Patent ID: 12225265

DETAILED DESCRIPTION

FIG.1shows an illustrative system100for identifying a user with a hearing impairment and recommending media content to the user based on the hearing impairment, in accordance with some embodiments of the present disclosure. The system100may include user equipment104(e.g., a television, mobile device, phone, tablet, computer, or any other suitable computing device) and a sensor106(e.g., a camera communicatively coupled to (or integrated with) the user equipment104. The user equipment104is depicted as a television, but may be any user equipment with any functionality described below with respect to at leastFIGS.4and5. The user equipment104may comprise control circuitry (also described in further detail with respect to at leastFIGS.4and5), which executes a content recommendation application. The user equipment104may include a graphical user interface (GUI), which may include one or more GUIs110,122, enabling users to interact with a content recommendation application. The user equipment104, the sensor106, biometrics database114, and user profiles database116may be communicatively coupled via a network (e.g., network506ofFIG.5). In some embodiments, the biometrics database114and user profiles database116may be included in any of media content source502, server504and/or user equipment508,510ofFIG.5.

The content recommendation application may identify users in the vicinity of the user equipment104. For example, as shown, the user102may be viewing the recommend content GUI110provided by the content recommendation application, and the sensor106may capture in real time one or more images of user102. The content recommendation application may analyze an image112of a face of the user102, in order to identify facial characteristics of the user102. For example, the content recommendation application may utilize any suitable facial recognition algorithm and/or image processing techniques to identify or extract various features (e.g., distance between eyes, distance from chin to forehead, shape of jawline, depth of eye sockets, height of cheek bones, overall arrangement of facial features, size and shape of facial features, etc.) of the face of the user102in the image112.

The content recommendation application may compare the identified facial features of user102to facial feature information of users stored in the biometrics database114. Based on such comparisons, the content recommendation application may determine whether there is a match between identified facial features of the user102and facial features of users stored in the biometrics database. In some embodiments, the content recommendation application may compute a similarity score for the comparison and may determine that there is a match if a computed similarity score exceeds a certain threshold.

In some embodiments, the content recommendation application may generate an image signature or facial signature of the user102. For example, the facial signature may comprise a feature vector including numerical values representing the various detected facial features (e.g., a numerical value representing a distance between eyes, a numerical value representing a shape of jawline, etc.), and such feature vector may be compared to feature vectors associated with known faces of users in the biometrics database114.

The content recommendation application may determine, based on the above comparison, that the identified facial features of image112match biometric data for the user102. In response to such determinations, the content recommendation application may retrieve a user profile118for the user102from the user profiles database116. Although facial recognition is described as the method of identifying the user102, this is only one example, and any suitable recommendation method may be used by the content recommendation application to identify the user102. For example, if the content platform the user102is accessing requires the user to log in (e.g., via the user equipment104), the content recommendation application may determine the identity of the user102based on the login information. The content recommendation application may also identify the user102using information obtained from a device associated with the user102(e.g., the user equipment104, a smartwatch, a smartphone, a hearing prosthesis, etc.). In some embodiments, the content recommendation application may identify the user102based on a voice of the user102(e.g., voice recognition). In some embodiments, if a user detected by the content recommendation application does not have a user profile, the content recommendation application may prompt the user to create a profile.

The user profile118may indicate, e.g., various interests of the user, viewing history of the user, prior search queries of the user, prior interactions with media assets by the user, social media interactions by the user related to media assets, etc. In addition, the user profile118may indicate whether the user102has a disability (e.g., a sensory impairment) that may affect the ability of the user102to enjoy certain types of content (e.g., a hearing impairment, a visual impairment, a learning disability, etc.). For example, users with a visual impairment may have a difficult time understanding content with negligible vocal content (e.g., content with many scenes having non-verbal communication, fights, emotional scenes, etc.). Similarly, users with a hearing impairment may have a difficult time understanding content that is not easily capturable in subtitles (e.g., scenes with fast dialogue, scenes with several characters speaking, scenes with a high rate of frame changes with corresponding dialogue, etc.). As shown, the user profile118may indicate that the user102has a hearing impairment120and a severity of the hearing impairment (“50% hearing impairment”).

In some embodiments, the user102may enter a disability (e.g., the disability120) into their user profile118. For example, the content recommendation application may prompt the user102to submit any disabilities. In some embodiments, the content recommendation application may determine a disability of a user through a sensory impairment test. For example, the content recommendation application may administer a hearing test by playing a series of sounds through a speaker of the user equipment104and prompting the user to indicate if they heard each of the sounds. Based on the user response, the content recommendation application may determine if the user has a hearing impairment, and, if so, a level of the hearing impairment. Similarly, the content recommendation application may administer a vision test by displaying a series of symbols on the user equipment104and prompting the user to indicate if they are able to identify each of the symbols. Based on the user response, the content recommendation application may determine if the user has a visual impairment, and, if so, a level of the visual impairment. In some embodiments, when administering a hearing impairment test or visual impairment test, the content recommendation application may account for factors that may affect the test (e.g., a distance of the user from the user equipment104, a noise level in the vicinity of the user equipment104, etc.). In some embodiments, the content recommendation application may retrieve a medical history of the user to determine a disability of the user. In some embodiments, the content recommendation application may determine a disability of the user by monitoring the user's interactions with the user equipment104(e.g., by monitoring volume levels over time, subtitle settings, etc.).

