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 .
Procedural Summary
This is responsive to the claims filed 03/29/2024.
Claims 1-20 are pending.
Applicant’s IDS submission is acknowledged and provided herewith.
The Drawings filed on 03/29/2024 are noted.
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.
Claims 1 to 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The examiner follows the two step-analysis, as described in MPEP 2106 (available at https://www.uspto.gov/web/offices/pac/mpep/s2106.html). The following diagram is an overview of the steps involved.
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Step 1 of the two step-analysis considers whether the claims fall into one of the four statutory categories of invention such as a process, machine, manufacture, or composition of matter. The instant invention claims a method and a system in claims 1-20. As such, the claimed invention falls into the broad statutory categories of invention. However, claims that fall within one of the four statutory categories may nevertheless be ineligible if they encompass laws of nature, physical phenomena, or abstract ideas.
Step 2A has been further divided into two prongs as shown in the following diagram.
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Under prong 1 of step 2A, the examiner considers whether the claim recites an abstract idea, law of nature or natural phenomenon. The term “abstract idea” is not interpreted as a layperson might. Instead, the term “abstract idea” is interpreted as described in legal opinions by courts.
According to MPEP 2106.04(a):
the Office has set forth an approach to identifying abstract ideas that distills the relevant case law into enumerated groupings of abstract ideas. The enumerated groupings are firmly rooted in Supreme Court precedent as well as Federal Circuit decisions interpreting that precedent, as is explained in MPEP § 2106.04(a)(2). This approach represents a shift from the former case-comparison approach that required examiners to rely on individual judicial cases when determining whether a claim recites an abstract idea. By grouping the abstract ideas, the examiners’ focus has been shifted from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types.
The enumerated groupings of abstract ideas are defined as:
1) Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations (see MPEP § 2106.04(a)(2), subsection I);
2) Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) (see MPEP § 2106.04(a)(2), subsection II); and
3) Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III).
Representative claim 1 recites the following (with emphasis):
“1. A method for generating background audio in a video game, the method implemented by\
one or more processors, and the method comprising:
obtaining, by one or more of the processors, text data comprising text for speech audio that is to be present in the background audio;
obtaining, by one or more of the processors, contextual data comprising data descriptive of an environment in the video game; and
generating, by one or more of the processors, the background audio based upon processing the text data and the contextual data using one or more machine learning models.”
The underlined portions of representative claim 1 generally encompass the abstract idea, with substantially similar features in claims 19 and 20. The dependent claims further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed. The abstract idea may be viewed, for example, as:
steps or instructions involving observations, judgements or evaluations, which are mental processes under the 2019 PEG;
use of machine learning in a given environment as discussed in Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025); and/or
Real-time monitoring of an electric power grid, as in Electric Power Group, LLC v. Alstom (Fed. Cir. 2016).
In Electric Power Group, the Federal Circuit found that merely selecting information, by content or source, for collection, analysis, and display does nothing significant to differentiate a process from ordinary mental processes, whose implicit exclusion from § 101 undergirds the information-based category of abstract ideas. The claims at issue were directed to gathering information to identify problems in an electric grid and to output that information to a user. The court found that such steps constitute an abstract idea based upon several previous court decisions, including Microsoft Corp. v. AT&T Corp., OIP Techs., Inc. v. Amazon.com, Inc., Content Extraction &Transmission LLC v. Wells Fargo Bank, Digitech Image Techs. LLC v. Elecs. For Imaging, Inc., CyberSource Corp. v. Retail Decisions, Inc. The Court also relied upon TLI Communications, Digitech, Bancorp Servs. LLC v. Sun Life, among others, to state that analyzing information by steps people go through in their minds are essentially mental processes within the abstract-idea category. Like the claims in Recentive, the instant claims merely recite the use of generic machine learning applied to a given data environment. The Recentive court determined that claimed methods are not rendered patent eligible by the fact that using existing machine learning technology they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. The courts have consistently held, in the context of computer-assisted methods, that such claims are not made patent eligible under § 101 simply because they speed up human activity. Therefore, under prong 1, the above analysis demonstrates that the claimed invention encompasses an abstract idea in the form of mental processes and/or certain methods of organizing human activity.
