  FIG. 11  shows a diagrammatic representation of the machine  1100  in the example form of a computer system, within which instructions  1110  (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine  1100  to perform any one or more of the methodologies discussed herein may be executed. As such, the instructions  1110  may be used to implement modules or components described herein. The instructions  1110  transform the general, non-programmed machine  1100  into a particular machine  1100  programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine  1100  operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine  1100  may operate in the capacity of 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. The machine  1100  may comprise, but not be 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 telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions  1110 , sequentially or otherwise, that specify actions to be taken by machine  1100 . Further, while only a single machine  1100  is illustrated, the term “machine” shall also be taken to include a collection of machines that individually or jointly execute the instructions  1110  to perform any one or more of the methodologies discussed herein. 
     The machine  1100  may include processors  1104 , memory memory/storage  1106 , and I/O components  1118 , which may be configured to communicate with each other such as via a bus  1102 . The memory/storage  1106  may include a memory  1114 , such as a main memory, or other memory storage, and a storage unit  1116 , both accessible to the processors  1104  such as via the bus  1102 . The storage unit  1116  and memory  1114  store the instructions  1110  embodying any one or more of the methodologies or functions described herein. The instructions  1110  may also reside, completely or partially, within the memory  1114 , within the storage unit  1116 , within at least one of the processors  1104  (e.g., within the processor&#39;s cache memory), or any suitable combination thereof, during execution thereof by the machine  1100 . Accordingly, the memory  1114 , the storage unit  1116 , and the memory of processors  1104  are examples of machine-readable media. 
     The I/O components  1118  may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific I/O components  1118  that are included in a particular machine  1100  will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components  1118  may include many other components that are not shown in  FIG. 11 . The I/O components  1118  are grouped according to functionality merely for simplifying the following discussion and the grouping is in no way limiting. In various example embodiments, the I/O components  1118  may include output components  1126  and input components  1128 . The output components  1126  may 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), haptic components (e.g., a vibratory motor, resistance mechanisms), other signal generators, and so forth. The input components  1128  may include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instrument), tactile input components (e.g., a physical button, a touch screen that provides location and/or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like. 
     In further example embodiments, the I/O components  1118  may include biometric components  1130 , motion components  1134 , environmental environment components  1136 , or position components  1138  among a wide array of other components. For example, the biometric components  1130  may include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram based identification), and the like. The motion components  1134  may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environment components  1136  may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometer that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas detection sensors to detection concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components  1138  may include location sensor components (e.g., a Global Position system (GPS) receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like. 
     Communication may be implemented using a wide variety of technologies. The I/O components  1118  may include communication components  1140  operable to couple the machine  1100  to a network  1132  or devices  1120  via coupling  1122  and coupling  1124  respectively. For example, the communication components  1140  may include a network interface component or other suitable device to interface with the network  1132 . In further examples, communication components  1140  may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices  1120  may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a Universal Serial Bus (USB)). 
     Moreover, the communication components  1140  may detect identifiers or include components operable to detect identifiers. For example, the communication components  1140  may include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components  1140 , such as, location via Internet Protocol (IP) geo-location, location via Wi-Fi® signal triangulation, location via detecting a NFC beacon signal that may indicate a particular location, and so forth. 
     Glossary 
     “CARRIER SIGNAL” in this context refers to any intangible medium that is capable of storing, encoding, or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible medium to facilitate communication of such instructions. Instructions may be transmitted or received over the network using a transmission medium via a network interface device and using any one of a number of well-known transfer protocols. 
     “CLIENT DEVICE” in this context refers to any machine that interfaces to a communications network to obtain resources from one or more server systems or other client devices. A client device may be, but is not limited to, a mobile phone, desktop computer, laptop, portable digital assistants (PDAs), smart phones, tablets, ultra books, netbooks, laptops, multi-processor systems, microprocessor-based or programmable consumer electronics, game consoles, set-top boxes, or any other communication device that a user may use to access a network. 
     “COMMUNICATIONS NETWORK” in this context refers to one or more portions of a network that may 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 Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, a network or a portion of a network may include a wireless or cellular network and the coupling may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or other type of cellular or wireless coupling. In this example, the coupling may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1xRTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard setting organizations, other long range protocols, or other data transfer technology. 
