DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1-15 rejected under 35 U.S.C. 101 because the claimed invention is directed to a
judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 1 is directed to a method (i.e., a process), claim 13 is directed to a computing device (i.e., a machine), claim 14 is directed to a non-transitory computer readable medium (i.e., a manufacture), and claim 15 is directed to a use of the computer-implemented method (i.e., a process). In other words, Step 1 of the subject-matter eligibility analysis is “Yes.”
However, the claims are drawn to an abstract idea of monitoring a position of the avatar, determining whether the avatar is within the audible range, and outputting information on the audio consumption, either in the form of “mental process,” in terms of processes that can be performed in the human mind (including an observation, evaluation, judgement or opinion). Claims that require a computer may also recite a mental process, as described in MPEP 2106.04(a)(2)(III)(C). The claims are reasonably understood as reciting the following limitations: monitoring a position of the avatar within the virtual environment, wherein the position of the avatar within the virtual environment is controllable by the user using at least one user input device comprised in or connected to the computing device and the audio emitter has an audible range defining an area or a volume of the virtual environment, the one or more audio tracks being output table via at least one audio output device comprised in or connected to the computing device when the avatar is within the audible range; in response to the avatar entering the audible range of the audio emitter, starting an audio consumption timer; in response to the avatar leaving the audible range of the audio emitter, stopping the audio consumption timer; evaluating audio consumption of the user based at least on the audio consumption timer and at least one duration of at least one audio track of the one or more audio tracks emitted, at least in part, during running of the audio consumption timer; and outputting information on the audio consumption of the user. These limitations simply describe a process of observing and evaluating observed information. These activities are mental processes involving observation, evaluation, and judgement that can be performed in the human mind. These limitations are analogous to collecting and analyzing information as well as displaying results.
Furthermore, the claims do not include additional elements that either alone or in combination are sufficient to claim a practical application because to the extent that a “computing device.” “audio output,” “avatar,” “game engine”, and “virtual environment” are claimed, as these are recited at a high level of generality and are generic and are conventional computer components. These additional elements are tools for implementing the abstract idea and do not improve the computer system. They explain the judicial exception using generic computer or technological components and link the use of the judicial exception to a specific technological environment. The claims do not integrate the judicial exception into a practical application. Therefore, Step 2A, Prong Two of the subject matter eligibility analysis is “No.”
Likewise, the claims do not include additional elements that either alone or in combination are sufficient to amount to significantly more than the judicial exception because to the extent that a “computing device.” “audio output,” “avatar,” “game engine”, and “virtual environment” are claimed these are all generic, well-known, and conventional computing elements. As evidence that these are generic, well-known, and conventional computing elements. US 2023/0017111 A1 to Chhabra et al. discloses computing device [0051], an audio output [0070], an avatar [0003], a game engine [0048], and a virtual environment [0059]. Furthermore, Applicant’s specification discloses these elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a), per MPEP §2106.07(a) III (a), which satisfies the Examiner’s evidentiary burden requirement per the Berkheimer memo.
Specifically, the Applicant’s claimed a “computing device” is described in para. [0017], as follows: “[0017] FIG. 1 illustrates a system 100 comprising at least a computing device 101, a (remote) database server 141, a remote server 121 and one or more further computing devices 132.” An “audio output” in para. [0019], as follows: “[0019] For example, the computing device 101 may comprise one or more user input devices, a display, a touch screen which may act as both a user input device and a display, and/or one or more audio output devices.” An “avatar” is described in para. [0013], as follows: “[0013] An audio emitted may be activated, for example, when an avatar of the user enters a pre-defined area or volume around the audio emitter—defined, e.g., as sphere surrounding the audio emitter—and/or when a specifically programmed interaction occurs within the virtual environment, for example when an avatar of the user switches on a jukebox in the virtual environment.” An “game engine” is described in para. [0021], as follows: “[0021] the virtual environment may be implemented, for example, using a game engine such as Unreal Engine or Unity.” A “virtual environment” is described in para. [0013] as follows: “[0013] Audio emitters can be triggered based on certain events occurring within the virtual environment. An audio emitted may be activated, for example, when an avatar of the user enters a pre-defined area or volume around the audio emitter—defined, e.g., as sphere surrounding the audio emitter—and/or when a specifically programmed interaction occurs within the virtual environment.”
These elements are reasonably considered generic and conventional computer
components. As such, the claimed limitations do not provide anything significantly more than
the judicial exception. Therefore, step 2B, of the subject-matter eligibility analysis is “No.”
