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 .
This action is in response to the Amendment filed on 01/29/2026.
Claims 1-22 are pending. Claim 1, 2, 13 have been amended.
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.
Claim(s) 1, 3, 5-6, 8-9, 11, 13-14, 16-17, 19-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Schriber et al. (US 20190155829 A1, hereinafter Schriber), in view of Mashrabov et al. (US 20200234483 A1, hereinafter Mashrabov).
Regarding Claim 13, Schriber teaches a system for generating video (Schriber, Paragraph [0013], [0056], “a system comprises a user interface presenting a visual representation of a script written in natural language text” “data library 220 may contain images of outfits associated with one or more characters, sketches (image and video), or any other relevant information or data that can be used to create and/or edit aspects of the script or visualization”),
implemented by one or more processors operatively coupled to a non-transitory computer readable storage device, on which are stored modules processors to perform the steps of (Schriber, Paragraph [0215], “Computing component 1200 might also include one or more memory components, simply referred to herein as main memory 1208…might be used for storing information and instructions to be executed by processor 1204”): - user interfaces module configured to receive user or entity instructions by text or voice using natural language (Schriber [0064], "FIG. 3A illustrates a script layout view with additional features presented in the UI to assist in writing a narrative story in natural English language. An example UI 300 ... includes editing panel 302 .. . Editing panel 302 ... is used to present a textual representation of a script. A user can add, edit, delete, and/or view the script."; [0070]-[0071], "[0070] In some embodiments, the user can record a soundtrack with their. .. voice over any dialog text as voice clips ... Characters assigned to the voice clips will be animated with lip sync technology ... [0071] ... a user may select an option to record spoken dialog of the script text. .. Time durations associated with the spoken dialog can be determined and presented to the user"); - video generation server configures for: - analyzing entity instructions, received in natural language using a trained AI analysis engine (Schriber, Paragraph [0016], “In one embodiment, the analytics engine is trained using known or most-used words representative of the one or more of the character, the action, and the location relevant to the scene”; [0123], “Rule sheets are capable of parsing structured natural language text to generate certain categories of rules and errors, which can then be used by the character systems, enabling them to make logical inferences on the information they possess.”; [0041], “In order to train frontend analytics engine 206 and/or backend analytics engine 212, a logical, formal language can be developed using known words or most-used words to represent or indicate a character, location, action, etc.); for identifying technical and creative requirements including: style, context and/or content, type and properties of content objects, [[ layout of video frames, ]] order sequence of displaying content, functionality of objects (Schriber [0060]-[0063], "compiler 214 ... analyze a script of consistency” “check ... structural errors ... errors in camera placement, prop placement” “contextual errors ... story-based inconsistencies” “Compiler 214 may generate one or more notifications” “determine that an interaction exists ... and determine that a call to action cue should be provided ... such as a lighting change or audio cue to direct the audience to that interaction"; [0065]-[0068], "A script may include a series of scenes ... elements ... ' modules.' Modules ... location, dialog, transition, or action” “A location module sets a new environment. .. dialog module sets a spoken conversation ... transition module sets a period of changing ... action module sets an expressive action” “Location, dialog and action modules are provided with the option of choosing a camera shot. .. a list of options ... common type of shots, common angle shots and common camera movements” “users have the option to manually edit the selected camera shot ... create a new camera shot. .. assign a name to their own personalized camera shot."). - selecting at least one video [[ template ]] of at least one scene based analysed instructions and all identified technical and creative requirements (Schriber [0065], "A script may include a series of scenes .. . 'modules.' ... A user can ... select a desired module and drag it to a desired point in the scri9t on editing panel 302."; [0067]-[0068], "Location, dialog and action modules are provided with the option of choosing a camera shot ... [a] list of options ... common type of shots, common angle shots and common camera movements ... users have the option to manually edit the selected camera shot. .. create a new camera shot ... assign a name to their own personalized camera shot"); wherein the selecting is performed autonomously by the system based on the identified technical and creative requirements (Schriber, Paragraph [0112], “Multiple pages (views) can be provided to the user that support a full creative workflow <read on creative requirements>, project editing, etc. All pages many have similar functions since they allow the user to register objects with all the needed attributes, validate those attributes, and save them in the back-end logic”; [0068], “the platform can recommend the most appropriate and common shot for the given module” [0118], “an external application, e.g., AR/VR applications 432/434, can be launched using application launcher 428. These executables or components may be fully independent <read on performed autonomously>, yet access the same persistent data. To exchange data”); . exploring and [[ aggregating ]] content of text, image or video multimedia