Step 2A, Prong 2
Under prong 2 of step 2A, the examiner considers whether the additional elements in the claims integrate the abstract idea into a practical application. To do so, the examiner looks to the following exemplary considerations, looking at the elements individually and in combination (as set forth by MPEP §2106.05). The judicial exception is not integrated into a practical application because:
(a) It does not improve the functioning of a computer or to any other technology or technical field;
(b) Applying the judicial exception does not effect a particular treatment or prophylaxis for a disease or medical condition;
(c) Do not apply the judicial exception with, or by use of a particular machine;
(d) It does not effect a transformation or reduction of a particular article to a different state or thing;
(e) It does not apply or use the judicial exception in some other meaningful way beyond generally linking the use of the exception to a particular technological environment such that the claims as a whole are more than a drafting effort designed to monopolize the exception.
Here, the abstract idea is not integrated into a practical application. According to 2019 PEG, a consideration indicative of integration into a practical application includes improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)) or adding a specific limitation other than what is well-understood, routine, conventional activity, or adding unconventional steps that confine the claim to a particular application (a non-conventional and non-generic arrangement of various computer components for filtering Internet content, as discussed in BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350-51, 119 USPQ2d 1236, 1243 (Fed. Cir. 2016) (MPEP § 2106.05(d)). Conversely, considerations not indicative of integration include adding words “apply it” (or equivalent) with the judicial exception or mere instructions to implement the abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. (MPEP 2106.05(f)); adding insignificant extra-solution activity (MPEP 2106.05(g)), or generally linking the use of the abstract idea to a particular technological environment or field of use (MPEP 2106.05(h)).
Claims 1, 19, and 20 further recite one or more processors, yet these are recited so generically (no details whatsoever are provided other than in name only) that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014).
The obtaining and generating steps are deemed to be data gathering and data presentation for the use of the judicial exception and similarly are recited at a high level of generality. Thus, these limitations are a form of insignificant extra-solution activity (See MPEP 2106.05(g), See also selecting a particular source and type of data to be manipulated where “Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)).
Even when the limitations are viewed in combination, the additional elements in this claim do no more than automate the organizing activities needed to be performed, using the one of more computer components as tools. While this type of automation is an improvement in a general sense as opposed to performance manually, there is no change to the computers and other technology that are recited in the claim as automating the abstract ideas, and thus this claim cannot improve computer functionality or other technology. See, e.g., Trading Technologies Int’l v. IBG, Inc., 921 F.3d 1084, 1093 (Fed. Cir. 2019) (using a computer to provide a trader with more information to facilitate market trades improved the business process of market trading, but not the computer) and the cases discussed in MPEP 2106.05(a)(I), particularly FairWarning IP, LLC v. Latric Sys., 839 F.3d 1089, 1095 (Fed. Cir. 2016) (accelerating a process of analyzing audit log data is not an improvement when the increased speed comes solely from the capabilities of a general-purpose computer) and Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055 (Fed. Cir. 2017) (using a generic computer to automate a process of applying to finance a purchase is not an improvement to the computer’s functionality). Furthermore, the additional elements do not serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Accordingly, Claims 1, 19, 20, and their dependent claims as a whole does not integrate the recited judicial exception into a practical application and these claims are directed to the judicial exception. Thus, Claims 1-20 lack the eligibility requirements of Step 2 Prong II.
Step 2B
Finally, under step 2B, the examiner evaluates whether the additional elements:
• add a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
• simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
The present claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements recite a display device, a random number generator, a processor, and a memory. These additional elements are generically claimed computer components which enable a game to be conducted by performing the basic functions of: (i) receiving, processing, and storing data, (ii) automating mental tasks and (iii) receiving or transmitting data over a network, e.g., using the Internet to gather data. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application.