     “EMPHEMERAL MESSAGE” in this context refers to a message that is accessible for a time-limited duration. An ephemeral message may be a text, an image, a video and the like. The access time for the ephemeral message may be set by the message sender. Alternatively, the access time may be a default setting or a setting specified by the recipient. Regardless of the setting technique, the message is transitory. 
     “MACHINE-READABLE MEDIUM” in this context refers to a component, device or other tangible media able to store instructions and data temporarily or permanently and may include, but is not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage (e.g., Erasable Programmable Read-Only Memory (EEPROM)) and/or any suitable combination thereof. The term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions. The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., code) for execution by a machine, such that the instructions, when executed by one or more processors of the machine, cause the machine to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. The term “machine-readable medium” excludes signals per se. 
     “COMPONENT” in this context refers to a device, physical entity or logic having boundaries defined by function or subroutine calls, branch points, application program interfaces (APIs), or other technologies that provide for the partitioning or modularization of particular processing or control functions. Components may be combined via their interfaces with other components to carry out a machine process. A component may be a packaged functional hardware unit designed for use with other components and a part of a program that usually performs a particular function of related functions. Components may constitute either software components (e.g., code embodied on a machine-readable medium) or hardware components. A “hardware component” is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware components of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware component that operates to perform certain operations as described herein. A hardware component may also be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware component may include dedicated circuitry or logic that is permanently configured to perform certain operations. A hardware component may be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC). A hardware component may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware component may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware components become specific machines (or specific components of a machine) uniquely tailored to perform the configured functions and are no longer general-purpose processors. It will be appreciated that the decision to implement a hardware component mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. Accordingly, the phrase “hardware component”(or “hardware-implemented component”) should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which hardware components are temporarily configured (e.g., programmed), each of the hardware components need not be configured or instantiated at any one instance in time. For example, where a hardware component comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware components) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware component at one instance of time and to constitute a different hardware component at a different instance of time. Hardware components can provide information to, and receive information from, other hardware components. Accordingly, the described hardware components may be regarded as being communicatively coupled. Where multiple hardware components exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware components. In embodiments in which multiple hardware components are configured or instantiated at different times, communications between such hardware components may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware components have access. For example, one hardware component may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware component may then, at a later time, access the memory device to retrieve and process the stored output. Hardware components may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information). The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented components that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented component” refers to a hardware component implemented using one or more processors. Similarly, the methods described herein may be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented components. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an Application Program Interface (API)). The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented components may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented components may be distributed across a number of geographic locations. 
     “PROCESSOR” in this context refers to any circuit or virtual circuit (a physical circuit emulated by logic executing on an actual processor) that manipulates data values according to control signals (e.g., “commands”, “op codes”, “machine code”, etc.) and which produces corresponding output signals that are applied to operate a machine. A processor may, for example, be 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) or any combination thereof. A processor may further be a multi-core processor having two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously. 
     “TIMESTAMP” in this context refers to a sequence of characters or encoded information identifying when a certain event occurred, for example giving date and time of day, sometimes accurate to a small fraction of a second. 
     “LIFT” in this context is a measure of the performance of a targeted model at predicting or classifying cases as having an enhanced response (with respect to a population as a whole), measured against a random choice targeting model. 
     “PHONEME ALIGNMENT” in this context, a phoneme is a unit of speech that differentiates one word from another. One phoneme may consist of a sequence of closure, burst, and aspiration events; or, a dipthong may transition from a back vowel to a front vowel. A speech signal may therefore be described not only by what phonemes it contains, but also the locations of the phonemes. Phoneme alignment may therefore be described as a “time-alignment” of phonemes in a waveform, in order to determine an appropriate sequence and location of each phoneme in a speech signal. 
     “AUDIO-TO-VISUAL CONVERSION” in this context refers to the conversion of audible speech signals into visible speech, wherein the visible speech may include a mouth shape representative of the audible speech signal. 
     “TIME DELAYED NEURAL NETWORK (TDNN)” in this context, a TDNN is an artificial neural network architecture whose primary purpose is to work on sequential data. An example would be converting continuous audio into a stream of classified phoneme labels for speech recognition. 
     “BI-DIRECTIONAL LONG-SHORT TERM MEMORY (BLSTM)” in this context refers to a recurrent neural network (RNN) architecture that remembers values over arbitrary intervals. Stored values are not modified as learning proceeds. RNNs allow forward and backward connections between neurons. BLSTM are well-suited for the classification, processing, and prediction of time series, given time lags of unknown size and duration between events.