Patent Publication Number: US-11386903-B2

Title: Methods and systems for speech presentation based on simulated binaural audio signals

Description:
RELATED APPLICATIONS 
     This application is a continuation application of U.S. patent application Ser. No. 16/012,704, filed Jun. 19, 2018, and entitled “Methods and Systems for Speech Presentation in an Artificial Reality World,” which is hereby incorporated by reference in its entirety. 
    
    
     BACKGROUND INFORMATION 
     Artificial reality technologies (e.g., virtual reality technology, augmented reality technology, mixed reality technology, etc.) allow users to experience artificial reality worlds. For example, artificial reality worlds may be implemented as partially or fully simulated realities that do not exist in the real world as such, or that do exist in the real world but are difficult, inconvenient, expensive, or otherwise problematic for users to experience in real life (i.e., in a non-simulated manner). Artificial reality technologies may thus provide users with a variety of entertainment experiences, educational experiences, vocational experiences, and/or other enjoyable or valuable experiences that may be difficult or inconvenient for the users to experience otherwise. 
     As in the real world, certain artificial reality worlds may immerse users in complex and chaotic audio environments. For instance, an artificial reality world may include a significant number of people speaking at once, as well as various other types of noise, reverberation, and other sound propagation effects that, in combination, may make it difficult for users to distinguish and understand speech in the artificial reality world. This difficulty to understand may significantly diminish the benefits of the artificial reality experience that the users might otherwise enjoy. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings illustrate various embodiments and are a part of the specification. The illustrated embodiments are merely examples and do not limit the scope of the disclosure. Throughout the drawings, identical or similar reference numbers designate identical or similar elements. 
         FIG. 1  illustrates an exemplary system for speech presentation in an artificial reality world according to principles described herein. 
         FIG. 2  illustrates an exemplary configuration in which the system of  FIG. 1  operates to facilitate understanding of speech presented in an artificial reality world according to principles described herein. 
         FIG. 3  illustrates a perspective view of an exemplary artificial reality world according to principles described herein. 
         FIG. 4  illustrates exemplary aspects that may affect the propagation of sound from a speaker to an avatar within the artificial reality world of  FIG. 3  according to principles described herein. 
         FIG. 5  illustrates an exemplary schematic view of a complex audio environment within the artificial reality world of  FIG. 3  according to principles described herein. 
         FIG. 6  illustrates exemplary operations that may be performed by a speech presentation system to extract auto-transcribable speech signals from a simulated binaural audio signal according to principles described herein. 
         FIG. 7A  illustrates an exemplary media player device that may be used by a user to experience artificial reality media content according to principles described herein. 
         FIG. 7B  illustrates an exemplary artificial reality experience according to principles described herein 
         FIG. 8A  illustrates an exemplary screenshot of a media player device display screen that is presenting a plurality of closed captioning datasets within an artificial reality world according to principles described herein. 
         FIG. 8B  illustrates an exemplary screenshot of a media player device display screen that is presenting a user-selected closed captioning dataset within an artificial reality world according to principles described herein. 
         FIG. 9  illustrates an exemplary speech presentation method for facilitating understanding of speech presented in an artificial reality world according to principles described herein. 
         FIG. 10  illustrates another exemplary speech presentation method for facilitating understanding of speech presented in an artificial reality world according to principles described herein. 
         FIG. 11  illustrates an exemplary computing device according to principles described herein. 
     
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
     Methods and systems for speech presentation in an artificial reality world are described herein. For example, as will be described in more detail below, an exemplary speech presentation system (e.g., an exemplary closed captioning system) may facilitate understanding of speech presented in an artificial reality world by performing, sequentially or concurrently and in any suitable order, one or more of the following operations and/or other operations described herein. 
     First, the speech presentation system may receive a simulated binaural audio signal associated with a media player device that is presenting an artificial reality world to a user of the media player device. The simulated binaural audio signal may be representative of a rendered simulation of sound propagating to an avatar representing the user within the artificial reality world. For example, the simulated binaural audio signal may be a signal configured to simulate for the user what the avatar hears in the audio environment of the artificial reality world (e.g., by including representations of sounds from various sources such as people speaking and other sound sources) and how the avatar hears it (e.g., by taking into account various aspects that affect the propagation of sound to the avatar such as reverberation and echoes in the room, where the avatar is positioned with respect to the sound sources, how the avatar and the sound sources are oriented with respect to one another, etc.). 
     Along with receiving the simulated binaural audio signal, the speech presentation system may further receive acoustic propagation data representative of at least one aspect affecting propagation of sound to the avatar. For example, the acoustic propagation data may represent one or more of the aspects affecting the propagation of sound described above that are accounted for in the simulated binaural audio signal to simulate how the user hears the sound presented to the avatar. 
     Based on the acoustic propagation data, the speech presentation system may extract from the simulated binaural audio signal an auto-transcribable speech signal representative of speech originating from a speaker within the artificial reality world. As used herein, a “speaker” may refer to any sound source from which speech may originate. For example, as will be described in more detail below, speakers may include avatars whose corresponding users are speaking, media content presentations (e.g., two-dimensional video presentations or audio presentations within the artificial reality world) that feature people speaking, non-player characters built into the artificial reality world who are speaking, or the like. Accordingly, an auto-transcribable speech signal may refer to an audio signal that is derived from the simulated binaural audio signal, but that only includes speech from one speaker (rather than multiple speakers who may be speaking concurrently within the artificial reality world), and that has had various aspects affecting the propagation of sound (e.g., noise, echoes, reverberation, distance-based attenuation, etc.) diminished or removed completely to facilitate automatic transcription of the signal by a speech-to-text converter. 
     Based on the auto-transcribable speech signal, the speech presentation system may generate a closed captioning dataset representative of the speech originating from the speaker. For example, a speech-to-text converter may operate on the auto-transcribable speech signal to generate closed captions (i.e., a textual transcription or set of subtitles indicative of what is being said) for the speech originating from the speaker. The system may also provide the closed captioning dataset to the media player device. For example, the system may transmit the closed captioning dataset along with data indicating that the closed captioning dataset corresponds to the speaker (e.g., rather than to another speaker who may be speaking concurrently within the artificial reality world). 
     Speech presentation methods and systems for facilitating understanding of speech presented in an artificial reality world may significantly improve conventional artificial reality systems and provide various benefits to users engaging in artificial reality experiences. For example, by operating directly on a simulated binaural audio signal that is being presented to the user, speech presentation systems described herein may be more versatile and effective than conventional systems would be. For instance, to function properly, conventional systems may require sound input signals to already be filtered and separated out so that the signals are easily transcribable by automated systems without additional processing. Additionally, conventional systems may require that input signals already be correlated with particular speakers so that closed captioning datasets generated may be properly correlated with the proper speakers. 
     In various examples, artificial reality worlds may include extremely complex sound environments with many speakers associated with varied and disparate speech sources such as users using a live chat feature within the artificial reality world, prerecorded speech stored on the media player device, live or prerecorded speech associated with media content presentations being transmitted from media providers (e.g., television providers, video-on-demand providers, web video providers, radio providers, etc.), and so forth. As such, it may not be practical, convenient, or even possible in some examples for a conventional system to receive individual auto-transcribable speech signals pre-correlated to correspond to each of these speech sources, particularly in real time. 
     Unlike conventional systems, the speech presentation systems described herein may be flexibly configured to operate based only on the simulated binaural audio signal (i.e., the input audio that is being rendered for presentation to the user by the media player device) and the acoustic propagation data (which is already known to the system since it was used to render the simulated binaural audio signal). Based only on these readily-available inputs, the speech presentation systems and methods described herein may thus generate closed captioning data for various disparate sources in real time without access to any particular filtered or separated versions of the speech signals or any metadata about the sources from which the signals originate. 
     In this way, the speech presentation methods and systems described herein may facilitate users&#39; understanding of speech presented in artificial reality worlds in various ways. For example, as will be described in more detail below, the speech presentation systems described herein may provide great flexibility to users in being able to read real-time closed captions for speech that the users wish to focus on, while easily ignoring other speech that may be surrounding the respective avatars of the users within the artificial reality world. With this facilitated understanding, users will benefit from enjoyable and effective experiences within artificial reality worlds, even when the artificial reality worlds include complex and chaotic audio environments. 
     Various embodiments will now be described in more detail with reference to the figures. The disclosed systems and methods may provide one or more of the benefits mentioned above and/or various additional and/or alternative benefits that will be made apparent herein. 