In response to retrieving the user profile118of the user102and determining that the user102has, e.g., a “50% hearing impairment,” the media content application may identify media content items to recommend to the user102based on the retrieved user profile118and the type of the disability120and the severity of the type of the disability120. For example, as shown, GUI122may be generated for presentation to the user102, including an identifier124for an identified media content item (“Transformers”) with a high hearing impairment favorability factor126(i.e., 92%). That is, as explained in further detail in reference toFIG.3, the content recommendation application may recommend a media content item that a user with a hearing impairment is able to comprehend. For example, because “Transformers” is a media content item with mostly fight scenes and explosions without much verbal content, the user102may be able to easily comprehend the media content item, despite their hearing impairment. In some embodiments, a plurality of media content items may be identified based on the user profile118(e.g., various interests of the user102, viewing history of the user102, prior search queries of the user102, prior interactions with content media items by the user102, social media interaction by the user102related to media content items, etc.), and one or more of these identified content items may be selected based on a favorability factor of each of the identified media content items for the determined disability120of the user102(e.g., the favorability factor may be used as a factor in recommending media content items). In some embodiments, the determined disability120may be used as a factor in selecting a media content item, along with other factors in the user profile118. In response to the user102selecting the identifier124, the corresponding media content item may be generated for presentation on the user equipment104.

In some embodiments, when a media content item (e.g., corresponding to the selected identifier124) is generated for presentation on the user equipment104, the media content application may determine if any modified audio streams are available for the media content item. For example, the media content application may determine if there are any modified audio streams that are easier for a user with a hearing impairment to understand (e.g., reduced background noise, increased verbal content levels relative to other volume levels, optimized for different types of hearing prostheses such as a cochlear implant, a bone conduction device, a middle ear implant, a brain stem implant, etc.). In some embodiments, if multiple modified audio streams are available, the media content application may select the modified audio stream that best improves understanding for the particular user. For example, if the media content application determines that the user102has a cochlear implant and determines that a modified audio stream that is optimized for users with cochlear implants exists, the media content application may generate the media content item for presentation on the user equipment104with the modified audio stream. In some embodiments, if the user102has a wired/wireless hearing aid/headphone(s) that is able to receive and reproduce audio content (e.g., via a speaker), the media content application may transmit an audio stream directly to the hearing aid/headphone(s). In this way, if multiple users are consuming the media content item (e.g., including users without hearing impairments), the volume of the audio stream being produced by the user equipment104may be played at a normal level, while the user102may adjust the level of the audio stream in their hearing aid/headphone(s). In some embodiments, if the user102has a device capable of displaying subtitles (e.g., a smartphone), the media content application may display subtitles on the device so that subtitles do not need to be displayed on a main display viewed by multiple users (e.g., the user equipment104).

FIG.2shows an illustrative system200for identifying a user with a visual impairment and recommending media content to users based on the visual impairment, in accordance with some embodiments of the present disclosure. The system200may include user equipment204, a sensor206, biometrics database214, and user profiles database216. The system200may correspond to the system100described above with reference toFIG.1.

The content recommendation application may identify users in the vicinity of the user equipment204. For example, as shown, users202and203may be viewing a recommended content GUI210provided by the content recommendation application, and the sensor206may capture in real time one or more images of the users202and203. The content recommendation application may analyze images212and213of the respective faces of the users202and203, in order to identify facial characteristics of the users202and203, and identify the users202and203based on a comparison with features stored in the biometrics database214, using the techniques described above with reference toFIG.1. It should be understood that the content recommendation application may identify the users202and203using any other suitable technique (e.g., as described above with reference toFIG.1).

The content recommendation application may retrieve, from the user profiles database216, a user profile218based on the identity of the user202and a user profile219based on the identity of the user203. The content recommendation application may analyze the user profiles218and219to determine if either of the users202and203has a disability. For example, as shown, the user profile218may indicate that the user202does not have a disability220(“None”), while the user profile219may indicate that the user203has a visual impairment221(“80% visual impairment”).

In response to retrieving the user profiles218and219of the users202and203and determining that the use202does not have a disability and that user203has an “80% visual impairment,” the media content application may identify media content items to recommend to the users202and203based on the retrieved user profiles218and219and the type of the disability221. For example, as shown, a GUI222may be generated for presentation to the users202and203, including identifiers224and225for identified media content items (“GoodFellas” and “Twelve Angry Men”). As shown, “GoodFellas” may have an average visual impairment favorability factor226(“71%”), and “Twelve Angry Men” may have a high visual impairment favorability factor227(“94%”). In some embodiments, when the content recommendation application identifies multiple users, at least one of whom does not have a disability, the content recommendation application may recommend some media content items with a high favorability factor and some media content items with a lower favorability factor. In some embodiments, it may be advantageous to recommend only media content items with a minimum favorability factor so that all of the users in the vicinity of the user equipment204may comprehend and enjoy the media content items. Although the visual impairment favorability factors226and227are included in the GUI222, this is only an example, and the visual impairment favorability factors226and227may be output by a speaker of the user equipment204(e.g., if the user203is using an accessibility mode such as a screen reader).