based on identified technical and creative requirements of the selected at least one [[ template ]] (Schriber [0070]-[0072], "user can record a soundtrack with their. .. voice ... Characters ... animated with lip sync technology ... Time durations ... presented to the user” “record spoken dialog of the script text” “the script can be uploaded ... a script in a platform-specific format or other third-party format can be uploaded ... the platform may perform a conversion from a non-native platform format to the native platform format. .. "). generating new video by implementing selected or new video [[ template ]] using [[ aggregated ]] content wherein the generated video complies with all analyzed requirements (Schriber [0063], "As alluded to above, the disclosed platform provides ... the ability to generate storyboards", and [0073]-[0078], "time line view ... illustrate the evolution of each character in a scene” “There are lines and controls for each character, camera, and smart object. .. elements ... can also be dragged into different positions and overlapping positions” “The time duration of a transition can also be extended or reduced”).
But Schriber does not explicitly disclose [[ exploring and ]] aggregating [[ content of text, image or video multimedia based on identified technical and creative requirements of the selected at least one template ]] [[ generating new video by implementing selected or new video template using ]] aggregated [[ content wherein the generated video complies with all analyzed requirements ]].
However, Mashrabov teaches a system for generating video, implemented by one or more processors operatively coupled to a non-transitory computer readable storage device (Mashrabov, Paragraph [0005], “a system for generating personalized videos with customized text messages” “The system may include at least one processor and a memory storing processor-executable codes”; [0008], “the processor-readable instructions are executed by a processor ... to implement the above-mentioned method for generating personalized videos with customized text messages") video generation server configures for (Mashrabov, Paragraph [0038], “A user interface of the messenger 220 and the system 400 for template-based personalized videos can be provided via the graphical display system 230. The communication chats can be enabled via the communication module”):
analyzing [[ entity instructions for identifying technical and creative requirements including: ]] style, context and/or content, type and properties of content objects, layout of video frames, order sequence of disapplying content, [[ functionality of objects ]] (Mashrabov, Paragraph [0005] teaches "preset text parameters ... may describe visual effects applied to the text and include a font of the text, a color of the text, and a position of the text in at least one of the frame images. The visual effects may include a letter animation of appearance, displaying the text along a path, displaying copies of the text, a compression of the text, slicing of the text, a directional appearance of the text, a randomized letter appearance, a distortion and scaling of the text, a gradient fill of the text, adding a shadow and a glow to the text, adding a directional glow to the text, a flash appearance of the text, adding a perspective shadow to the text, applying a dynamic glow to the text, displaying a distorted shadow or an outline of the text, outlining the text, applying colored font assets to the text, and so forth" [0006] further teaches generating a "configuration file ... The text parameters may include a scale of the text, a position of the text in at least one frame ... a rotation of the text, a color of the text, a number of lines of the text, a maximum length of the text, and so forth ... The processor may be further configured to .. . render an output video comprising the sequence of frame images featuring the input text rendered according to the text parameters ... send the output video to a further computing device via a communication chat"); selecting at least one video template of at least one scene based analysed instructions and all identified technical and creative requirements (Mashrabov, Paragraph [0005), "The ... processor may be configured to receive a video template. The video template may include a sequence of frame images and preset text parameters defining an animation of a text"]); exploring and aggregating content of text, image or video multimedia based on identified technical and creative requirements of the selected at least one template (Mashrabov, Paragraph [0043]-[0047], FIG. 4 description, "The system 250 may receive a user face image 405, a video template 4I0, and an input text 407. The vide9 template 410 may include a sequence of frame images, face area parameters, facial landmark parameters, animated object images, and preset text parameters ... and a soundtrack. The system 250 may generate, based on the user data 435 and data sequences 420, frames 445 of a personalized video 440 ... The system 250 may further add the soundtrack to the personalized video 440."); Generating new video by implementing selected or new video template using aggregated content wherein the generated video complies with all analyzed requirements (Mashrabov, Paragraph [0006], "The processor may be further configured to receive an input text and render an output video comprising the sequence of frame images featuring the input text rendered according to the text parameters. The rendering may be performed based on the configuration file. The processor may be further configured to play back the output video in a full screen mode prior to sending the output video ... the user may be provided with an option to change the input text to a further input text and the input text may be dynamically changed in the displayed output video ... "; [0043]-[0047], "The system 250 may generate ... frames 445 of a personalized video 440 ... add the soundtrack ... ").