Additionally, while the specification discusses the use of large language models (LLMs), it does not provide any indication that the LLMs themselves are improved in any way. See, e.g., Spec. ¶¶ 29-31 and 35-36. Instead, the LLMs appear to be pre-existing, off-the-shelf computer components arranged in conventional ways. Nothing in the claims provides detail about specific or improved LLMs, but rather they apply particular wager information to existing LLMs to process that wager information. In light of the court decision in Recentive, this is not sufficient to save a claim from abstraction.
Therefore, for at least the above reasons, Claims 1 to 20 are directed to applying an abstract idea (e.g., rules for conducting a game and/or mental process) on a general purpose computer without (i) improving the performance of the computer itself (as in McRO, Bascom and Enfish), or (ii) providing a technical solution to a problem in a technical field (as in DDR). In other words, none of Claims 1 to 20 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
AIA Notice
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S. Patent Application Publication 2025/0177863 A1 to Yip et al. (hereinafter Yip).
Regarding Claim 1, and similarly recited Claims 19 and 20, Yip discloses a method for generating background audio in a video game, the method implemented by one or more processors, and the method comprising:
obtaining, by one or more of the processors (figs. 1-3, game processor 200), text data comprising text for speech audio that is to be present in the background audio (¶¶ 5, 15-16, 30 discloses the audio data can be generated or shared by the user playing the game or by other users playing the game with the user or spectating the game of the user, or can be music or audio rendering in the background while the user is playing the game…);
obtaining, by one or more of the processors, contextual data comprising data descriptive of an environment in the video game (¶¶ 5, 15-16, 26 discloses The audio processor processes the audio data inputs to identify characteristics of the audio signal included in the audio data and use select ones of the characteristics of the audio data to influence interactions between at least two assets identified in the game scenes currently rendering at the user interface 115a rendered on the display 115 of the client device 110. The select ones of the characteristics of the audio data include descriptive data that provides details of the audio data and at least one temporal data that can be used to match the audio data to corresponding game scene. The game scene is useful in obtaining current game state and the game context of the game); and
generating, by one or more of the processors, the background audio based upon processing the text data and the contextual data using one or more machine learning models (¶¶ 5, 15-16, 32-34 discloses the audio signal can be processed using a machine learning (ML) algorithm, which builds an artificial intelligence (AI) model using the details from the audio data and the game context of the game to identify the characteristics associated with the audio data that can be used to influence interactions between the at least two assets, identify the type of interactions to impart to the at least two assets, and to identify audio synchronization control(s) to control the interactions of the identified type….).
Regarding Claim 2, Yip discloses the method of claim 1, wherein generating, by one or more of the processors, the background audio based upon processing the text data and the contextual data using one or more machine learning models comprises:
modifying the text data, by a first large language model-based machine learning model, based upon the contextual data (¶¶ 5, 15-16, 32-34).
Regarding Claim 3, Yip discloses the method of claim 2, wherein the modified text data comprises one or more additional paralinguistic tokens (¶¶ 29, 32).
Regarding Claim 4, Yip discloses the method of claim 2, wherein the text data is modified based upon a speaking style indicated in the contextual data (¶¶ 15-16, 21, 23-24, 20, 32-33).
Regarding Claim 5, Yip discloses the method of claim 1, wherein generating, by one or more of the processors, the background audio based upon processing the text data and the contextual data using one or more machine learning models comprises:
including one or more sound effects in the background audio based upon the contextual data (¶¶ 15-16, 21, 23-24, 20, 32-33).
Regarding Claim 6, Yip discloses the method of claim 5, wherein including one or more sound effects in the background audio based upon the contextual data comprises:
extracting, by a second large language model-based machine learning model, ambient feature data from the contextual data (¶¶ 15-16, 21, 23-25, 30, 34).
Regarding Claim 7, Yip discloses the method of claim 6, wherein including one or more sound effects in the background audio based upon the contextual data comprises:
selecting the one or more sound effects from an audio data store based upon the ambient feature data (¶¶ 15-16, 21, 23-25, 30, 34).
Regarding Claim 8, Yip discloses the method of claim 6, wherein including one or more sound effects in the background audio based upon the contextual data comprises:
generating, by one or more of the machine learning models, the one or more sound effects based upon the ambient feature data (¶¶ 15-16, 21, 23-25, 30, 34).