Although only a visual impairment and a hearing impairment are discussed above, it should be understood that the systems and processes described herein may be applied to other types of disabilities that may affect the ability of a user to comprehend certain types of content. As one example, if a user has a learning disability, the content recommendation application may recommend media content items that are easy for a user with a learning disability to understand. As another example, if a user is prone to seizures, the content recommendation application may recommend media content items that are unlikely to cause a seizure (e.g., media content items that do not include quickly changing scenes or quickly changing brightness).

FIG.3shows an illustrative table300of favorability factors for a plurality of media content items, in accordance with some embodiments of the present disclosure. As shown, the table300includes three media content items (e.g., corresponding to the identifiers124,224, and225ofFIGS.1and2). For each of the media content items, the content recommendation application may determine a total duration of scenes302, a duration of scenes with a vocal output (e.g., dialogue) greater than a threshold304, and a duration of scenes easily capturable in subtitles306. As shown, based on these variables302,304, and306, the content recommendation application may determine a visual impairment favorability factor (“FV”)308and a hearing impairment favorability factor (“FH”)310for each of the media content items.

In some embodiments, to determine the variables302,304, and306for each of the media content items, the content recommendation application may retrieve metadata associated with each media content item. The metadata may include metadata specific to each scene (e.g., segment) of a media content item, such as the identification of the scene, the length of the scene, the visual and audio content of the scene, etc. However, this is only an example, and the content recommendation application may also perform image and audio processing to generate metadata for each of the media content items. In some embodiments, the content recommendation application may analyze the metadata for each of the media content items to identify portions of the media content items that do not correspond to the storyline of the media content items (e.g., the credits) and exclude these portions from the calculations of the variables302,304,306. For example, as shown, the content recommendation application may determine the total duration of scenes302of “Transformers,” which has a listed runtime of 144 minutes, as 130 minutes. Similarly, the content recommendation may determine the total duration of scenes302of “GoodFellas” and “Twelve Angry Men” as 140 minutes and 90 minutes, respectively.

In some embodiments, the content recommendation application may analyze the metadata of each scene of the media content item to determine the duration of scenes with vocal output greater than a threshold (e.g., the variable304). For example, for each scene, the content recommendation application may determine the number of words in the scene and the length of the scene and calculate the words per minute for the scene. The content recommendation application may compare the words per minute for the scene with a threshold value (e.g., five words a minute) to determine if the scene should be counted as a scene with vocal output (e.g., to exclude scenes with negligible vocal output). For example, as shown, the content recommendation application may determine the duration of scenes with vocal output greater than a threshold (e.g., the variable304) of “Transformers,” “GoodFellas,” and “Twelve Angry Men” as 80 minutes, 120 minutes, and 85 minutes, respectively. In some embodiments, the threshold value may be adjusted by the user or adjusted based on the severity of the user disability. However, this is only an example, and the duration of vocal output with respect to a duration of the media content may be determined based on a duration of all of the verbal outputs in a media content item and the duration of the media content item (e.g., the variable302) in order to determine a rate of words per minute or other unit of time for the media asset.

In some embodiments, the content recommendation application may analyze the metadata of each scene of the media content item to determine the duration of scenes easily capturable by subtitles (e.g., variable306). For example, for each scene, the content recommendation application may determine if the vocal output exceeds a certain threshold words per minute (e.g., eighty) or if the vocal output switches between more than a threshold number of speaking characters per minute (e.g., six characters). In some embodiments, these thresholds may be adjusted by the user or adjusted based on the severity of the user disability or a reading ability of the user. In some embodiments, the content recommendation application may use a combination of the words per minute and the number of speaking characters per minute to determine if the scene is easily capturable by subtitles. In some embodiments, if the scene includes descriptions that are displayed as subtitles, the content recommendation application may adjust (e.g., lower) the threshold words per minute or threshold number of speaking characters based on the descriptions. In some embodiments, the content recommendation application may determine that a scene is easily capturable by subtitles if the total number of words to be displayed via subtitles (e.g., corresponding to characters, descriptions, and spoken words) is less than a threshold number of words per minute (e.g., sixty-five). Based on the duration of all the scenes that are determined to be easily capturable in subtitles, the content recommendation application may determine the variable306. For example, as shown, the content recommendation application may determine the duration of scenes easily capturable in subtitles (e.g., the variable306) of “Transformers,” “GoodFellas,” and “Twelve Angry Men” as 120 minutes, 100 minutes, and 30 minutes, respectively.

Based on the determined variables302,304, and306for each of the media content items, the content recommendation application may determine a visual impairment favorability factor (“FV”)308and a hearing impairment favorability factor (“FH”)310for each of the media content items. The visual impairment favorability factor308of a media content item corresponds to an estimated ability of a user with a hearing impairment to comprehend that media content item. For example, it may be difficult for a user with a visual impairment (e.g., the user102ofFIG.1) to comprehend media content that has very negligible vocal output (e.g., scenes with non-verbal communication, emotional scenes, fights, etc.). The content recommendation application may calculate the visual impairment favorability factor308by dividing the variable304by the variable302. Similarly, the hearing impairment favorability factor310of a media content item corresponds to an estimated ability of a user with a visual impairment to comprehend that media content item. For example, it may be difficult for a user with a hearing impairment (e.g., the user203ofFIG.2) to comprehend media content that has very quick vocal outputs or dialogues (e.g., scenes with many characters speaking, characters speaking very quickly, etc.). The content recommendation application may calculate the hearing impairment favorability factor310by dividing the variable306by the variable302. A high favorability factor for a disability means that a user with that disability will have a high likelihood of comprehending the corresponding media content item.