       FIG. 1  illustrates an exemplary speech presentation system  100  (“system  100 ”) for facilitating understanding of speech presented in an artificial reality world. As shown, system  100  may include, without limitation, a communication facility  102 , a signal extraction facility  104 , a closed captioning management facility  106 , and a storage facility  108  selectively and communicatively coupled to one another. It will be recognized that although facilities  102  through  108  are shown to be separate facilities in  FIG. 1 , facilities  102  through  108  may be combined into fewer facilities, such as into a single facility, or divided into more facilities as may serve a particular implementation. Each of facilities  102  through  108  may be distributed between multiple devices (e.g., including suitable server-side devices and/or client-side devices) and/or multiple locations as may serve a particular implementation. Additionally, one or more of facilities  102  through  108  may be omitted from system  100  in certain implementations, while additional facilities may be included within system  100  in the same or other implementations. 
     In some examples, facilities  102  through  108  may be configured to operate in real time so as to analyze audio data and generate and provide closed captioning data as quickly as a simulated binaural audio signal is generated and presented to a user by a media player device. As used herein, operations may be performed in “real time” when they are performed immediately and without undue delay. For example, real-time data processing operations associated with an ongoing event (e.g., a virtual social gathering with other users, a real-world sporting event, etc.) may be completed while the event is still ongoing (e.g., rather than after the fact), even if there is some amount of delay such as a few seconds or minutes. As such, real-time operations may provide closed captioning data to facilitate understanding of artificial reality users who are experiencing a real-world event live or at approximately the same time as people attending the real-world event are experiencing it. 
     Each of facilities  102  through  108  may include or be implemented by one or more physical computing devices such as hardware and/or software components (e.g., processors, memories, communication interfaces, instructions stored in memory for execution by the processors, etc.). For instance, the facilities may be implemented using separate computing components unique to each facility, or may be implemented using shared computing components. Each of facilities  102  through  108  will now be described in more detail. 
     Communication facility  102  may be configured to perform various operations associated with requesting, accessing, or otherwise receiving input data for processing by system  100 . For example, communication facility  102  may be configured to receive input data such as a simulated binaural audio signal, acoustic propagation data, and/or any other suitable input as may serve a particular implementation. The simulated binaural audio signal received by communication facility  102  may be associated with (and, in some examples, received from) a media player device that is presenting an artificial reality world to a user of the media player device. The simulated binaural audio signal may be representative of a simulation of sound propagating to an avatar representing the user within the artificial reality world. In other words, rather than receiving individual, separate signals for each of the distinct sounds (e.g., speech instances or other sounds) that may be presented to the avatar in the artificial reality world, communication facility  102  may receive only a single simulated binaural audio signal that includes a mixture of all the distinct sounds as the sounds are being presented to the user (i.e., a simulation of how the sounds would propagate and combine together at the virtual ears of the user&#39;s avatar). 
     Additionally, communication facility  102  may be configured to receive acoustic propagation data representative of various aspects affecting propagation of sound to the avatar within the artificial reality world. For example, acoustic propagation data may describe the different sounds mixed together in the simulated binaural audio signal and how these sounds have originated, mixed, and virtually propagated through the artificial reality world to reach the two ears of the avatar. As will be described in more detail below, acoustic propagation data may include various types of data as may serve a particular implementation. For instance, acoustic propagation data may describe the respective positioning of the avatar and the one or more sound sources (e.g., speakers) within the artificial reality world, the respective orientation of the avatar and the one or more sound sources, the propagation space through which sounds travel to reach the avatar (e.g., details about the walls, floors, ceilings, objects, and other surfaces included within the artificial reality world that may cause sound to echo and reverberate), and so forth. 
     In some examples, speech presentation system may be included within, communicatively coupled with, and/or otherwise associated with an artificial reality provider system that has applied many of the affects that the acoustic propagation data describes onto the sounds. For example, when a user experiencing an artificial reality world speaks into a microphone to utilize a chat feature (i.e., to speak to another user also experiencing the artificial reality world), the artificial reality provider system may receive the audio signal representative of the speaking user&#39;s speech and may apply various affects to it (e.g., echo, reverberation, attenuation, etc.) before mixing it into a simulated binaural audio signal presented to another user. As such, the artificial reality provider system may be able to provide the acoustic propagation data to a speech presentation system to facilitate the speech presentation system in reversing the applied affects for each particular sound source from which sound is originating in the simulated binaural audio signal. 
     To this end, signal extraction facility  104  may be configured to perform this reversal of affects applied to various sounds included within the simulated binaural audio signal, as well as to otherwise separate, filter, and “clean up” the various audio signals mixed into the simulated binaural audio signal. More particularly, signal extraction facility  104  may be configured to extract, from the simulated binaural audio signal and based on the acoustic propagation data, an auto-transcribable speech signal representative of speech originating from a speaker within the artificial reality world. As mentioned above, an auto-transcribable speech signal, as used herein, may refer to a speech signal that has been separated from other overlapping or concurrent speech signals and has been filtered (e.g., by removing propagation affects such as those described above) to a degree that the signal can be automatically transcribed by an automatic speech-to-text converter (e.g., a speech-to-text algorithm, hardware system, software program, or the like). Various details about how auto-transcribable speech signal may be extracted from a simulated binaural audio signal based on acoustic propagation data will be described in more detail below. 
     Closed captioning management facility  106  may be configured to generate a closed captioning dataset representative of the speech originating for the speaker based on the auto-transcribable speech signal extracted by signal extraction facility  104 . Additionally, closed captioning management facility  106  may be configured to provide the closed captioning dataset to the media player device so that the closed captioning dataset may be presented to the user to facilitate the user&#39;s understanding of the speech as it is mixed together with various other sounds in the simulated binaural audio signal representing the complex sound environment of the artificial reality world. 
     Along with generating the closed captioning dataset and other closed captioning datasets for other speech instances mixed into the simulated binaural audio signal, closed captioning management facility  106  may further manage correlation data between different auto-transcribable speech signal (and associated closed captioning datasets) and the corresponding speakers from which the speech signals originate. In other words, closed captioning management facility  106  may be configured to not only convert each extracted auto-transcribable speech signal into a closed captioning dataset, but also to associate the auto-transcribable speech signal and the resultant closed captioning dataset with the speaker with whom they correspond (i.e., from whom the speech originates). As closed captioning management facility  106  provides the closed captioning dataset to the media player device for presentation to the user, correlation metadata indicative of which closed captioning dataset corresponds to which speaker may also be provided to allow the media player device to properly present the closed captions as originating from the appropriate speakers within the artificial reality world. 
     Storage facility  108  may store audio signals (e.g., simulated binaural audio signals, auto-transcribable speech signals, etc.) or buffered portions thereof, acoustic propagation data, program instructions, and/or any other data received, generated, managed, maintained, used, and/or transmitted by facilities  102  through  106 . 
     To illustrate system  100  in operation,  FIG. 2  shows an exemplary configuration  200  in which system  100  operates to facilitate understanding of speech presented in an artificial reality world. As shown in  FIG. 2 , an artificial reality provider system  202  that includes a chat management system  204  and a media content management system  206  is communicatively coupled, by way of a network  208 , with a media player device  210  being used with a user  212 . Additionally, configuration  200  is shown to include system  100 , which is communicatively coupled with artificial reality provider system  202  and media player device  210  by way of network  208  and/or in other ways that will be described. System  100  was described above in relation to  FIG. 1 , and each of the other components in configuration  200  will now be described. 
     Artificial reality provider system  202  may include one or more computing devices (e.g., server computers, database storage centers, etc.) responsible for capturing, accessing, generating, distributing, and/or otherwise providing and curating artificial reality media content (e.g., virtual reality media content, augmented reality media content, etc.) to be delivered to media player devices such as media player device  210 . As such, artificial reality provider system  202  may generate and/or access (e.g., from one or more content creation systems not explicitly shown) artificial reality data such as image data, audio data, and the like. Artificial reality provider system  202  may also process, prepare, and deliver this data in a form that may be used by media player device  210  to present an artificial reality experience to user  212 . 
     In some examples, such as the example illustrated by configuration  200 , artificial reality provider system  200  may be made up of two or more subsystems each configured to perform particular tasks. For example, as shown in  FIG. 2 , chat management system  204  and media content management system  206  are examples of two subsystems that may be included within artificial reality provider system  202 . While systems  204  and  206  are the only subsystems illustrated to be included within artificial reality provider system  202  in configuration  200 , it will be understood that various other subsystems not explicitly shown may also be included within artificial reality provider system  202  or communicatively coupled thereto as may serve a particular implementation. 
