DETAILED ACTION
Applicant's Submission of a Response - RCE
Applicant’s submission of a response on 5/1/2026 has been received and fully considered. In the response, claims 1, 6, 8, 13, 17, and 19 have been amended; claim 2 has been canceled; and new claim 23 has been added. Therefore, claims 1, 3, 5-10 and 13-23 are pending.
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.
Claims 1, 3, 6-9, 16, and 17-23 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2020/0306641 to Kolen in view of U.S. Patent Application Publication No. 2023/0376328 to Nagar.
With regard to claim 1, Kolen discloses a computer-implemented method comprising:
analyzing a stored media file to determine a content characteristic (e.g., see at least paragraph 36, that discusses “the system may optionally access metadata information associated with music being streamed by the user”);
analyzing a virtual environment in a current interactive session to determine a parameter associated with the content characteristic that corresponds to current activity within the virtual environment (e.g., see at least paragraphs 37 and 38 that discuss “style preference may be utilized by the system to generate music, for example based on contextual information occurring in the electronic game” or a “certain musical cue maybe selected based on the user reaching a particular progression point within the electronic game”); and
modifying the parameter of the virtual environment presented during the current interactive session based on at least in part on a waveform (e.g., see at least paragraphs 68 and 69 for discussion of creating audio waveforms; see also paragraph 72 that states “the audio waveform 144B may be utilized as an input to a different artificial neural network 224” and “Subsequent to training, the audio waveform 144B may be analyzed by the network 224 in view of style preference 212. The network 224 may then generate personalized music 102 in accordance with the style preference.”) generated using the content characteristic (e.g., see at least paragraph 47, that states as “the user manipulates the character within the region, the game information 114 may be updated to indicate triggers or contextual information associated with the manipulation. In this way, if the user encounters a particular boss, or enters a particular [room], the game information 114 may be updated reflect these encounters”; see also paragraph 50 for discussion of playing personalized music based on a user’s control of the game);
[claim 6] further comprising analyzing the stored media file to determine the content characteristics associated with the content characteristic (e.g., see at least paragraph 47, that states as “the user manipulates the character within the region, the game information 114 may be updated to indicate triggers or contextual information associated with the manipulation. In this way, if the user encounters a particular boss, or enters a particular [room], the game information 114 may be updated reflect these encounters”; see also paragraph 50 for discussion of playing personalized music based on a user’s control of the game);
[claim 7] further comprising analyzing an in-game scene within the virtual environment to identify a scene characteristic of the in-game scene ((e.g., see at least paragraph 47, that states as “the user manipulates the character within the region, the game information 114 may be updated to indicate triggers or contextual information associated with the manipulation. In this way, if the user encounters a particular boss, or enters a particular [room], the game information 114 may be updated reflect these encounters”; see also paragraph 50 for discussion of playing personalized music based on a user’s control of the game).
[claim 8] further comprising comparing the content characteristic regarding one or more portions of the stored media file to the scene characteristic of the in-game scene (e.g., see at least paragraph 47, that states as “the user manipulates the character within the region, the game information 114 may be updated to indicate triggers or contextual information associated with the manipulation. In this way, if the user encounters a particular boss, or enters a particular [room], the game information 114 may be updated reflect these encounters”; see also paragraph 50 for discussion of playing personalized music based on a user’s control of the game);
[claim 9] wherein modifying the parameters of the virtual environment includes modifying sound or music of the in-game scene based at least in part on the content characteristic of the one of the portions of the stored media file and the scene characteristics of the in-game scene (e.g., see at least paragraph 47, that states as “the user manipulates the character within the region, the game information 114 may be updated to indicate triggers or contextual information associated with the manipulation. In this way, if the user encounters a particular boss, or enters a particular [room], the game information 114 may be updated reflect these encounters”; see also paragraph 50 for discussion of playing personalized music based on a user’s control of the game);
[claim 16] further comprising receiving a user selection of a user profile of a second stored media file, wherein the user profile is associated with a second content characteristic; and modifying the parameter includes modifying the parameter based at least in part on the second content characteristic (e.g., see at least paragraph 52 that discloses creating a user profile associated with music personalization);