In addition, dependent claims 2-13 do not provide a practical application
and are insufficient to amount to significantly more than the judicial exception. As such,
dependent claims 2-13 are also rejected under 35 U.S.C § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1, 2, and 11-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20230017111 A1 to Chhabra et al. in view of US 20040249489 A1 to Dick and US 20190236094 A1 to Sharifi.
Regarding claim 1, Chhabra et al. teaches a computer-implemented method of spatialized audio in a virtual metaverse is disclosed, comprising: receiving a request to receive audio associated with a metaverse place of the virtual metaverse from a first user of a plurality of users, wherein the first user is associated with a user device, and wherein the plurality of users are associated with a respective avatars of a plurality of avatars in the metaverse place and additionally one or more audio characteristics of at least one of the respective audio streams based on the one or more spatial parameters to create spatialized audio streams [0006]. It further discusses In this manner, the properties can include properties such as: propagation medium (e.g., water, air, other, etc.), audio source (e.g., a player or non-player audio source), audio volume (e.g., representative of volume of an audio source) [0087]. However, Chhabra et al. does not teach starting an audio consumption timer in response to an avatar entering the audible range of the audio emitter as well as stopping it, evaluating audio consumption of the user based at least on the audio consumption timer as well as outputting information on the audio consumption of the user. Dick teaches monitoring in an audio data player the elapsed playback time for an audio data file and determining the compression ratio for each data portion traversed, and calculating a playback time for each data portion traversed [0012]. It further teaches a linear buffer receiving data from the circular buffer, the linear buffer containing a time-length of audio data (.DELTA.T), the audio decoder receiving data from the linear buffer, and the timekeeper calculating an elapsed playback time (T2) comprising the elapsed playback time for audio data exiting the circular buffer (T1) minus the time-length of audio data contained in the linear buffer (.DELTA.T). [0014]. Sharifi further teaches as used in this specification, content can be identified as consumed by the user based on the user likely having viewed the content, listened to the content, read the content, or otherwise been exposed to the content or a portion of the content. [0018]. It further teaches data can be stored at a media consumption history database associated with the content consumption engine 130, where the data identifies the content consumed by the user and information associated with both the user's consumption of the content, e.g., when and where the user consumed the content, and the content itself, e.g., one or more entities associated with the content [0020]. It would have been obvious to modify the virtual audio system with the elapsed playback time monitoring of Dick in order to determine the duration of audio playback and further with the consumption of Sharifi to evaluate whether the audio content has been consumed by the user.
Regarding claim 2, Chhabra et al. teaches the computer-implemented method of claim 1, further comprising: activating the audio emitter in response to the avatar being within a triggering range of the audio emitter or in response to a first pre-defined triggering event occurring in the virtual environment, wherein the triggering range is larger than or equal to the audible range; and/or deactivating the audio emitter in response to the avatar leaving the triggering range of the audio emitter or in response to a second pre-defined triggering event occurring in the virtual environment. (Chhabra et al. teaches a speaker object can be created that emits sounds as though a representing a functioning juke box having a particular position within a metaverse place. Thereafter, avatars in the vicinity of the speaker object may receive spatialized audio streams that include a transformed audio stream that includes sounds from the speaker object [0086]. It further teaches the spatialized audio API 106 can also include properties including parameters or properties associated with sound propagation. In this manner, the properties can include properties such as: propagation medium (e.g., water, air, other, etc.), audio source (e.g., a player or non-player audio source), audio volume (e.g., representative of volume of an audio source), attenuation distance [0087]). However, Chhabra et al. does not teach starting an audio consumption timer in response to an avatar entering the audible range of the audio emitter as well as stopping it, evaluating audio consumption of the user based at least on the audio consumption timer as well as outputting information on the audio consumption of the user. Dick teaches monitoring in an audio data player the elapsed playback time for an audio data file and determining the compression ratio for each data portion traversed, and calculating a playback time for each data portion traversed [0012]. It further teaches a linear buffer receiving data from the circular buffer, the linear buffer containing a time-length of audio data (.DELTA.T), the audio decoder receiving data from the linear buffer, and the timekeeper calculating an elapsed playback time (T2) comprising the elapsed playback time for audio data exiting the circular buffer (T1) minus the time-length of audio data contained in the linear buffer (.DELTA.T). [0014]. Sharifi further teaches as used in this specification, content can be identified as consumed by the user based on the user likely having viewed the content, listened to the content, read the content, or otherwise been exposed to the content or a portion of the content. [0018]. It further teaches data can be stored at a media consumption history database associated with the content consumption engine 130, where the data identifies the content consumed by the user and information associated with both the user's consumption of the content, e.g., when and where the user consumed the content, and the content itself, e.g., one or more entities associated with the content [0020]. It would have been obvious to modify the virtual audio system with the elapsed playback time monitoring of Dick in order to determine the duration of audio playback and further with the consumption of Sharifi to evaluate whether the audio content has been consumed by the user.