     Chat management system  204  may serve as a central hub for hosting all chat communications that may occur within an artificial reality world being generated and provided by artificial reality provider system  202 . For example, as user  212  and other users experiencing the same artificial reality world using other media player devices (not explicitly shown in  FIG. 2 ) speak to one another, all the voice signals may pass through chat management system  204 . Chat management system  204  may maintain, organize, process, and provide to media player device  210  any chat signals that may be relevant to user  212  (e.g., representative of speech that user  212  may expect to be able to hear based on the position of his or her avatar within the artificial reality world). 
     Chat management system  204  may receive speech signals representative of chat data in any way and/or using any digital or analog voice or data transmission technologies as may serve a particular implementation. For example, chat management system  204  may receive speech signals from users by way of over-the-top (“OTT”) telecommunication serves in which data packets representative of voice communications are delivered over an Internet Protocol (“IP”) network. In other examples, chat management system  204  may receive speech signals by way of more traditional telephonic communication technologies, or any other communication technologies as may serve a particular implementation. 
     In some examples, chat management system  204  may apply various propagation effects to each chat signal provided to media player device  210 . For example, chat management system  204  may apply any of the effects described herein, such as a reverberation effect to simulate natural echoes in the virtual room in which the avatar of user  212  is standing, an attenuation effect to simulate the natural drop-off of the volume as the sound virtually propagates from a speaking avatar to the avatar of user  212 , and so forth. Additionally, chat management system  204  may perform processing to facilitate other aspects of the artificial reality world being generated and provided by artificial reality provider system  202 . For instance, chat management system  204  may perform sound processing to facilitate phoneme animation for the speaking avatar (i.e., to simulate moving of the speaking avatar&#39;s mouth in synchronicity with the speech). 
     Media content management system  206  may perform similar hosting functionality as chat management system  204 , but for media content rather than chat communications between users. For example, within a particular artificial reality world, various media content such as two-dimensional video content (e.g., television, movies, web videos, etc.), three-dimensional video content, and radio or other audio-only content may be presented. For instance, in one exemplary artificial reality world, a virtual sports lounge may include various virtual television sets placed around the lounge area to provide real-time video streaming of the same types of content (e.g., live television channels) as may be presented in a real sports lounge. Accordingly, media content management system  206  may be configured to serve as a central hub for media content presentations that may be presented within the artificial reality world being generated and provided by artificial reality provider system  202 . For example, media content management system  206  may access various live media content streams (e.g., television channels, radio channels, etc.), as well as media content that may be stored within media content management system  206  itself or within another subsystem of artificial reality provider system  202 . Media content management system  206  may maintain, organize, process, and provide to media player device  210  any media content that may be relevant to user  212  (e.g., content user  212  may expect to be able to see and/or hear based on the position of his or her avatar within the artificial reality world). 
     As with chat management system  204 , media content management system  206  may apply various propagation effects to each media content signal it provides to media player device  210 . For example, media content management system  206  may apply any of the effects described herein, such as those described above in relation to chat management system  204 . 
     Network  208  may provide data delivery means between server-side systems such as artificial reality provider system  202  and client-side systems such as media player device  210  in a server-client data delivery architecture such as implemented by configuration  200 . As such, network  208  may include a provider-specific wired or wireless network (e.g., a cable or satellite carrier network, a mobile telephone network, a traditional telephone network, a broadband cellular data network, etc.), the Internet, a wide area network, a content delivery network, and/or any other suitable network or networks, and artificial reality media content may be distributed using any suitable communication technologies included within network  208 . Data may flow between artificial reality provider system  202  and media player device  210  using any communication technologies, devices, media, and protocols as may serve a particular implementation. 
     In certain examples, network  208  may employ mobile edge computing or multi-access edge computing (“MEC”) technologies to enable cloud computing capabilities at the edge of a cellular network (e.g., a 5G cellular network in certain implementations, or any other suitable cellular network associated with any other generation of technology in other implementations). For example, one or more servers included within artificial reality provider system  202  (e.g., servers implementing chat management system  204 , media content management system  206 , closed captioning system  100 , or the like) may be implemented as MEC servers implemented on the edge of the cellular network so as to be communicatively and/or physically closer to client systems (e.g., media player device  210 ) than conventional servers would be in a server-client architecture that does not employ such technologies. In this way, communicative latency between client devices and MEC server devices may be reduced, leading to an artificial reality experience that is more responsive, more efficient, and more immersive and enjoyable to the user. 
     Media player device  210  may be configured to present artificial reality content (e.g., one or more artificial reality worlds) generated and provided by artificial reality provider system  202  to user  212 . For example, media player device  210  may take any of various forms including a head-mounted virtual media content device (e.g., a virtual reality gaming device, a set of augmented reality glasses, etc.), a mobile or wireless device (e.g., a smartphone, a tablet device, etc.), or any other device or configuration of devices that may serve a particular implementation to facilitate receiving and/or presenting artificial reality media content to a user. Media player device  210  may represent one media player device to which an artificial reality world is provided, but it will be understood that a plurality of other similar media player devices may also be provided with the same artificial reality world so as to allow a plurality of other users to experience the artificial reality world concurrently with user  212 . For example, as mentioned above, each of these users may chat with one another and/or with user  212  within the artificial reality world. 
     Along with various streams of video data that may be received from artificial reality provider system  202  (e.g., from subsystems not explicitly shown in configuration  200 ), media player device  210  may also receive streams of audio data from artificial reality provider system  202 . For example, as described above, media player device  210  may receive chat signals from chat management system  204 , as well as audio signals associated with media content presentations from media content management system  206 . Media player device  210  may further receive audio directly from user  212  (e.g., by way of a microphone built into media player device  210 ) and/or may include, stored within a storage device built into media player device  210 , additional audio that may be presented within the artificial reality world (e.g., such as audio associated with a non-player character within a particular artificial reality world, a particular artificial reality game, or the like). 
     Based on all the audio received from all of these sources, as well as based on information known to media player device  210  regarding the current position and orientation of an avatar of user  212  and of sound sources within the artificial reality world, media player device  210  may be configured to generate a simulated binaural audio signal to present to user  212 . For instance, as described above, the simulated binaural audio signal may incorporate and mix together all the different sounds that user  212  may expect to hear in each ear based on sound propagation within the artificial reality world with respect to his or her avatar. In certain examples in which an artificial reality world is particularly complex (i.e., where there are a large number of speakers and/or other sound sources concurrently generating sounds), it may not be possible for media player device  210  to generate the simulated binaural audio signal to a suitable degree of quality in real time due to a lack of processing capability of the media player device. As such, in these examples, media player device  210  may provide information about the user&#39;s position and orientation (e.g., which direction the user&#39;s head is turned to, etc.) to an external system such as artificial reality provider system  202  or a system on the client side of network  208  that has additional processing capabilities, and this external system may generate the simulated binaural audio signal instead. 
     Once the simulated binaural audio signal has been generated, media player device  210  (or the external system that generated the simulated binaural audio signal instead of media player device  210 ) may provide the simulated binaural audio signal to system  100  to allow system  100  to perform the closed captioning operations described herein. 
     System  100  may be implemented as an independent system on either the server side or the client side of the server-client architecture, or may be combined with another system or device in configuration  200  as may serve a particular implementation. For instance, in some examples such as illustrated by an exemplary client-server division  214 - 1 , system  100  may be implemented as a server-side system on the same side of network  208  as artificial reality provider system  202 . Additionally, as illustrated by arrow  216 , system  100  may be implemented within artificial reality provider system  202  (i.e., as an additional subsystem along with systems  204  and  206 ) or may be communicatively coupled directly with artificial reality provider system  202  such that communications with artificial reality provider system  202  may be direct rather by way of network  208 . 
     In other examples, such as illustrated by another exemplary client-server division  214 - 2 , system  100  may be implemented as a client-side system on the same side of network  208  as media player device  210 . Additionally, as illustrated by arrow  218 , system  100  may be implemented within media player device  210  or may be communicatively coupled directly with media player device  210  such that communications with media player device  210  are direct rather than by way of network  208 . 