For example, as shown, the content recommendation application may determine that “Transformers” has a visual impairment favorability factor308of “62% and a hearing impairment favorability factor310of “92%” (e.g., “Transformers,” which consists mostly of fight scenes and explosions without much verbal content, is an excellent candidate for a user with a hearing impairment, but not a good candidate for a user with a visual impairment). Similarly, as shown, the content recommendation application may determine that “GoodFellas” has a visual impairment favorability factor308of “86%” and a hearing impairment favorability factor310of “71%” (e.g., “GoodFellas, which consists of a mix of verbal content and scenes that are easily capturable by subtitles, is a good candidate for a user with a visual impairment and an acceptable candidate for a user with a hearing impairment). Also, as shown, the content recommendation application may determine that “Twelve Angry Men” has a visual impairment favorability factor308of “94%” and a hearing impairment favorability factor310of “33%” (e.g., “Twelve Angry Men,” which consists mostly of verbal content in a jury room, is an excellent candidate for a user with a visual impairment, but not a good candidate for a user with a hearing impairment). In some embodiments, a hearing impairment favorability factor may be adjusted based on the availability of modified audio streams for a media content item. For example, if a media content item has modified audio streams that are easier for a user with a hearing impairment to understand (e.g., reduced background noise, increased verbal content levels relative to other volume levels, optimized for different types of hearing prostheses such as a cochlear implant, a bone conduction device, a middle ear implant, a brain stem implant, etc.), the determined hearing impairment favorability factor may be increased.

Although only three media content items are discussed with reference toFIG.3, it should be understood that a visual impairment favorability factor and a hearing impairment favorability factor may be calculated for each media asset recommendation candidate. In some embodiments, it may be advantageous to determine favorability factors of media content items in advance of determining any recommendations and accessing the favorability factors from a database when recommending media content items.

FIGS.4-5describe exemplary devices, systems, servers, and related hardware for identifying disabilities of users and recommending media content to the users based on the identified disabilities, in accordance with some embodiments of the present disclosure.FIG.4shows generalized embodiments of illustrative user equipment devices400and401. For example, user equipment device400may be a tablet or smartphone device. In another example, user equipment system401may be a user television equipment system (e.g., the user equipment104or204). In another example, the user equipment system401may be a stereo or other audio playback device. The user television equipment system401may include a set-top box416. The set-top box416may be communicatively connected to a camera418, a speaker414, and a display412. In some embodiments, the camera may detect users viewing the display. In some embodiments, the display412may be a television display or a computer display. In some embodiments, the set-top box416may be communicatively connected to a user input interface410. In some embodiments, the user input interface410may be a remote control device. The set-top box416may include one or more circuit boards. In some embodiments, the circuit boards may include processing circuitry, control circuitry, and storage (e.g., RAM, ROM, hard disk, removable disk, etc.). In some embodiments, the circuit boards may include an input/output path. More specific implementations of user equipment devices are discussed below in connection withFIG.5. Each one of the user equipment device400and the user equipment system401may receive content and data via input/output (I/O) path402. The I/O path402may provide content (e.g., broadcast programming, on-demand programming, Internet content, content available over a local area network (LAN) or wide area network (WAN), and/or other content) and data to control circuitry404, which includes processing circuitry406and a storage408. The control circuitry404may be used to send and receive commands, requests, and other suitable data using the I/O path402. The I/O path402may connect the control circuitry404(and specifically the processing circuitry406) to one or more communications paths (described below). I/O functions may be provided by one or more of these communications paths, but are shown as a single path inFIG.4to avoid overcomplicating the drawing.

The control circuitry404may be based on any suitable processing circuitry such as the processing circuitry406. As referred to herein, processing circuitry should be understood to mean circuitry based on one or more microprocessors, microcontrollers, digital signal processors, programmable logic devices, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc., and may include a multi-core processor (e.g., dual-core, quad-core, hexa-core, or any suitable number of cores) or supercomputer. In some embodiments, processing circuitry may be distributed across multiple separate processors or processing units, for example, multiple of the same type of processing units (e.g., two Intel Core i7 processors) or multiple different processors (e.g., an Intel Core i5 processor and an Intel Core i7 processor). In some embodiments, the control circuitry404executes instructions for a media guidance application stored in memory (i.e., the storage408). Specifically, the control circuitry404may be instructed by the media guidance application to perform the functions discussed above and below. In some implementations, any action performed by the control circuitry404may be based on instructions received from the media guidance application.

In client/server-based embodiments, the control circuitry404may include communications circuitry suitable for communicating with a media guidance application server or other networks or servers. The instructions for carrying out the above-mentioned functionality may be stored on a server (which is described in more detail in connection withFIG.5). Communications circuitry may include a cable modem, an integrated services digital network (ISDN) modem, a digital subscriber line (DSL) modem, a telephone modem, an Ethernet card, or a wireless modem for communications with other equipment, or any other suitable communications circuitry. Such communications may involve the Internet or any other suitable communication networks or paths (which is described in more detail in connection withFIG.5). In addition, communications circuitry may include circuitry that enables peer-to-peer communication of user equipment devices, or communication of user equipment devices in locations remote from each other (described in more detail below).