[claim 20] further comprising identifying that the content characteristic determined from the stored media file corresponds to the current activity within the virtual environment (e.g., see at least paragraphs 37 and 38 that discuss “style preference may be utilized by the system to generate music, for example based on contextual information occurring in the electronic game” or a “certain musical cue maybe selected based on the user reaching a particular progression point within the electronic game”);
[claim 21] wherein: analyzing the stored media file to determine the content characteristic includes analyzing the stored media file to determine a plurality of content characteristics (e.g., see at least paragraph 36, that discusses “the system may optionally access metadata information associated with music being streamed by the user”);
each content characteristic of the plurality of content characteristics is associated with a corresponding emotional characteristic (e.g., see at least paragraph 12 for discussion of indication of a “particular emotion or feeling to be achieved from the generated music”); the content characteristic is a first content characteristic of the plurality of content characteristics;
the first content characteristic is associated with a first emotional characteristic (e.g., see at least paragraph 12 for discussion of indication of a “particular emotion or feeling to be achieved from the generated music”);
analyzing the virtual environment includes identifying a second emotional characteristic associated with an in-game scene that is depicted in the current interactive session and that includes the character (e.g., see at least paragraph 38 that discusses different musical cues may be theme or emotion, wherein emotion is the first characteristic and theme is the second characteristic; alternatively, see paragraph 7 that describes more than one emotional response including “sadness, happiness, excitement, and so on”);
the in-game scene corresponds to a game that is different than the stored media file (e.g., see at least paragraph 43 for discussion of systems that “generate personalized music for different electronic games”); and
the computer-implemented method further comprises generating a determination that the first emotional characteristic corresponds to the second emotional characteristic, wherein modifying the parameter includes modifying at least one of music or scenery in the in-game scene to correspond to the first content characteristic based at least in part on the determination (e.g., see at least paragraphs 7 and 8 that discuss adjusting the music based on a combination of different emotional responses and styles); and
[claim 22] wherein modifying the parameter includes modifying the in-game scene to correspond to the first content characteristic based at least in part on the determination (e.g., see at least paragraph 10 that discusses “if this portion of music were to be adjusted in style to a second style, the users may have a much greater affinity, or emotional response, to in game events, actions, and so on”).
With regard to claim 1, 6 and 23, Kolen discloses all of the recited features but is silent regarding modifying a voice of an NPC or virtual object.
Reasonably pertinent to the problem faced, Nagar teaches modification of a voice (e.g., see at least paragraphs 18 and 74 for discussion of mimicking a voice). Additionally, in at least paragraph 97, Nagar teaches identifying persona for voice modification purposes when stating a persona is “identified by the AI/Machine learning engine…may modify the virtual agent…may include the application of one or more audio components…voice signature”. Additionally, paragarph 97 of Nagar discusses the settings include “speech patterns, slang, tone, grammar, speed, vocabular…”, which would not be audio that is identical to the player. While Nagar doesn’t recite the term “text-to-speech” model terminology, Nagar utilizes an AI to interpret speech patterns, which would include text.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the current invention to modify Kolen with the voice modification as taught by Nagar in order to use a known technique to improve similar devices (methods, or products) in the same way. In this case, the voice modification helps provide a more interesting voice output that is more entertaining.
With regard to claims 3 and 18, Kolen discloses all of the recited features but is silent regarding the stored media file being sensor data.
Reasonably pertinent to the problem faced, Nagar teaches the use of sensor data for media files (e.g., see at least paragraphs 38, 59, and 77 that discuss user data collection via sensors).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the current invention to modify Kolen with the sensor data taught by Nagar in order to use a known technique to improve similar devices (methods, or products) in the same way. In this case, the sensor data helps provide automatic user data input that reduces the user efforts and accurately collects data.
Claims 17 and 19 are made obvious by Kolen in view of Nagar based on the same analysis set forth above for claim 1, which is similar in claim scope.
Claims 5 and 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Kolen in view of Nagar and further in view of U.S. Patent Application Publication No. 2020/0298125 to Stroud.