       FIG. 3  illustrates a perspective view of an exemplary artificial reality world  300 . As shown, an avatar  302  representing user  212  may be included within artificial reality world  300 . In other words, media player device  210  may present to user  212  (e.g., by way of a display screen and speakers included as part of media player device  210 ) the same things that avatar  302  virtually sees and hears in artificial reality world  300 . For example, avatar  302  may virtually see and/or hear a media content presentation  304  including two speakers  306  (i.e., speakers  306 - 1  and  306 - 2 , representing two news anchors on a news program) presented on a two-dimensional display screen (e.g., a virtual television screen or the like) within artificial reality world  300 . As another example, avatar  302  may virtually see and/or hear one or more other avatars such as an avatar  308  illustrated in  FIG. 3 . Various additional objects  310  (e.g., sofas, light fixtures, coffee tables, etc.), as well as various walls  312 , a window  314 , a floor  316 , and other objects not explicitly shown or designated in  FIG. 3  may also be seen and/or heard by avatar  302 . For example, while these inanimate objects  310  through  316  may not themselves act as sound sources, the objects may nevertheless affect the propagation of sound originating from speakers  306  and/or avatar  308 . Additionally, it will be understood that additional sound sources not explicitly shown from the view of  FIG. 3  may also be present within artificial reality world  300  (e.g., additional media content presentations, avatars, and/or other sound sources that are behind avatar  302  and may be heard but not seen by avatar  302  unless the avatar is turned around). 
     Artificial reality world  300  may be implemented using any type of artificial reality technology as may serve a particular implementation. For instance, artificial reality world  300  and the objects, avatars, and media content presentations included therein may generated using virtual reality technology and may be based on any scenery or objects as may serve a particular implementation. As one example, artificial reality world  300  may be an immersive virtual reality world generated based on a live (e.g., real-time) feed of camera-captured scenery of a real-world scene. In other examples, artificial reality world  300  may be an immersive virtual reality world generated based on camera-captured scenery of a real-world scene captured previously, or based on a completely virtualized (e.g., animated) world that does not include camera-captured scenery but, rather, is entirely computer generated. 
     In other implementations, artificial reality world  300  may be implemented using a type of artificial reality that is not completely virtual, such as augmented reality or mixed reality. In these examples, avatar  302  may be implemented by user  212  himself or herself and the room represented by artificial reality world  300  may be the real-world room in which user  212  is actually located. In these examples, certain objects illustrated in artificial reality world  300  may be objects around user  212  in the real world, while other objects may be virtually added to the world. For example, objects  310  may be real-world objects that user  212  may see and interact with (e.g., by sitting on one of the sofas), while avatar  308  may not actually be present in the room with user  212  but may be artificially added to artificial reality world  300  to be heard and seen by user  212 . Other types of artificial reality may function in a similar manner or in any manner as may serve a particular implementation. 
     User  212  may view and interact with various objects included in artificial reality world  300  by way of avatar  302  as user  212  experiences artificial reality world  300 . For example, user  212  may cause avatar  302  to walk into the room, to move around the room (e.g., to approach avatar  308  for a conversation), to sit on the sofa (e.g., to watch media content presentation  304 ), and so forth. Similarly, user  212  may cause avatar  302  to move into other areas or rooms of artificial reality world  300  that are not explicitly illustrated in  FIG. 3 , or to go to other artificial reality worlds that may be available. 
     As user  212  directs avatar  302  to move through artificial reality world  300 , it may be desirable for user  212  to hear sounds (e.g., speech originating from avatar  308  or media content presentation  304 , media content such as music, sound effects such as footsteps, etc.) as they would sound if user  212  were actually located in a real-world space like artificial reality world  300 . To this end, system  100  may identify the position and orientation of avatar  302  and a particular sound source making a particular sound, and apply sound propagation effects to the sound to simulate various aspects of sound propagation. 
     To illustrate,  FIG. 4  shows exemplary aspects that may affect the propagation of sound from a speaker to an avatar within artificial reality world  300 . Specifically, as shown, sound may virtually propagate from a speaker  402  to avatar  302  within artificial reality world  300  in accordance with various propagation aspects including a position  404  of avatar  302 , a position  406  of speaker  402 , an orientation  408  of avatar  302 , an orientation  410  of speaker  402 , a cone of propagation  412  of sound originating from speaker  402 , a head shadow  414  caused by interference of the head and body of avatar  302  with sound originating from speaker  402 , dimensions  416  of artificial reality world  300 , various echoes  418  of the sound from various surfaces  420  within artificial reality world  300 , and so forth as may serve a particular implementation. 
     While speaker  402  is depicted in  FIG. 4  as a loudspeaker symbol, it will be understood that speaker  402  may be any suitable sound source from which speech originates within artificial reality world  300 . For example, speaker  402  may be an additional avatar (e.g., avatar  308  illustrated in  FIG. 3 ) representing, within artificial reality world  300 , an additional user of an additional media player device that is presenting artificial reality world  300  to the additional user concurrently with the presenting of artificial reality world  300  to user  212 . As another example, speaker  402  may be a speaker included on a media content presentation that is received from a media provider distinct from the media player device and is presented within artificial reality world  300 . For instance, speaker  402  may be one of speakers  306 - 1  or  306 - 2 , the news anchors on media content presentation  304  illustrated in  FIG. 3 . 
     As yet another example, speaker  402  may be a non-player character within the artificial reality world. In other words, rather than being an avatar representative of a real person who may wish to chat with user  212 , speaker  402  may be a prerecorded or artificial intelligence (“AI”) character presented based on data stored within the media player device (e.g., programmed into a game or the like that is loaded on the media player device). In some examples, the non-player character may be displayed at a particular place in the world such as at location  406  of speaker  402 . In other examples, however, a non-player character may be displayed on a video overlay that is presented to user  212  in front of the depiction of artificial reality world  300 , may be displayed on a control console within which artificial reality world  300  is presented, may not be displayed at all (e.g., serving as an auto-navigator who speaks into the user&#39;s ears), or may be displayed in any other suitable manner. 
     In still other examples, speaker  402  may be any other source of speech included within artificial reality world  300  as may serve a particular implementation. 
     Regardless of what type of sound source implements speaker  402 ,  FIG. 4  shows that various aspects may affect the virtual propagation of speech from speaker  402  to each of the ears of avatar  302 . For example, the relative positions  404  and  406  of avatar  302  and speaker  402  with respect to one another within artificial reality world  300  may affect the magnitude (e.g., loudness) of sound to be perceived by avatar  302 . Specifically, as the distance between positions  404  and  406  increases, the volume to be perceived by avatar  302  of sound originating from speaker  402  may drop off according to a known fall-off curve. 
     As another exemplary propagation aspect, the relative orientations  408  and  410  of avatar  302  and speaker  402  (i.e., which directions avatar  302  and speaker  402  are facing with respect to one another and with respect to artificial reality world  300 ) may similarly affect how sound is perceived by avatar  302 . For instance, speech originating from speaker  402  may tend to propagate with the greatest magnitude in the direction in which speaker  402  is oriented. This area is illustrated by cone of propagation  412  in  FIG. 4 . As such, a listener who is within cone of propagation  412  may hear speech originating from speaker  402  at a greater overall volume than a listener who is outside of cone of propagation  412  (i.e., who speaker  402  is facing away from). Additionally, along with overall volume effects, certain frequencies may be significantly attenuated outside of cone of propagation  412 , causing speech to sound different for listeners outside of cone of propagation  412 . 
     Similarly, head shadow  414  may represent a somewhat analogous concept for avatar  302  as cone of propagation  412  represents for speaker  402 . That is, just as orientation  410  of speaker  402  affects how sound is projected into artificial reality world  300 , orientation  408  of avatar  302  affects how sound is received from artificial reality world  300 . Specifically, one ear of avatar  302  that is oriented in a direction away from a sound source (e.g., the left ear of avatar  302  in the example of  FIG. 4 ) may receive a lower overall volume and/or a more attenuated version of certain frequencies of the sound due to interference from the head and/or other body parts than the ear that is oriented toward the sound source. This effect is referred to as an interaural level difference (“ILD”). A related phenomenon known as interaural time difference (“ITD”) may also be affected by orientation  408  of avatar  302 , thereby causing sound to arrive at the ear nearer to the sound source prior to arriving at the ear farther from the sound source. ILD and ITD cues may be applied to sounds presented to user  212  to help user  212  to localize sound sources in space (i.e., to determine, based on natural cues, where speaker  402  is within artificial reality world  300  in relation to avatar  302 ). 
     Along with natural propagation effects arising from the respective positions and orientations of speaker  402  and avatar  302  within artificial reality world  300 , various aspects of artificial reality world  300  may further affect how sound propagates from speaker  402  to avatar  302 . For example, dimensions  416  and other physical measurements associated with artificial reality world  300  (e.g., the shape of the room, the height of the ceiling, etc.) may have a direct impact on sound reverberation within artificial reality world  300 . Specifically, echoes  418  off of various surfaces  420  (e.g., walls as well as other surfaces included within artificial reality world  300 ) may arrive to the ears of avatar  302  at different times based on dimensions  416  and other physical aspects of the room. Additionally, the virtual material from which surfaces  420  are constructed (e.g., whether being hard, flat material that efficiently reflects sound, soft or uneven material that absorbs and/or scatters sound, etc.) may further serve as significant propagation aspects that affect speech propagation to avatar  302 . 