Regarding claim 11, Chhabra et al. teaches the computer-implemented method according to claim 1 further comprising: providing, by the computing device or by the computing device in communication with at least one remote server, the virtual environment. (Chhabra et al. teaches in one implementation, the game application 112 or 118 may permit users to use and interact with online experience platform 102, such as search for a game, experience, or other content; control a virtual character in a virtual experience hosted by online experience platform 102, or view or upload content, such as games 105, images, video items, web pages, documents, and so forth. In one example, the game application may be a web application (e.g., an application that operates in conjunction with a web browser) that can access, retrieve, present, or navigate content (e.g., virtual character in a virtual environment, etc.) [0079], as well as According to aspects of the disclosure, the game application 112/118 may be an online experience platform application for users to build, create, edit, upload content to the online experience platform 102 as well as interact with online experience platform 102 (e.g., play games 105 hosted by online experience platform 102). [0080]).
Regarding claim 12, Chhabra et al. teaches the computer-implemented method according to any preceding claim 1 wherein the virtual environment is a two-dimensional or three-dimensional virtual environment implemented using a game engine. (Chhabra et al. teaches a game 105 rendered in connection with a game engine 104. In some implementations, a game 105 may have a common set of rules or common goal, and the virtual environments of a game 105 share the common set of rules or common goal [0059]. Chhabra et al. further teaches the one or more environments of a game 105 or virtual experience may be collectively referred to as a “world,” “gaming world,” “virtual world,” “universe,” or “metaverse” herein. An example of a world may be a 3D metaverse place of a game 105)
Regarding claim 13, Chhabra et al. teaches a computing device comprising means for performing the computer-implemented method according to claim 1. (Chhabra et al. teaches in some implementations, one or more client devices 110 or 116 may connect to the online experience platform 102 at any given moment. It may be noted that the number of client devices 110 or 116 is provided as illustration, rather than limitation. In some implementations, any number of client devices 110 or 116 may be used [0078]. It further teaches in another example, the game application may be a native application (e.g., a mobile application, app, or a gaming program) that is installed and executes local to client device 110 or 116 and allows users to interact with online experience platform 102. The game application may render, display, or present the content (e.g., a web page, a user interface, a media viewer, an audio stream) to a user. In an implementation, the game application may also include an embedded media player that is embedded in a web page [0079].
Regarding claim 14, Chhabra et al. teaches a non-transitory computer readable media having stored thereon instructions that, when executed by a computing device, cause the computing device to perform the computer-implemented method according to claim 1. (Chhabra et al. teaches in some implementations, one or more client devices 110 or 116 may connect to the online experience platform 102 at any given moment. It may be noted that the number of client devices 110 or 116 is provided as illustration, rather than limitation. In some implementations, any number of client devices 110 or 116 may be used [0078]. It further teaches in another example, the game application may be a native application (e.g., a mobile application, app, or a gaming program) that is installed and executes local to client device 110 or 116 and allows users to interact with online experience platform 102. The game application may render, display, or present the content (e.g., a web page, a user interface, a media viewer, an audio stream) to a user [0079].
Regarding claim 15, Chhabra et al. teaches the Use of the computer-implemented method according to claim 1 for tracking of audio consumption in an online virtual environment comprising a plurality of avatars representing a plurality of users. (Chhabra et al. teaches One or more games 105 are provided by the online experience platform. In some implementations, a game 105 can include an electronic file that can be executed or loaded using software, firmware or hardware configured to present the game content (e.g., digital media item) to an entity [0059]. It further teaches games and/or virtual experiences may have one or more environments (also referred to as “gaming environments,” “metaverse places,” or “virtual environments” herein) where multiple environments may be linked. An example of an environment may be a three-dimensional (3D) environment [0060].
Claim(s) 3 and 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20230017111 A1 to Chhabra et al. in view of US 20040249489 A1 to Dick and US 20190236094 A1 to Sharifi in further view of US 10223063 B2 to Gibson et al.