Regarding Claim 9, Yip discloses the method of claim 1, wherein generating, by one or more of the processors, the background audio based upon processing the text data and the contextual data using one or more machine learning models comprises:
generating, by a text-to-speech machine learning model, speech audio based upon the text data; and wherein the background audio comprises the speech audio (¶¶ 15-16, 21, 23-24, 30, 34).
Regarding Claim 10, Yip discloses the method of claim 9, wherein generating, by one or more of the processors, the background audio based upon processing the text data and the contextual data using one or more machine learning models comprises:
mixing the speech audio and the one or more sound effects to generate the background audio (¶¶ 15-16, 21).
Regarding Claim 11, Yip discloses the method of claim 9, wherein generating the speech audio is further based upon the contextual data (¶¶ 15-16, 21, 23-24, 20, 32-33).
Regarding Claim 12, Yip discloses the method of claim 11, wherein generating, by one or more of the processors, the background audio based upon processing the text data and the contextual data using one or more machine learning models comprises:
extracting, by a third large language model-based machine learning model, voice conditioning feature data from the contextual data (¶¶ 15-16, 21, 23-24, 20, 32-33); and
wherein, the speech audio is generated based upon the voice conditioning feature data (¶¶ 15-16, 21, 23-24, 20, 32-33).
Regarding Claim 13, Yip discloses the method of claim 12, wherein the voice conditioning feature data comprises prosody data and/or wherein the voice conditioning feature data comprises speaker characteristic data (¶¶ 15-16, 21, 23-24, 20, 32 discloses audio processor 220 can engage a voice recognition module 224 to identify a speaker providing content included in the audio signal. For example, the voice recognition module can identify the spoken content (e.g., text or speech or lyrics of a song included in the content) and analyze the audio to identify if a human or a robot (or “bot”) is providing the content. When the content is from a human, the spoken content can be further analyzed to identify a singer or a speaker providing the content, the event or location or context when the content was generated and/or presented, etc).
Regarding Claim 14, Yip discloses the method of claim 12, wherein the second large language model-based machine learning model used to extract the ambient feature data and the third large language model-based machine learning model used to extract the voice conditioning feature data are the same machine learning model (¶¶ 15-16, 21, 23-24, 32-33).
Regarding Claim 15, Yip discloses the method of claim 1, wherein the contextual data further comprises game state data (¶¶ 15-16, 21, 26, 32).
Regarding Claim 16, Yip discloses the method of claim 1, wherein the contextual data further comprises data descriptive of real-world events (¶¶ 15-16, 21, 23-24 discloses FIG. 2 shows examples of audio data that can be used to provide audio synchronization control to synchronize movement of assets within game scenes of a game, …. The audio related to audio content 104b can be generated by the user/other users by performing some actions, such as clapping, whistling, humming, singing, beat-boxing, playing on a musical instrument, etc., and such audio is distinguishably audible to enable the one or more microphones disposed in the real-world environment of the user to detect and capture. The audio generated through actions of the user can be picked up and replicated by other users.).
Regarding Claim 17, Yip discloses the method of claim 1, further comprising: causing the generated background audio to be played in a running instance of the video game (¶¶ 15-16, 21, 23-24 discloses FIG. 2 shows examples of audio data that can be used to provide audio synchronization control to synchronize movement of assets within game scenes of a game).
Regarding Claim 18, Yip discloses the method of claim 1, further comprising:
generating a plurality of background audio samples, wherein the plurality of background audio samples each comprise different spoken dialogue (¶¶ 15-16, 21, 23-24); and
selecting, by a fourth large language model-based machine learning model, a subset of the plurality of background audio samples to generate background audio with extended dialogue (¶¶ 15-16, 21, 23-24).
Conclusion
Claims 1-20 are examined above.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAUNA-KAY HALL whose telephone number is (571)270-1419. The examiner can normally be reached M-F 9:00AM-5:00PM.
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/S.N.H/Examiner, Art Unit 3715 /DAVID L LEWIS/Supervisory Patent Examiner, Art Unit 3715