Memory may be an electronic storage device provided as the storage408that is part of the control circuitry404. As referred to herein, the phrase “electronic storage device” or “storage device” should be understood to mean any device for storing electronic data, computer software, or firmware, such as random-access memory, read-only memory, hard drives, optical drives, digital video recorders (DVRs, sometimes called personal video recorders, or PVRs), solid state devices, quantum storage devices, gaming consoles, gaming media, or any other suitable fixed or removable storage devices, and/or any combination of the same. The storage408may be used to store various types of content described herein as well as media guidance application data described above. For example, the storage408may be used to store the calendar data described inFIG.2. In some embodiments, the calendar data may be stored in association with a user profile. Nonvolatile memory may also be used (e.g., to launch a boot-up routine and other instructions). Cloud-based storage, described in relation toFIG.5, may be used to supplement the storage408or instead of the storage408.

The control circuitry404may include video generating circuitry and tuning circuitry, such as one or more analog tuners, one or more MPEG-2 decoders or other digital decoding circuitry, high-definition tuners, or any other suitable tuning or video circuits or combinations of such circuits. Encoding circuitry (e.g., for converting over-the-air, analog, or digital signals to MPEG signals for storage) may also be provided. The control circuitry404may also include scaler circuitry for upconverting and downconverting content into the preferred output format of the user equipment400. The circuitry404may also include digital-to-analog converter circuitry and analog-to-digital converter circuitry for converting between digital and analog signals. The tuning and encoding circuitry may be used by the user equipment device to receive and to display, to play, or to record content. The tuning and encoding circuitry may also be used to receive guidance data. The circuitry described herein, including for example, the tuning, video generating, encoding, decoding, encrypting, decrypting, scaler, and analog/digital circuitry, may be implemented using software running on one or more general purpose or specialized processors. Multiple tuners may be provided to handle simultaneous tuning functions (e.g., watch and record functions, picture-in-picture (PIP) functions, multiple-tuner recording, etc.). If the storage408is provided as a separate device from the user equipment device400, the tuning and encoding circuitry (including multiple tuners) may be associated with the storage408.

A user may send instructions to the control circuitry404using the user input interface410. The user input interface410may be any suitable user interface, such as a remote control, mouse, trackball, keypad, keyboard, touchscreen, touchpad, stylus input, joystick, voice recognition interface, or other user input interfaces. The display412may be provided as a stand-alone device or integrated with other elements of each one of the user equipment device400and the user equipment system401. For example, the display412may be a touchscreen or touch-sensitive display. In such circumstances, the user input interface410may be integrated with or combined with display412. The display412may be one or more of a monitor, a television, a display for a mobile device, or any other type of display. A video card or graphics card may generate the output to the display412. The video card may be any processing circuitry described above in relation to the control circuitry404. The video card may be integrated with the control circuitry404. Speakers414may be provided as integrated with other elements of each one of the user equipment device400and the user equipment system401or may be stand-alone units. The audio component of videos and other content displayed on the display412may be played through the speakers414. In some embodiments, the audio may be distributed to a receiver (not shown), which processes and outputs the audio via speakers414.

The media guidance application may be implemented using any suitable architecture. For example, it may be a stand-alone application wholly implemented on each one of the user equipment device400and the user equipment system401. In such an approach, instructions of the application are stored locally (e.g., in the storage408), and data for use by the application is downloaded on a periodic basis (e.g., from an out-of-band feed, from an Internet resource, or using another suitable approach). The control circuitry404may retrieve instructions of the application from the storage408and process the instructions to recommend media content items as discussed. Based on the processed instructions, the control circuitry404may determine what action to perform when input is received from the user input interface410. For example, movement of a cursor on a display up/down may be indicated by the processed instructions when the user input interface410indicates that an up/down button was selected.

In some embodiments, the media guidance application is a client/server-based application. Data for use by a thick or thin client implemented on each one of the user equipment device400and the user equipment system401is retrieved on demand by issuing requests to a server remote to each one of the user equipment device400and the user equipment system401. In one example of a client/server-based guidance application, the control circuitry404runs a web browser that interprets web pages provided by a remote server. For example, the remote server may store the instructions for the application in a storage device. The remote server may process the stored instructions using circuitry (e.g., the control circuitry404) and identify user disabilities and recommend media content items based on the type of disabilities as discussed.

In some embodiments, the media guidance application is downloaded and interpreted or otherwise run by an interpreter or virtual machine (run by the control circuitry404). In some embodiments, the media guidance application may be encoded in the ETV Binary Interchange Format (EBIF), received by the control circuitry404as part of a suitable feed, and interpreted by a user agent running on the control circuitry404. For example, the media guidance application may be an EBIF application. In some embodiments, the media guidance application may be defined by a series of JAVA-based files that are received and run by a local virtual machine or other suitable middleware executed by control circuitry404. In some of such embodiments (e.g., those employing MPEG-2 or other digital media encoding schemes), the media guidance application may be, for example, encoded and transmitted in an MPEG-2 object carousel with the MPEG audio and video packets of a program.