Regarding claim 3, Chhabra et al. teaches the computer-implemented method of claim 1 which teaches a computer-implemented method of spatialized audio in a virtual metaverse is disclosed, comprising: receiving a request to receive audio associated with a metaverse place of the virtual metaverse from a first user of a plurality of users, wherein the first user is associated with a user device, and wherein the plurality of users are associated with a respective avatars of a plurality of avatars in the metaverse place and additionally one or more audio characteristics of at least one of the respective audio streams based on the one or more spatial parameters to create spatialized audio streams [0006]. It further discusses in this manner, the properties can include properties such as: propagation medium (e.g., water, air, other, etc.), audio source (e.g., a player or non-player audio source), audio volume (e.g., representative of volume of an audio source) [0087]. However, Chhabra et al. doesn’t teach evaluating of the audio consumption of the user comprises, detecting audio consumption event has occurred and wherein an occurrence of the audio consumption event indicates that the user has consumed an audio track, and incrementing a value of an audio consumption. Gibson et al. teaches Referring now to FIG. 2A, in performing the method 200, for each track of a plurality of tracks (or more generally, media content items) consumed by a user of the media-providing service, the electronic device determines (204) whether the track has previously been consumed by (e.g., requested by, listened by, streamed to, provided to) the user based on the listening history of the user [0019]. It further teaches determining the electronic device determines (208) a discovery score (e.g., metric) based on a number of the plurality of tracks determined to not have been previously consumed by the user (e.g., a number of the plurality of tracks that are not in the listening history of the user) [0020]. Dick further teaches a method is disclosed for monitoring in an audio data player the elapsed playback time for an audio data file having data portions capable of having different compression ratios, characterized by, concurrently with playback, forward scan, and reverse scan of the audio data file, determining the compression ratio for each data portion traversed, and calculating a playback time for each data portion traversed [0012]. It would have been obvious to one of ordinary skill in the art to modify Chhabra et al. in view of Gibson et al. and Dick to evaluate user audio consumption using playback history and elapsed playback time in order to improve tracking of audio consumption and user metrics.
Regarding claim 4, Chhabra et al. teaches a computer-implemented method for audio streams based on the one or more spatial parameters to create spatialized audio streams; combining the spatialized audio streams to create a combined spatialized audio stream; and providing the combined spatialized audio stream to the user device [0006]. It further teaches for example, if the number of users participating in gameplay of a game 105 exceeds a threshold number, the online experience platform 102 may perform one or more game engine functions that were previously performed by the client devices 110 or 116 [0069]. However, Chhabra et al. does not teach calculating a track consumption metric based on elapsed playback time or a percentage or ratio of playback time as well as determining whether the metric fails to exceed the first predefined threshold. Gibson et al. teaches the threshold may be a predefined threshold. For example, satisfying the threshold discovery score may indicate that the number of new (i.e., previously unconsumed) tracks consumed by the user is greater than the number of repeated (i.e., previously consumed) tracks consumed by the user [0024], while Dick teaches monitoring elapsed playback time for an audio data file having data portions capable of having different compression ratios, characterized by, concurrently with playback, forward scan, and reverse scan of the audio data file, determining the compression ratio for each data portion traversed, and calculating a playback time for each data portion traversed. [0012]. It would have been obvious in the ordinary skill in the art to modify Chhabra et al. in view of Gibson et al. and Dick to evaluate user audio consumption using elapsed playback time and threshold-based in order to improve tracking of audio consumption and user metrics.
Claim(s) 5, 6, 7, 8, 9 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20230017111 A1 to Chhabra et al. in view of US 20040249489 A1 to Dick, US 20190236094 A1 to Sharifi, US 10223063 B2 to Gibson et al., in further view of US 20220020348 A1 to Kusakabe et al. and US 20090099474 A1 to Pineda et al.