     While  FIG. 4  shows an overhead, two-dimensional view of artificial reality world  300 , it will be understood that the propagation aspects illustrated in  FIG. 4  may be determined in three dimensions in a manner analogous to the real world. For instance, positions  404  and  406  may be three-dimensional positions that also include a height component not explicitly illustrated in the view of  FIG. 4 . Similarly, orientations  408  and  410 , cone of propagation  412 , head shadow  414 , and echoes  418  may all be implemented in three dimensions rather than the two dimensions illustrated in  FIG. 4 . 
     While  FIG. 4  illustrates a relatively simple example in which avatar  302  perceives sound from a single speaker  402 , it will be understood that, in certain examples, a plurality of speakers may be concurrently speaking within artificial reality world  300 . As such, in addition to extracting an auto-transcribable speech signal representative of speech from speaker  402 , system  100  may be configured to further extract (e.g., from the same simulated binaural audio signal as contains the speech from speaker  402  and based on the same types of acoustic propagation data) an additional auto-transcribable speech signal representative of additional speech originating from an additional speaker within the artificial reality world. Additionally, based on the additional auto-transcribable speech signal, system  100  may generate an additional closed captioning dataset representative of the additional speech originating from the additional speaker, and may provide the additional closed captioning dataset to the media player device along with the closed captioning dataset. 
     For instance, the additional speaker may be included on a media content presentation that is received from a media provider distinct from the media player device and is presented within artificial reality world  300 , while speaker  402  may be an additional avatar representing, within the artificial reality world, an additional user of an additional media player device (e.g., a media player device that is presenting artificial reality world  300  to the additional user concurrently with the presenting of artificial reality world  300  to user  212 ). In some examples, these auto-transcribable speech signals may be extracted even when at least a portion of the auto-transcribable speech signal and a portion of the additional auto-transcribable speech signal overlap in time so as to correspond to a period of time within artificial reality world  300  when speaker  402  and the additional speaker are speaking concurrently. Additionally, in the same or other examples, system  100  may be configured to correlate the generated closed captioning datasets to their respective speakers. Specifically, for instance, system  100  may provide the closed captioning dataset so as to correspond to the additional avatar, and the additional closed captioning dataset so as to correspond to the media content presentation. 
       FIG. 5  illustrates an exemplary schematic view of a complex audio environment within artificial reality world  300 . Specifically,  FIG. 5  illustrates a top view of artificial reality world  300  in which avatar  302  is presented not only with speech from one speaker, but from a plurality of different speakers  502  (e.g., speakers  502 - 1  through  502 - 9 ). While the propagation aspects described in relation to  FIG. 4  are not explicitly illustrated in  FIG. 5  for clarity, it will be understood that avatar  302  and each of speakers  502  may be associated with some or all of the same propagation effects described above in relation to  FIG. 4 . However, with the significantly larger number of sound sources included in the example of  FIG. 5 , it will be understood that the audio environment of artificial reality world  300  in  FIG. 5  is significantly more complex than the audio environment of artificial reality world  300  in the example of  FIG. 4 . 
     As with speaker  402  in the example of  FIG. 4 , it will be understood that each of speakers  502  may be any type of speaker described herein. For instance, if artificial reality world  300  is implemented as a sports lounge, speaker  502 - 1  may represent a virtual stereo system playing music to be heard throughout the room, speaker  502 - 2  may represent another avatar who is currently chatting with avatar  302 , speakers  502 - 3  through  502 - 5  may represent different characters on a media content presentation playing on a virtual television screen mounted on the wall, and speakers  502 - 6  through  502 - 9  may represent additional avatars within artificial reality world  300  who are chatting amongst themselves (i.e., engaging in conversations not necessarily intended by their respective users to be heard by the user of avatar  302 ). 
     It will be understood that a sports lounge is merely one example of the type of artificial reality world  300  that may be provided for users to experience together. In other examples, artificial reality world  300  may be implemented as an emergency response command center where multiple emergency responders can view multiple media content presentations on multiple screens and talk to one other conveniently to quickly solve problems even without physically being in the same room. In still other examples, artificial reality world  300  may be a VIP room at a virtual concert, a virtual party, a private virtual chatroom for a family or school class reunion, or any other suitable type of artificial reality world configured for use by any number of users for any purpose as may serve a particular implementation. 
     As described above, each of the sound propagation aspects illustrated in  FIG. 4 , as well as other suitable sound propagation aspects, may be accounted for in generating a simulated binaural audio signal to be presented to the user associated with avatar  302  (i.e., user  212 ). As such, it may be desirable for some or all of these aspects to be removed or reversed in order to prepare a signal to be analyzed by a speech-to-text converter to generate a closed captioning dataset. Additionally, in examples such as illustrated in  FIG. 5  where multiple speakers are speaking concurrently, it may be desirable for speech originating from different speakers to be separated in order to prepare the different speech instances to be analyzed by a speech-to-text converter. As used herein, the process of separating out and filtering individual speech signals in preparation for a speech-to-text converter in these ways may be referred to as extracting one or more auto-transcribable speech signals. 
     To illustrate how such extracting may be performed,  FIG. 6  shows an exemplary signal extraction  600  that may be performed by system  100  and that includes various exemplary operations  602  (i.e., operations  602 - 1  through  602 - 5 ) that may be performed to extract one or more auto-transcribable speech signals from a simulated binaural audio signal. System  100  may perform some or all of operations  602  to convert a simulated binaural audio signal  604  into a plurality of auto-transcribable speech signals  608  (i.e., auto-transcribable speech signals  608 - 1  through  608 -N) based on acoustic propagation data  606 . Specifically, simulated binaural audio signal  604  may be processed, concurrently or sequentially in any suitable order, by a noise reduction operation  602 - 1 , a reversing operation  602 - 2 , a feature identification operation  602 - 3 , a speech separation operation  602 - 4 , and a speaker recognition operation  602 - 5 . In some examples, signal extraction  600  may be performed in real time so that closed captions may be generated and displayed live as speakers within artificial reality world  300  are speaking. Each of operations  602  will now be described in more detail. 
     System  100  may perform noise reduction operation  602 - 1  to remove noise from simulated binaural audio signal  604 . As such, noise reduction operation  602 - 1  may increase a signal-to-noise ratio of simulated binaural audio signal  604  in any suitable way, and may involve removing various types of noise. For example, noise reduction operation  602  may remove noise recorded on any of the original speech signals from which simulated binaural audio signal  600  is rendered (e.g., noise in the room while a user is being recorded for a chat communication, background music playing together with speech in a media content presentation, etc.), noise introduced by any transmission or processing of simulated binaural audio signal  604  or its constituent signals prior to signal extraction  600 , noise intentionally introduced onto simulated binaural audio signal  604  to recreate certain elements of artificial reality world  300  (e.g., non-speech sound effects associated with virtual objects included within artificial reality world  300 ), or any other noise as may be present in a particular example. In some examples, certain types of noise may be reduced or removed from simulated binaural audio signal  604  based on acoustic propagation data  606 . 
     In some examples, acoustic propagation data  606  may be representative of a simulated environmental effect that is applied, within simulated binaural audio signal  604 , to speech originating from a speaker in order to simulate the propagation of the speech to the avatar. For example, acoustic propagation data  606  may include data representative of simulated environmental effects that have been applied such as echoes and reverberation, attenuation of the overall volume or of certain frequencies based on the respective position and orientation of the avatar and the speakers, and other such effects described herein. In such examples, it may be desirable for these environmental effects to be reversed (i.e., withdrawn, unapplied, etc.) to prepare a signal for automatic transcribing by a speech-to-text converter. 
     Accordingly, system  100  may perform reversing operation  602 - 2  to reverse the simulated environmental effect or effects that may be applied to the speech represented by simulated binaural audio signal  604 . For example, system  100  may perform reversing operation  602 - 2  based on the acoustic propagation data  606  by performing inverse operations to the operations performed to apply the environmental effects originally. 
     The noise reduction and environmental effect reversal performed in operations  602 - 1  and  602 - 2  may help to filter or “clean up” simulated binaural audio signal  604  to make it easier for a speech-to-text converter to process. However, if simulated binaural audio signal  604  includes a plurality of speech instances (e.g., from a plurality of speakers such as speakers  502  illustrated in the complex audio environment of  FIG. 5 ), any degree of filtering and cleaning up simulated binaural audio signal  604  may still be insufficient to prepare the signal for processing by a speech-to-text converter that is configured to process only one speech instance at a time. Accordingly, simulated binaural audio signal  604  may also be processed by additional operations to break out multiple speech instances (e.g., one for each of the plurality of speakers included within artificial reality world  300 ) that all may be merged together in simulated binaural audio signal  604 . 