FIG.5is a diagram of an illustrative media system, in accordance with some embodiments of the disclosure. User equipment devices508and510(such as the user equipment104or204) may be coupled to communication network506. The communication network506may be one or more networks including the Internet, a mobile phone network, mobile voice or data network (e.g., a 4G or LTE network), cable network, public switched telephone network, or other types of communication network or combinations of communication networks. Paths (e.g., depicted as arrows connecting the respective devices to the communication network506) may separately or together include one or more communications paths, such as a satellite path, a fiber-optic path, a cable path, a path that supports Internet communications (e.g., IPTV), free-space connections (e.g., for broadcast or other wireless signals), or any other suitable wired or wireless communications path or combination of such paths. Communications with the client devices may be provided by one or more of these communications paths but are shown as a single path inFIG.5to avoid overcomplicating the drawing.

Although communications paths are not drawn between user equipment devices, these devices may communicate directly with each other via communications paths such as short-range communication paths, point-to-point communications paths, such as USB cables, IEEE 1394 cables, wireless paths (e.g., Bluetooth, infrared, IEEE 802-11x, etc.), or other short-range communication via wired or wireless paths. The user equipment devices may also communicate with each other directly through an indirect path via the communication network506.

The system500includes a media content source502and a server504. Communications with the media content source502and the server504may be exchanged over one or more communications paths but are shown as a single path inFIG.5to avoid overcomplicating the drawing. In addition, there may be more than one of each of the media content source502and the server504, but only one of each is shown inFIG.5to avoid overcomplicating the drawing. If desired, the media content source502and the server504may be integrated as one source device.

In some embodiments, the server504may include control circuitry511and a storage514(e.g., RAM, ROM, hard disk, removable disk, etc.). The server504may also include an input/output path512. The I/O path512may provide device information, or other data, over a local area network (LAN) or wide area network (WAN), and/or other content and data to the control circuitry511, which includes processing circuitry, and the storage514. The control circuitry511may be used to send and receive commands, requests, and other suitable data using the I/O path512. The I/O path512may connect the control circuitry511(and specifically processing circuitry) to one or more communications paths.

The control circuitry511may be based on any suitable processing circuitry such as one or more microprocessors, microcontrollers, digital signal processors, programmable logic devices, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc., and may include a multi-core processor (e.g., dual-core, quad-core, hexa-core, or any suitable number of cores) or supercomputer. In some embodiments, control circuitry511may be distributed across multiple separate processors or processing units, for example, multiple of the same type of processing units (e.g., two Intel Core i7 processors) or multiple different processors (e.g., an Intel Core i5 processor and an Intel Core i7 processor). In some embodiments, the control circuitry511executes instructions for an emulation system application stored in memory (e.g., the storage514). Memory may be an electronic storage device provided as the storage514that is part of the control circuitry511.

The server504may retrieve guidance data from media content source502, process the data as will be described in detail below, and forward the data to the user equipment devices508and510. The media content source502may include one or more types of content distribution equipment including an audio distribution facility, a television distribution facility, cable system headend, satellite distribution facility, programming sources (e.g., television broadcasters, such as NBC, ABC, HBO, etc.), intermediate distribution facilities and/or servers, Internet providers, on-demand media servers, and other content providers. NBC is a trademark owned by the National Broadcasting Company, Inc., ABC is a trademark owned by the American Broadcasting Company, Inc., and HBO is a trademark owned by the Home Box Office, Inc. Media content source502may be the originator of content (e.g., a television broadcaster, a Webcast provider, etc.) or may not be the originator of content (e.g., an on-demand content provider, an Internet provider of content of broadcast programs for downloading, etc.). The media content source502may include cable sources, satellite providers, on-demand providers, Internet providers, over-the-top content providers, or other providers of content. The media content source502may also include a remote media server used to store different types of content (including video content selected by a user), in a location remote from any of the client devices.

Client devices may operate in a cloud computing environment to access cloud services. In a cloud computing environment, various types of computing services for content sharing, storage or distribution (e.g., video sharing sites or social networking sites) are provided by a collection of network-accessible computing and storage resources, referred to as “the cloud.” For example, the cloud can include a collection of server computing devices (such as, e.g., server504), which may be located centrally or at distributed locations, that provide cloud-based services to various types of users and devices connected via a network (such as the Internet) via communication network506. In such embodiments, user equipment devices may operate in a peer-to-peer manner without communicating with a central server.

FIG.6depicts a flowchart of illustrative steps for identifying disabilities of users and recommending media content to the users based on the identified disabilities, in accordance with some embodiments of the present disclosure. The process600may be executed by the control circuitry404(e.g., in a manner instructed to the control circuitry404by the content recommendation application). The control circuitry404may be part of user equipment (e.g., a device that may have any or all of the functionality of the user equipment devices508or510), or of a remote server separated from the user equipment by way of the communication network506, or distributed over a combination of both. It should be noted that the process600, or any step thereof, could be performed on, or provided by, any of the devices shown inFIGS.1,2,4, and5.

The process600begins at step602when the content recommendation application (e.g., via control circuitry404) may identify users (e.g., user102ofFIG.1or users202and203ofFIG.2) in the vicinity of user equipment (e.g., user equipment104ofFIG.1or user equipment204ofFIG.2). In some embodiments, facial recognition techniques may be used to identify the user. For example, an image (e.g., image112ofFIG.1or images212and213ofFIG.2) of a user may be captured by way of a sensor (e.g., sensor106ofFIG.1or sensor206ofFIG.2), and image processing and facial recognition techniques may be used to identify the user (e.g., by comparing extracted facial characteristics to facial characteristics of users in a database (e.g., biometrics database114ofFIG.1or biometrics database214ofFIG.2). In some embodiments, a user may be identified by a profile currently logged into the user equipment or by information obtained from a device associated with the user. In some embodiments, the user may be identified using voice recognition techniques.