With regard to claims 5 and 13-15, Kolen discloses all of the recited features but is silent regarding storing user inputs and generating a custom tutorial with mapped button input sequences.
Reasonably pertinent to the problem faced, Stroud teaches storing user inputs (e.g., see at least paragraphs 8, 16, 17, and 51 for discussion of storing a sequence of button presses) and generating a custom tutorial based on current activity with mapped button input sequences (e.g.., see at least Figs. 5A and 5B; see also paragraphs 108-114 that discuses analyzing a user’s behavior and to help a user better understand nuances of the game play and assist the user to improve the game play of the game; see at least paragraphs 108 and 109 that disclose that hints are provided based upon “game behavior of the user detected during play of the game, the game logic may generate behavior metrics for the user…behavior metrics may identify game hints…for the user to assist the user to improve his/her game play”) including an illustration (e.g., see at least Fig. 4B, illustration shown in “Hint C”; see also paragraph 109 that shows an icon on the GUI).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the current invention to modify Kolen with the button sequence and tutorials as taught by Stroud in order to use a known technique to improve similar devices (methods, or products) in the same way. In this case, the storing user button inputs sequence and generating a tutorial allows a user to learn from more skilled players by tracking the skilled players inputs.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Kolen in view of Nagar and further in view of U.S. Patent Application Publication No. 2022/0319087 to Zhang.
With regard to claim 10, Kolen discloses all of the recited features but is silent regarding modifying the appearance of a virtual character.
Reasonably pertinent to the problem faced, Zhang teaches modifying the appearance of a virtual character (e.g., see at least 46 that describes using a virtual camera to modify the facial appearance of a virtual character).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the current invention to modify Kolen with the facial modification for virtual characters as taught by Zhang in order to use a known technique to improve similar devices (methods, or products) in the same way. In this case, the modifying game facial appearances provides for a more personalized gaming experience that increases player enjoyment.
Response to Arguments
Applicant's arguments filed 2/17/2026 have been fully considered but they are not persuasive.
On page 7, final paragraph (continued on page 8), Applicant asserts that “neither Kolen nor Nagar teaches or suggests using a user’s voice to synthesize a character’s voice from a vocal waveform generated using the user’s voice.” The Examiner respectfully disagrees. When viewed in combination, Kolen teaches uses waveforms to modify game audio (e.g., see at least paragraph 72) and Nagar teaches that the use of modified voice data in a game (e.g., see paragraph 18 that includes a ranking algorism that considers “interactions with the user while conversing” including “tone, and other audio or visual indicators”). The rejection does not rely solely upon either Kolen or Nagar, but the rejection relies upon a combination of Kolen in view of Nagar. For at least this reason, claim 1 remains rejected.
On page 8, final paragraph (continued on page 9), Applicant argues that “Stroud fails to generating tutorial content based at least in part on current activity, as required by claim 13.” The Examiner respectfully disagrees. As set forth above in the body of the 103 rejection, Stroud teaches that hints are provided based upon current activity (e.g., see at least paragraphs 108 and 109, “game behavior of the user detected during play of the game, the game logic may generate behavior metrics for the user…behavior metrics may identify game hints…for the user to assist the user to improve his/her game play”)(emphasis added by the Examiner). For at least this reason, claim 13 remains rejected.
On page 9, Applicant argues that the newly added features of claim 23 are not taught by Nagar, “Nagar does not disclose or suggest training a text-to-speech (TTS) model on a specific stored media file, nor does it describe generating new utterances that were not present in the original audio.” The Examiner respectfully disagrees. In at least paragraph 97, Nagar teaches identifying persona for voice modification purposes when stating a persona is “identified by the AI/Machine learning engine…may modify the virtual agent…may include the application of one or more audio components…voice signature”. Additionally, paragarph 97 of Nagar discusses the settings include “speech patterns, slang, tone, grammar, speed, vocabular…”, which would not be audio that is identical to the player. For at least this reason, claim 23 is rejected.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES S MCCLELLAN whose telephone number is (571)272-7167. The examiner can normally be reached Monday-Friday (8:30AM-5:00PM).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached at 571-270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/James S. McClellan/Primary Examiner, Art Unit 3715
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