     For example, feature identification operation  602 - 3  may be performed to identify, within simulated binaural audio signal  604 , a plurality of features of the sound propagating to the avatar such that speech separation operation  602 - 4  may be performed based on the identified plurality of features of the sound propagating to the avatar. Sound features identified as part of the performance of feature identification operation  602 - 3  may include or be associated with various aspects of speech so as to collectively provide data indicative of a specific identify of a speaker from whom the speech originates. In other words, taken together, the features identified as part of feature identification operation  602 - 3  may serve as a vocal equivalent of a fingerprint, thereby allowing system  100  to positively distinguish one voice from another because system  100  may recognize each voice as belonging to specific known speakers. 
     To this end, the features identified as part of the performance of feature identification operation  602 - 3  may, in certain examples, include cepstral coefficients associated with specific voices of specific speakers. For instance, system  100  may detect and analyze a mel-frequency cepstral coefficient (“MFCC”), a gammatone frequency cepstral coefficient (“GFCC”), and/or other cepstral coefficients as may serve within a particular implementation to facilitate the identification of a particular voice. Additionally, in certain examples, machine learning techniques may be employed in association with feature identification operation  602 - 3  to facilitate system  100  in associating particular voices with particular speakers. For instance, by analyzing different manners in which different speakers annunciate particular vowel sounds, a machine learning technique may improve its ability to match speech instances to particular speakers. Specific voices may also be identified and matched to certain speakers in some implementations using comparison data stored in a biometric database. For example, the biometric database may include various data for various specific speakers (e.g., well-known people who may speak on media content presentations, users who have experienced artificial reality world  300  previously, etc.). 
     Another feature that may be identified for each speech instance included within simulated binaural audio signal  604  may be a root-mean-square (“RMS”) magnitude of the speech instance. The RMS magnitude may indicate how near or far the avatar is from each speaker. For example, if the avatar with which simulated binaural audio signal  604  is associated is avatar  302  and simulated binaural audio signal  604  is a signal that includes speech from each of speakers  502  shown in  FIG. 5 , speech originating from speaker  502 - 2  may be identified to have a larger RMS magnitude than speaker  502 - 3  due to the relatively close proximity of speaker  502 - 2  and the relative distance to speaker  502 - 3 . Accordingly, as part of feature identification operation  602 - 3 , system  100  may identify that one speech instance included in simulated binaural audio signal  604  has a relatively low RMS magnitude while another has a relatively high RMS magnitude, indicating that two different speakers are likely present at different distances from avatar  302 . 
     Other features similar to RMS magnitude may likewise be identified in like manner. For instance, system  100  may identify one speech instance as originating from the right-hand side of avatar  302  (e.g., due to ILD and ITD cues applies to simulated binaural audio signal  604 ), while another speech instance originates from the left-hand side of avatar  302 . These identified features may similarly indicate that distinct speakers are present. 
     Based on the features identified as part of feature identification operation  602 - 3 , speech separation operation  602 - 4  may break out simulated binaural audio signal  604  into a plurality of auto-transcribable speech signals  608 . Specifically, system  100  may perform speech separation operation  602 - 4  by separating, based on a signal  610  representative of the plurality of features identified as part of feature identification operation  602 - 3 , one speech signal representative of speech originating from one speaker (e.g., speaker  502 - 2 ) from an additional speech signal representative of speech originating from an additional speaker (e.g., speaker  502 - 3 ) that is separate from the one speaker. In this way, any suitable number (i.e., N) of auto-transcribable speech signals  608  may be generated. 
     System  100  may perform speech separation operation  602 - 4  in any suitable manner. For example, system  100  may determine, based on features such as RMS magnitude, that different speech instances are included within simulated binaural audio signal  604  originating at different distances from the avatar, and may separate out the speech instances into unique auto-transcribable speech signals based on the RMS magnitude. Similarly, system  100  may determine, based on features associated with ILD and/or ITD, that different speech instances are included within simulated binaural audio signal  604  originating from different angles with respect to the avatar, and may thus separate out the speech instances based on the ILD and ITD features. Additionally or alternatively, system  100  may determine based on voice-specific features (e.g., cepstral coefficients, etc.) that different voices are originating from the same distance and the same angle with respect to the avatar. In these examples, system  100  may determine that there are multiple speakers on a particular media content presentation being presented at a particular location within artificial reality world  300 , and may separate out the speech instances of these speakers based on the voice-specific features. In other examples, combinations of these features and/or other features may be similarly used to separate speech instances into auto-transcribable speech signals  608  in any manner as may serve a particular implementation. 
     Additionally, in certain implementations, machine learning, artificial intelligence, multivariate statistics, digital signal processing, and other such techniques may be employed to facilitate speech separation operation  602 - 4 . For instance, system  100  may perform speech separation operation  602 - 4  using time-frequency representations of audio signals such as simulated binaural audio signal  604  or other suitable audio signals. Such time-frequency representations may be used to extract features and/or mathematical models from the audio signals. For example, the time-frequency representations may be used in combination with machine learning, statistical algorithms, and/or other techniques mentioned above, or may be used in isolation. 
     System  100  may perform speaker recognition operation  602 - 5  to generate a metadata signal  612  indicative of which auto-transcribable speech signal  608  goes with which speaker within artificial reality world  300 . Specifically, system  100  may perform speaker recognition operation  602 - 5  by determining that a speech signal representative of speech originating from a first speaker (e.g., speaker  502 - 2 ) corresponds to the first speaker and not to a second speaker (e.g., such as speaker  502 - 3 ). Additionally, system  100  may likewise determine that an additional speech signal representative of the speech originating from the second speaker corresponds to the second speaker and not to the first speaker. In some examples, metadata signal  612  may indicate how many speech instances are currently detected (i.e., how many auto-transcribable speech signals  608  are currently available) and which speaker each auto-transcribable speech signal  608  is associated with. In this way, as will be described in more detail below, each closed captioning dataset generated from each of auto-transcribable speech signals  608  may be associated with a particular speaker as the closed captions are presented to the user by the media player device. 
     As described above, media player devices may be used by users to access and experience artificial reality worlds. For example, media player device  210  may be configured to generate (e.g., based on data received from artificial reality provider system  202 ) a 3D representation of artificial reality world  300  to be experienced by user  212  from an arbitrary experience location (e.g., a dynamically selectable location selected by user  212  and corresponding to an arbitrary virtual location within artificial reality world  300 ). To this end, media player device  210  may include or be implemented by any device capable of presenting a field of view of an artificial reality world and detecting user input from user  212  to dynamically update the content of artificial reality world  300  presented within the field of view as user  212  experiences artificial reality world  300 . 
     To illustrate,  FIG. 7A  shows an exemplary implementation of media player device  210  that may be used by user  212  to experience artificial reality media content. As shown, the implementation of media player device  210  shown in  FIG. 7A  may be implemented as a head-mounted artificial reality device (e.g., a virtual reality gaming device) that includes a head-mounted display screen. In other examples, other form factors such as a personal computer device (e.g., a desktop computer, laptop computer, etc.), a mobile or wireless device (e.g., a smartphone, a tablet device, etc., possibly mounted to the head of user  212  by means of a head mount apparatus), or another suitable device or configuration of devices may be used. 
     In some examples, it may be undesirable for user  212  to be limited to one or more discrete positions within artificial reality world  300 . As such, artificial reality data generated and transmitted to media player device  210  may be configured to provide sufficient data to allow artificial reality world  300  to be rendered from any dynamically selectable experience location within the world. For example, the dynamically selectable experience location may be selected by user  212  while user  212  is experiencing artificial reality world  300  using media player device  210 . 
     As used herein, an “arbitrary experience location” may refer to any virtual point in space associated with an artificial reality world (e.g., particularly a virtual reality-type world). For example, arbitrary experience locations are not limited to fixed positions associated with capture devices (e.g., video cameras) that may capture a real-world scene upon which artificial reality world  300  is based, but also include positions between the capture devices. 
       FIG. 7B  illustrates an exemplary artificial reality experience  700  in which user  212  is presented with exemplary artificial reality media content representative of artificial reality world  300  as experienced from a dynamically selectable arbitrary experience location within artificial reality world  300 . Specifically, artificial reality media content  702  is presented within a field of view  704  that shows artificial reality world  300  from an arbitrary experience location in front of the sofa in artificial reality world  300 . As shown, artificial reality world  300  may be available for user  212  to experience by providing user input (e.g., head movements, keyboard input, etc.) to look around and/or to move around (i.e., dynamically select different experience locations within) artificial reality world  300 . 