At604, the content recommendation application (e.g., via control circuitry404) may query a database (e.g., user profiles database116ofFIG.1or user profiles database216ofFIG.2) based on the identity of the user to obtain a profile (e.g., user profile118ofFIG.1or user profiles218and219ofFIG.2) associated with the identified user.

At606, the content recommendation application (e.g., via control circuitry404) may determine that the user has a disability (e.g., hearing impairment120ofFIG.1or a visual impairment221ofFIG.2) based on the profile of the user. For example, the disability, the type of disability, and the severity of the disability may be stored in the profile of the user.

At608, the content recommendation application (e.g., via control circuitry404) may determine the type of the identified disability of the user (e.g., the hearing impairment120ofFIG.1or the visual impairment221ofFIG.2). In some embodiments, the control circuitry404may also determine the severity of the type of disability (e.g., 50% hearing impairment), as explained in greater detail inFIG.7.

At610, the content recommendation application (e.g., via control circuitry404) may determine a media content item to recommend to the user based on the determined type of disability and a favorability factor of the media content item for the determined type of disability. For example, as explained in greater detail inFIGS.7and8, the control circuitry404may select, as a media content item to recommend, a media content item that a user with the identified disability will be able to easily comprehend. For example, if the user has a hearing impairment, the control circuitry404may recommend a media content item that can easily be captured in subtitles (e.g., “Transformers” ofFIG.1). If the user has a visual impairment, the control circuitry404may recommend a media content item with a large among of vocal content (e.g., “Twelve Angry Men” ofFIG.2).

At612, the content recommendation application (e.g., via control circuitry404) may generate for presentation a GUI (e.g., GUI122ofFIG.1or GUI222ofFIG.2) including identifiers of each recommended media content item (e.g., respective identifiers124,224, and225ofFIGS.1and2).

FIG.7depicts a flowchart of illustrative steps for determining a content item to recommend to the user, in accordance with some embodiments of the present disclosure. Process700is one embodiment of a method for performing steps608and610ofFIG.6and begins after step606. At step702, the content recommendation application (e.g., via the control circuitry404) may determine if the user has a hearing impairment or a visual impairment. For example, the control circuitry404retrieves the type of sensory impairment from the profile of the user. In response to determining that the user has a hearing impairment, the process700proceeds to step704. Otherwise, in response to determining that the user has a visual impairment, the process700proceeds to step714.

At704, the content recommendation application (e.g., via control circuitry404) may determine the severity of the hearing impairment by retrieving the severity of the hearing impairment from the profile (e.g., user profile118ofFIG.1) of the user. In some embodiments, the control circuitry may determine the severity of the hearing impairment by administering a hearing test to the user (e.g., through the user equipment104).

At706, the content recommendation application (e.g., via control circuitry404) may set a hearing impairment threshold value based on the determined severity. For example, if the user has severe hearing loss, the hearing impairment threshold value may be set to a high threshold so that only media content items with a high hearing impairment favorability factor may be recommended to the user (e.g., as explained in further detail in step712).

At708, the content recommendation application (e.g., via control circuitry404) may identify a plurality of media content items based on the profile of the user. For example, the control circuitry404may identify media content items likely to be of interest to the user (e.g., based on various interests of the user, viewing history of the user, prior search queries of the user, prior interactions with media assets by the user, social media interactions by the user related to media assets, etc.). If multiple users are identified (e.g., users202and203ofFIG.2), the media content items may be identified based on profiles of both of the users (e.g., shared interests).

At710, the content recommendation application (e.g., via control circuitry404) may determine a hearing impairment favorability factor for each of the plurality of media content items, as explained in greater detail with reference toFIG.8A. The hearing impairment favorability factor of a media content item corresponds to an estimated ability of a user with a hearing impairment to comprehend that media content item.

At712, the content recommendation application (e.g., via control circuitry404) may select at least one of the plurality of media content items based on the hearing impairment threshold and the hearing impairment favorability factor for each of the plurality of media content items. For example, in some embodiments, the control circuitry404may select the media asset with the highest hearing impairment favorability factor. In some embodiments, if multiple media assets have a hearing impairment favorability factor that exceeds the hearing impairment threshold, the control circuitry404may select the media content item (or multiple content items), based on a popularity value, a ranking corresponding to the profile of the user, profiles of other users in the vicinity of the user equipment, etc.

At714, the content recommendation application (e.g., via control circuitry404) may determine the severity of the visual impairment by retrieving the severity of the visual impairment from the profile (e.g., user profile219ofFIG.2) of the user. In some embodiments, the control circuitry may determine the severity of the visual impairment by administering a vision test to the user (e.g., through the user equipment204).

At716, the content recommendation application (e.g., via control circuitry404) may set a visual impairment threshold value based on the determined severity. For example, if the user has severe vision loss, the visual impairment threshold value may be set to a high threshold so that only media content items with a high visual impairment favorability factor may be recommended to the user (e.g., as explained in further detail in step722).