Regarding claim 5, Chhabra et al. teaches the computer implemented method of claim 4. Chhabra et al. teaches a computer-implemented method for audio streams based on the one or more spatial parameters to create spatialized audio streams; combining the spatialized audio streams to create a combined spatialized audio stream; and providing the combined spatialized audio stream to the user device [0006]. It further teaches for example, if the number of users participating in gameplay of a game 105 exceeds a threshold number, the online experience platform 102 may perform one or more game engine functions that were previously performed by the client devices 110 or 116 [0069]. However, Chhabra et al. does not teach calculating a track consumption metric based on elapsed playback time or a percentage or ratio of playback time as well as determining whether the metric fails to exceed the first predefined threshold. Gibson et al. teaches the threshold may be a predefined threshold, they also don’t teach calculating a background audio level of an audio level as well as calculating a signal-to-noise ratio of the audio track. For example, satisfying the threshold discovery score may indicate that the number of new (i.e., previously unconsumed) tracks consumed by the user is greater than the number of repeated (i.e., previously consumed) tracks consumed by the user [0024], while Dick teaches monitoring elapsed playback time for an audio data file having data portions capable of having different compression ratios, characterized by, concurrently with playback, forward scan, and reverse scan of the audio data file, determining the compression ratio for each data portion traversed, and calculating a playback time for each data portion traversed. [0012]. Kusakabe et al. teaches in a power spectrum obtained by performing FFT, the foregoing difference may be calculated with regard to only a frequency lower than a predetermined frequency [0145]. Pineda et al. further teaches using ICA to "clean" the data in real time increases signal-to-noise ratio, making the relevant signal easier and faster to detect by a pattern recognition system [0049]. It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chhabra et al to include a signal-to-noise ratio as well as calculating a background audio level to track the current position of the avatar.
Regarding claim 6, Chhabra et al. teaches a computer-implemented method of claim 5, Chhabra et al. teaches a computer-implemented method for audio streams based on the one or more spatial parameters to create spatialized audio streams; combining the spatialized audio streams to create a combined spatialized audio stream; and providing the combined spatialized audio stream to the user device [0006]. It further teaches for example, if the number of users participating in gameplay of a game 105 exceeds a threshold number, the online experience platform 102 may perform one or more game engine functions that were previously performed by the client devices 110 or 116 [0069]. However, Chhabra et al. does not teach , the calculating of the background audio level and the calculating of the signal-to-noise ratio periodically or regularly while the audio consumption timer is running; and in response to the signal-to-noise ratio being below the second pre-defined threshold while the audio consumption timer is running, stopping the audio consumption timer. Kusakabe et al. teaches in a power spectrum obtained by performing FFT, the foregoing difference may be calculated with regard to only a frequency lower than a predetermined frequency [0145]. Pineda et al. further teaches using ICA to "clean" the data in real time increases signal-to-noise ratio, making the relevant signal easier and faster to detect by a pattern recognition system [0049]. It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chhabra et al to include a signal-to-noise ratio while the consumption timer is running.
Regarding claim 7, Chhabra et al. teaches the computer implemented method of claim 4. Chhabra et al. teaches a computer-implemented method for audio streams based on the one or more spatial parameters to create spatialized audio streams; combining the spatialized audio streams to create a combined spatialized audio stream; and providing the combined spatialized audio stream to the user device [0006]. It further teaches for example, if the number of users participating in gameplay of a game 105 exceeds a threshold number, the online experience platform 102 may perform one or more game engine functions that were previously performed by the client devices 110 or 116 [0069]. However, Chhabra et al. does not teach the threshold value between 24 dB and 26 dB. Pineda et al. teaches In other applications, ICA decomposes the signal into spatially separable subcomponents in order to maximize the signal-to-noise response and allow for multiple control signals (at 45) [0069]. It would have been obvious in the ordinary skill in the art before the effective filing date to modify Chhabra et al. to include the signal-to-noise ratio between 24 and 26 dB because this is approximately the lowest quality of signal that can be intelligibly understood by a user.
Regarding claim 8, Chhabra et al. teaches a computer-implemented method for audio streams based on the one or more spatial parameters to create spatialized audio streams; combining the spatialized audio streams to create a combined spatialized audio stream; and providing the combined spatialized audio stream to the user device [0006]. However, Chhabra et al. does not teach that the information on the audio consumption of the user comprises one or more audio tracks, such as the number of times an audio track was triggered, the number of audio consumption events, the average percentage of an audio track consumed, or the average length of time the audio track was consumed. Gibson et al. teaches in some embodiments, the listening history contains information regarding how many times a track was consumed by a user (e.g., maintains a count of how often tracks are repeated) [0019]. Gibson et al. further teaches The listening history may contain additional information (e.g., artist, album, genre, etc.) about the tracks consumed by the user and/or about listening contexts in which the tracks were consumed (e.g., time of day, day of a week, location (e.g., in the car, at home), etc.). [0019]. It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chhabra et al. in view of Gibson et al. to maintain audio consumption information that includes listening history in order to improve user tracking and customize media content based on the listening behavior of the user.