     For example, field of view  704  may provide a window through which user  212  may easily and naturally look around artificial reality world  300 . Field of view  704  may be presented by media player device  210  (e.g., on a display screen of media player device  210 ) and may include video depicting objects surrounding user  212  within artificial reality world  300 . Additionally, field of view  704  may dynamically change in response to user input provided by user  212  as user  212  experiences artificial reality world  300 . For example, media player device  210  may detect user input (e.g., moving or turning the display screen upon which field of view  704  is presented, changing to a new experience location, etc.). In response, field of view  704  may display different objects and/or objects seen from a different vantage point or experience location in place of the objects seen from the previous vantage point or experience location. 
     In  FIG. 7B , artificial reality world  300  is illustrated as a semi-sphere, indicating that user  212  may look in any direction within artificial reality world  300  that is substantially forward, backward, left, right, and/or up from the experience location currently selected. In other examples, artificial reality world  300  may include an entire 360° by 180° sphere such that user  212  may also look down. Additionally, user  212  may move around to other experience locations within artificial reality world  300  (e.g., sitting on the sofa, etc.). 
     Once a closed captioning dataset has been generated based on one of auto-transcribable speech signals  608 , the closed captioning dataset may be provided to media player device  210  as user  212  experiences artificial reality world  300  to facilitate the user&#39;s understanding of speech in any suitable way. For instance, in certain examples, the providing of the closed captioning dataset to media player device  210  may include presenting (e.g., on a display screen associated with media player device  210  and upon which artificial reality world  300  is presented) the closed captioning dataset in real time as speech originates from the speaker within artificial reality world  300 . Additionally, in examples where multiple speakers are speaking concurrently within artificial reality world  300 , media player device may present closed captioning datasets in ways that clearly indicate which closed captions are associated with which speaker, while providing minimal distraction to user  212  during the artificial reality experience. 
     For example, if media player device  210  is able to determine that user  212  is engaged in a face-to-face conversation with a particular other avatar within artificial reality world  300 , or is specifically watching a particular media content presentation being presented on a screen within artificial reality world  300 , media player device  210  may determine that any closed captioning data other than the data associated with the other avatar or the particular media content presentation would be distracting and unhelpful to user  212 . As such, media player device  210  may automatically and prominently display closed captions associated with the relevant speaker (i.e., the other avatar or the particular media content presentation being watched) while minimizing or abstaining from displaying closed captions associated with other speakers in artificial reality world  300 . 
     In other examples, however, it may not be possible for media player device  210  to automatically and accurately determine which speaker user  212  may wish to focus in on. Accordingly, in these examples, media player device  210  may provide customizable options to the user for displaying closed captioning data in whatever way the user prefers. 
     To illustrate,  FIGS. 8A and 8B  show exemplary screenshots  800  (i.e., screenshot  800 - 1  in  FIG. 8A  and screenshot  800 - 2  in  FIG. 8B ) of a display screen of media player device  210  as the display screen presents a closed captioning dataset within artificial reality world  300 . In  FIGS. 8A and 8B , a different part of artificial reality world  300  (or a different implementation of artificial reality world  300 ) is shown compared to what is illustrated in  FIG. 3 . Specifically, in screenshots  800 , artificial reality world  300  is shown to include an additional avatar  802  standing at the top of a staircase while a media content presentation (i.e., a similar news program as illustrated in  FIG. 3 ) is being presented in an adjoining room to the one in which the avatar of user  212  is located. 
     In the example of  FIGS. 8A and 8B , both avatar  802  and speakers  806 - 1  and/or  806 - 2  on media content presentation  804  may be speaking concurrently, while no other speaker is nearby the avatar of user  212 . Accordingly, it may not be possible for media player device  210  to accurately and reliably determine which of the three speakers (i.e., avatar  802 , speaker  806 - 1 , and speaker  806 - 2 ) user  212  may want to listen to and which ones he or she may want to tune out. Moreover, there may be additional speakers that are within the vicinity of the avatar of user  212  (e.g., such that the additional speakers can be heard by user  212 ), but that are not shown in screenshots  800  (e.g., because the additional speakers are off-screen, such as behind the avatar of user  212 ). Just as media player device  210  may not presume to know which of the three speakers explicitly shown in screenshots  800  user  212  wishes to listen to, media player device  210  may likewise not know whether or not user  212  wishes to listen to one or more of these off-screen speakers that are not shown in screenshots  800 . 
     Thus, screenshot  800 - 1  illustrates a first optional mode of operation that media player device  210  may provide to user  212 . In screenshot  800 - 1 , closed captions  808  are overlaid next to media content presentation  804  and are formatted so as to clearly indicate which speaker is saying what (i.e., captions for speaker  806 - 1  are left justified since speaker  806 - 1  is on the left, while captions for speaker  806 - 2  are right justified). Closed captions  810  are also overlaid next to avatar  802  to indicate what the other user associated with avatar  802  is saying. Additionally, closed captions  812  are overlaid toward the bottom of the screen and pointing in a general direction of an off-screen speaker that user  212  may see if he or she turns to look in the direction indicated (e.g., to the right in this example). In this way, user  212  may be able to read and easily understand what all three on-screen speakers, as well as additional off-screen speakers, are saying at once, or may ignore speech that he or she is not interested in and only read closed captions for the speaker he or she wants to listen to. 
     Conversely, user  212  may feel that the screen is too cluttered with all speech overlaid in speech bubbles on the screen (particularly in situations where there are more than two speakers). As such, screenshot  800 - 2  illustrates another optional mode of operation that may be offered by media player device  210 . In this example, media player device  210  may give user  212  customizable control over how he or she wants to listen to things in artificial reality world  300 . Specifically, in screenshot  800 - 2 , a selector mechanism  814  (e.g., a highlighted ring or box or any other such suitable mechanism for selecting one speaker over another) indicates that user  212  has selected to read captions associated with avatar  802 . User  212  may designate selector mechanism  814  to user  802  in any suitable manner. However, as shown, no similar selector mechanism is highlighting media content presentation  804 , indicating that user  212  may not currently be interested in understanding the speech coming from media content presentation  804  (i.e., the speech from speakers  806 - 1  and  806 - 2 ). As such, closed captions  816  are displayed at the bottom of the screen or in another unobtrusive place (i.e., to avoid unwanted clutter) only for speech originating from avatar  802 , because only avatar  802  has been selected by user  212 . In other examples, other modes of operation for displaying closed captioning datasets so as to facilitate understanding of speech presented in an artificial reality world may also be employed as may serve a particular implementation. 
       FIG. 9  illustrates an exemplary speech presentation method  900  for facilitating understanding of speech presented in an artificial reality world. While  FIG. 9  illustrates exemplary operations according to one embodiment, other embodiments may omit, add to, reorder, and/or modify any of the operations shown in  FIG. 9 . One or more of the operations shown in  FIG. 9  may be performed by system  100 , any components included therein, and/or any implementation thereof. 
     In operation  902 , a speech presentation system may receive a simulated binaural audio signal associated with a media player device that is presenting an artificial reality world to a user of the media player device. For example, the simulated binaural audio signal may be representative of a simulation of sound propagating to an avatar representing the user within the artificial reality world. Operation  902  may be performed in any of the ways described herein. 
     In operation  904 , the speech presentation system may further receive acoustic propagation data representative of an aspect affecting propagation of sound to the avatar within the artificial reality world. Operation  904  may be performed in any of the ways described herein. 
     In operation  906 , the speech presentation system may extract an auto-transcribable speech signal from the simulated binaural audio signal received in operation  902 . For example, the auto-transcribable speech signal may be representative of speech originating from a speaker within the artificial reality world, and the extracting may be performed based on the acoustic propagation data received in operation  904 . Operation  906  may be performed in any of the ways described herein. 
     In operation  908 , the speech presentation system may generate a closed captioning dataset representative of the speech originating from the speaker. For example, the speech presentation system may generate the closed captioning dataset based on the auto-transcribable speech signal extracted in operation  906 . Operation  908  may be performed in any of the ways described herein. 
     In operation  910 , the speech presentation system may provide the closed captioning dataset to the media player device associated with the simulated binaural audio signal received in operation  902 . Operation  910  may be performed in any of the ways described herein. 