At718, the content recommendation application (e.g., via control circuitry404) may identify a plurality of media content items based on the profile of the user, as described in step708.

At720, the content recommendation application (e.g., via control circuitry404) may determine a visual impairment favorability factor for each of the plurality of media content items, as explained in greater detail with reference toFIG.8B. The visual impairment favorability factor of a media content item corresponds to an estimated ability of a user with a visual impairment to comprehend that media content item.

At722, the content recommendation application (e.g., via control circuitry404) may select at least one of the plurality of media content items based on the visual impairment threshold and the visual impairment favorability factor for each of the plurality of media content items. For example, in some embodiments, the control circuitry404may select the media asset with the highest visual impairment favorability factor. In some embodiments, if multiple media assets have a visual impairment favorability factor that exceeds the visual impairment threshold, the control circuitry404may select the media content item (or multiple content items), based on a popularity value, a ranking corresponding to the profile of the user, profiles of other users in the vicinity of the user equipment, etc.

FIG.8Adepicts a flowchart of illustrative steps for determining hearing impairment favorability factors of media content items, in accordance with some embodiments of the present disclosure. Process710A is one embodiment of a method for performing step710ofFIG.7and begins after step708. The process710A may be repeated for each of the plurality of media content items identified in step708. In some embodiments, the process710A may be performed in advance for each media content item in a library of content items accessible to the user and stored in a database. At step801, the content recommendation application (e.g., via the control circuitry404) may retrieve metadata for a media content item (e.g., a first one of the plurality of identified media content items). In some embodiments, the metadata for a media content item may be stored in association with the media content item. In some embodiments, the metadata may be retrieved from a media content item metadata database.

At803, the content recommendation application (e.g., via control circuitry404) may determine the duration of scenes of the media content item based on the metadata. In some embodiments, the control circuitry404may exclude certain portions of the media content item (e.g., the credits) from the duration, based on the metadata.

At805, the content recommendation application (e.g., via control circuitry404) may determine the duration of the scenes that are easily capturable by subtitles based on the metadata. For example, if the words per minute to be displayed via subtitles (e.g., corresponding to characters, descriptions, and spoken words) does not exceed a threshold number of words per minute (e.g., sixty-five), the control circuitry404may determine that the scene is easily capturable by subtitles. In some embodiments, the threshold number of words per minute may be adjusted based on the user (e.g., a reading rate of the user).

At807, the content recommendation application (e.g., via control circuitry404) may determine a hearing impairment favorability factor based on a ratio of the duration of the scenes that are easily capturable by subtitles to the duration of scenes of the media asset. For example, as shown inFIG.3, the control circuitry404may determine the hearing impairment favorability factor of “Transformers” as “92%” (e.g., FH=duration of scenes easily capturable by subtitles/duration of scenes).

FIG.8Bdepicts a flowchart of illustrative steps for determining visual impairment favorability factors of media content items, in accordance with some embodiments of the present disclosure. Process720A is one embodiment of a method for performing step720ofFIG.7and begins after step718. The process720A may be repeated for each of the plurality of media content items identified in step718. In some embodiments, the process720A may be performed for each media content item in a library of content items accessible to the user. At step802, the content recommendation application (e.g., via the control circuitry404), retrieves metadata for a media content item (e.g., a first one of the plurality of identified media content items). In some embodiments, the metadata for a media content item may be stored in association with the media content item. In some embodiments, the metadata may be retrieved from a media content item metadata database.

At804, the content recommendation application (e.g., via control circuitry404) may determine the duration of scenes of the media content item based on the metadata, as described in step803.

At806, the content recommendation application (e.g., via control circuitry404) may determine the duration of the scenes with a vocal output greater than a threshold based on the metadata. For example, if a scene includes at least a certain number of words a minute (e.g., five words a minute), the control circuitry404may determine that the scene has a vocal output greater than a threshold (e.g., to exclude scenes with negligible vocal outputs that may not be easily understood by a user with a visual impairment).

At808, the content recommendation application (e.g., via control circuitry404) may determine a visual impairment favorability factor based on a ratio of the duration of the scenes with a vocal output greater than a threshold to the duration of scenes of the media asset. For example, as shown inFIG.3, the control circuitry404may determine the visual impairment favorability factor of “Twelve Angry Men” as “94%” (e.g., FV=duration of scenes with vocal output/duration of scenes).

The processes discussed above are intended to be illustrative and not limiting. One skilled in the art would appreciate that the steps of the processes discussed herein may be omitted, modified, combined and/or rearranged, and any additional steps may be performed without departing from the scope of the invention. For example, the plurality of media content items in step708may be identified based on the corresponding hearing impairment favorability factors and filtered based on the profile of the user. Similarly, the plurality of media content items in step718may be identified based on the corresponding visual impairment favorability factors and filtered based on the profile of the user. More generally, the above disclosure is meant to be exemplary and not limiting. Only the claims that follow are meant to set bounds as to what the present invention includes. Furthermore, it should be noted that the features and limitations described in any one embodiment may be applied to any other embodiment herein, and flowcharts or examples relating to one embodiment may be combined with any other embodiment in a suitable manner, done in different orders, or done in parallel. In addition, the systems and methods described herein may be performed in real time. It should also be noted that the systems and/or methods described above may be applied to, or used in accordance with, other systems and/or methods.