Regarding claim 9, Chhabra et al. teaches a the computer-implemented method of claim 1 which teaches a computer-implemented method of spatialized audio in a virtual metaverse is disclosed, comprising: receiving a request to receive audio associated with a metaverse place of the virtual metaverse from a first user of a plurality of users, wherein the first user is associated with a user device, and wherein the plurality of users are associated with a respective avatars of a plurality of avatars in the metaverse place and additionally one or more audio characteristics of at least one of the respective audio streams based on the one or more spatial parameters to create spatialized audio streams [0006]. It further discusses in this manner, the properties can include properties such as: propagation medium (e.g., water, air, other, etc.), audio source (e.g., a player or non-player audio source), audio volume (e.g., representative of volume of an audio source) [0087]. However, Chhabra et al. does not teach detecting audio consumption event has occurred and wherein an occurrence of the audio consumption event indicates that the user has consumed an audio track, and incrementing a value of an audio consumption. Gibson et al. teaches Referring now to FIG. 2A, in performing the method 200, for each track of a plurality of tracks (or more generally, media content items) consumed by a user of the media-providing service, the electronic device determines (204) whether the track has previously been consumed by (e.g., requested by, listened by, streamed to, provided to) the user based on the listening history of the user [0019]. It further teaches determining the electronic device determines (208) a discovery score (e.g., metric) based on a number of the plurality of tracks determined to not have been previously consumed by the user (e.g., a number of the plurality of tracks that are not in the listening history of the user) [0020]. Dick further teaches a method is disclosed for monitoring in an audio data player the elapsed playback time for an audio data file having data portions capable of having different compression ratios, characterized by, concurrently with playback, forward scan, and reverse scan of the audio data file, determining the compression ratio for each data portion traversed, and calculating a playback time for each data portion traversed [0012]. It would have been obvious to one of ordinary skill in the art to modify Chhabra et al. in view of Gibson et al. and Dick to evaluate user audio consumption using playback history and elapsed playback time in order to improve tracking of audio consumption and user metrics.
Regarding claim 10, Chhabra et al. teaches a computer-implemented method for audio streams based on the one or more spatial parameters to create spatialized audio streams; combining the spatialized audio streams to create a combined spatialized audio stream; and providing the combined spatialized audio stream to the user device [0006]. It further teaches for example, if the number of users participating in gameplay of a game 105 exceeds a threshold number, the online experience platform 102 may perform one or more game engine functions that were previously performed by the client devices 110 or 116 [0069]. However, Chhabra et al. does not teach calculating a value of a non-spatialized track consumption metric defined as the length of time that the non-spatialized audio track was playing during the running of the non-spatialized audio consumption timer or as a percentage or a ratio of the length of time that the non-spatialized audio track was playing during the running of the non-spatialized audio consumption timer and in response to the value of the non-spatialized track consumption metric failing to exceed the third pre-defined threshold, detecting that no non-spatialized audio consumption event occurred. Gibson et al. teaches the threshold may be a predefined threshold. For example, satisfying the threshold discovery score may indicate that the number of new (i.e., previously unconsumed) tracks consumed by the user is greater than the number of repeated (i.e., previously consumed) tracks consumed by the user [0024], while Dick teaches monitoring elapsed playback time for an audio data file having data portions capable of having different compression ratios, characterized by, concurrently with playback, forward scan, and reverse scan of the audio data file, determining the compression ratio for each data portion traversed, and calculating a playback time for each data portion traversed. [0012]. It would have been obvious in the ordinary skill in the art to modify Chhabra et al. in view of Gibson et al. and Dick to evaluate user audio consumption using elapsed playback time and threshold-based in order to improve tracking of audio consumption and user metrics.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure US 20090282335 A1 to Alexandersson teaches an electronic device is provided that plays back a collection of media objects. The electronic device includes a controller that assigns a virtual spatial location within a virtual space to a sample of each media object and plays back at least one of the samples to a user through a multichannel audio device. Each played sample is within a virtual audible range of a virtual user position in the virtual space, and each played sample is played using spatial audio so that the user perceives each played sample as emanating from the corresponding virtual spatial location within the virtual space. US 20120088586 A1 to Watkins et al. teaches a method is provided of virtual gameplay with linked characters in a game environment. In an interactive game environment, a request is received to link a first player character with a second character.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SENIYA BAIG whose telephone number is (571)270-0447. The examiner can normally be reached Monday-Thursday 7:30am-5:00pm, Friday 7:30am-4:00pm.
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/SENIYA BAIG/Examiner, Art Unit 3715
/WILLIAM H MCCULLOCH JR/Primary Examiner, Art Unit 3715