       FIG. 10  illustrates an exemplary speech presentation method  1000  for facilitating understanding of speech presented in an artificial reality world. While  FIG. 10  illustrates exemplary operations according to one embodiment, other embodiments may omit, add to, reorder, and/or modify any of the operations shown in  FIG. 10 . One or more of the operations shown in  FIG. 10  may be performed by system  100 , any components included therein, and/or any implementation thereof. 
     In operation  1002 , a speech presentation system may receive a simulated binaural audio signal associated with a media player device that is presenting an artificial reality world to a user of the media player device. For example, the simulated binaural audio signal may be representative of a simulation of sound propagating to an avatar of the user within the artificial reality world. Operation  1002  may be performed in any of the ways described herein. 
     In operation  1004 , the speech presentation system may further receive acoustic propagation data representative of an aspect affecting propagation of sound to the avatar within the artificial reality world. Operation  1004  may be performed in any of the ways described herein. 
     In operations  1006 - 1  and  1006 - 2 , the speech presentation system may extract a plurality of auto-transcribable speech signals from the simulated binaural audio signal received in operation  1002 . For example, the speech presentation system may extract the auto-transcribable speech signals based on the acoustic propagation data received in  1004 . 
     More particularly, in operation  1006 - 1 , the speech presentation system may extract a first auto-transcribable speech signal representative of speech originating from a media content presentation. For example, the media content presentation may be received from a media provider distinct from the media player device and may be presented within the artificial reality world. In operation  1006 - 2 , the speech presentation system may extract a second auto-transcribable speech signal representative of speech originating from an additional avatar. For example, the additional avatar may represent, within the artificial reality world, an additional user of an additional media player device that is presenting the artificial reality world to the additional user concurrently with the presenting of the artificial reality world to the user. Operations  1006 - 1  and  1006 - 2  may be performed in any of the ways described herein. Additionally, in some examples, operations  1006 - 1  and  1006 - 2  may be performed concurrently (i.e., in parallel, at the same time). 
     In operation  1008 - 1 , the speech presentation system may generate a first closed captioning dataset representative of the speech originating from the media content presentation, while, in operation  1008 - 2 , the speech presentation system may generate a second closed captioning dataset representative of the speech originating from the additional avatar. For example, the first closed captioning dataset may be generated based on the first auto-transcribable speech signal extracted in operation  1006 - 1 , while the second closed captioning dataset may be generated based on the second auto-transcribable speech signal extracted in operation  1006 - 2 . Operations  1008 - 1  and  1008 - 2  may be performed in any of the ways described herein. Additionally, in some examples, operations  1008 - 1  and  1008 - 2  may be performed concurrently. 
     In operation  1010 , the speech presentation system may provide the first and second closed captioning datasets generated in operations  1008 - 1  and  1008 - 2 , respectively, to the media player device associated with the simulated binaural audio signal received in operation  1002 . For example, the speech presentation system may provide the first closed captioning dataset so as to correspond to the media content presentation, and may provide the second closed captioning dataset so as to correspond to the additional avatar. Operation  1010  may be performed in any of the ways described herein. 
     In certain embodiments, one or more of the systems, components, and/or processes described herein may be implemented and/or performed by one or more appropriately configured computing devices. To this end, one or more of the systems and/or components described above may include or be implemented by any computer hardware and/or computer-implemented instructions (e.g., software) embodied on at least one non-transitory computer-readable medium configured to perform one or more of the processes described herein. In particular, system components may be implemented on one physical computing device or may be implemented on more than one physical computing device. Accordingly, system components may include any number of computing devices, and may employ any of a number of computer operating systems. 
     In certain embodiments, one or more of the processes described herein may be implemented at least in part as instructions embodied in a non-transitory computer-readable medium and executable by one or more computing devices. In general, a processor (e.g., a microprocessor) receives instructions, from a non-transitory computer-readable medium, (e.g., a memory, etc.), and executes those instructions, thereby performing one or more processes, including one or more of the processes described herein. Such instructions may be stored and/or transmitted using any of a variety of known computer-readable media. 
     A computer-readable medium (also referred to as a processor-readable medium) includes any non-transitory medium that participates in providing data (e.g., instructions) that may be read by a computer (e.g., by a processor of a computer). Such a medium may take many forms, including, but not limited to, non-volatile media, and/or volatile media. Non-volatile media may include, for example, optical or magnetic disks and other persistent memory. Volatile media may include, for example, dynamic random access memory (“DRAM”), which typically constitutes a main memory. Common forms of computer-readable media include, for example, a disk, hard disk, magnetic tape, any other magnetic medium, a compact disc read-only memory (“CD-ROM”), a digital video disc (“DVD”), any other optical medium, random access memory (“RAM”), programmable read-only memory (“PROM”), electrically erasable programmable read-only memory (“EPROM”), FLASH-EEPROM, any other memory chip or cartridge, or any other tangible medium from which a computer can read. 
       FIG. 11  illustrates an exemplary computing device  1100  that may be specifically configured to perform one or more of the processes described herein. As shown in  FIG. 11 , computing device  1100  may include a communication interface  1102 , a processor  1104 , a storage device  1106 , and an input/output (“I/O”) module  1108  communicatively connected via a communication infrastructure  1110 . While an exemplary computing device  1100  is shown in  FIG. 11 , the components illustrated in  FIG. 11  are not intended to be limiting. Additional or alternative components may be used in other embodiments. Components of computing device  1100  shown in  FIG. 11  will now be described in additional detail. 
     Communication interface  1102  may be configured to communicate with one or more computing devices. Examples of communication interface  1102  include, without limitation, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, an audio/video connection, and any other suitable interface. 
     Processor  1104  generally represents any type or form of processing unit capable of processing data or interpreting, executing, and/or directing execution of one or more of the instructions, processes, and/or operations described herein. Processor  1104  may direct execution of operations in accordance with one or more applications  1112  or other computer-executable instructions such as may be stored in storage device  1106  or another computer-readable medium. 
     Storage device  1106  may include one or more data storage media, devices, or configurations and may employ any type, form, and combination of data storage media and/or device. For example, storage device  1106  may include, but is not limited to, a hard drive, network drive, flash drive, magnetic disc, optical disc, RAM, dynamic RAM, other non-volatile and/or volatile data storage units, or a combination or sub-combination thereof. Electronic data, including data described herein, may be temporarily and/or permanently stored in storage device  1106 . For example, data representative of one or more executable applications  1112  configured to direct processor  1104  to perform any of the operations described herein may be stored within storage device  1106 . In some examples, data may be arranged in one or more databases residing within storage device  1106 . 
     I/O module  1108  may include one or more I/O modules configured to receive user input and provide user output. One or more I/O modules may be used to receive input for a single virtual experience. I/O module  1108  may include any hardware, firmware, software, or combination thereof supportive of input and output capabilities. For example, I/O module  1108  may include hardware and/or software for capturing user input, including, but not limited to, a keyboard or keypad, a touchscreen component (e.g., touchscreen display), a receiver (e.g., an RF or infrared receiver), motion sensors, and/or one or more input buttons. 
     I/O module  1108  may include one or more devices for presenting output to a user, including, but not limited to, a graphics engine, a display (e.g., a display screen), one or more output drivers (e.g., display drivers), one or more audio speakers, and one or more audio drivers. In certain embodiments, I/O module  1108  is configured to provide graphical data to a display for presentation to a user. The graphical data may be representative of one or more graphical user interfaces and/or any other graphical content as may serve a particular implementation. 
     In some examples, any of the facilities described herein may be implemented by or within one or more components of computing device  1100 . For example, one or more applications  1112  residing within storage device  1106  may be configured to direct processor  1104  to perform one or more processes or functions associated with facilities  102  through  106  of system  100 . Likewise, storage facility  108  of system  100  may be implemented by or within storage device  1106 . 
     To the extent the aforementioned embodiments collect, store, and/or employ personal information provided by individuals, it should be understood that such information shall be used in accordance with all applicable laws concerning protection of personal information. Additionally, the collection, storage, and use of such information may be subject to consent of the individual to such activity, for example, through well known “opt-in” or “opt-out” processes as may be appropriate for the situation and type of information. Storage and use of personal information may be in an appropriately secure manner reflective of the type of information, for example, through various encryption and anonymization techniques for particularly sensitive information. 
     In the preceding description, various exemplary embodiments have been described with reference to the accompanying drawings. It will, however, be evident that various modifications and changes may be made thereto, and additional embodiments may be implemented, without departing from the scope of the invention as set forth in the claims that follow. For example, certain features of one embodiment described herein may be combined with or substituted for features of another embodiment described herein. The description and drawings are accordingly to be regarded in an illustrative rather than a restrictive sense.