Mashrabov and Schriber are analogous since both of them are dealing with automated production of video content from user-provided input for rapid visual output. Schriber provides a way of parsing natural language scripts using a trained NLP analytics engine to generate structured scenes, storyboards, and pre-visualizations, but expressly stops short of producing a final rendered output video. Mashrabov provides a way of automatically rendering those organized scenes into a finished personalized video by applying predefined templates, style parameters and visual effects to the aggregated media content which teaches the missing downstream step of receiving structured scene templates and parameters and automatically rendering a finished, personalized output video. Therefore, it would ha e been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the template-driven automatic rendering and output video generation taught by Mashrabov into the system of Schriber such that The combined system can performs its known function in a way that yielding the predictable result of a complete end-to-end pipeline: from natural language input through NLP analysis and scene structuring to final rendered personalized video output
Regarding Claim 14. the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches wherein the video generation server the further configured to explore and aggregate content from different internal and/or external sources content of text, image or video multimedia based on identified technical and creative requirements (Schriber, Paragraph [0070], “the user can record a soundtrack with their (or another’s) voice over any dialog text as voice clips ... Characters assigned to the voice clips will be animated with lip sync technology, [0071], “Time durations associated with the spoken dialog can be determined and presented to the user", “a user may select an option to record spoken dialog of the script text”, [0072) “the script can be uploaded to the platform. That is a script in a platform-specific format or other third-party format can be uploaded ... the platform may perform a conversion from a non-native platform format to the native platform format”; it is noted the user recorded soundtrack and script text are different sources content and it is aggregated into final output].
But Schriber does not explicitly aggregating image or video multimedia from different internal and/or external sources content.
However, Mashrabov teaches explore and aggregate content from different internal and/or external sources content of text, image or video multimedia (Mashrabov, Paragraph [0047], [0051], "The system 250 may receive a user face image 405, a video template 410, and an input text 407. The video template 410 may include a sequence of frame images, face area parameters, facial landmark parameters, animated object images, and preset text parameters ... and a soundtrack. The system 250 may generate, based on the user data 435 and data sequences 420, frames 445 of a personalized video 440” “The system 250 may further add the soundtrack to the personalized video 440").
Mashrabov and Schriber are analogous since both of them are dealing with automated production of video content from user-provided input for rapid visual output.
Schriber provided a way of taking user-provided narrative/script content and spoken dialog and importing outside script files, and combining them for use in scene construction and timing. Mashrabov provided a way of assembling text, user-provided images, pre-existing template media, and soundtrack into a generated personalized video. Therefore, it would have been obvious to one of ordinary skill in the art to combine Mashrabov's multi-source aggregation of text, user face image, and template media into modified invention of Schriber's such that when script/audio/externally uploaded material, the system can pull all needed assets (text, voice, image, video frames, soundtrack) from various sources and merge them into the automatically generated video.
Regarding Claim 16. the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches wherein the user interface module is further configured to enable entity entering more instruction/editing previous instruction (Schriber, Paragraph [0064], "An example UT 300 ... includes editing panel 302 . .. Editing panel 302 ... is used to present a textual representation of a script./\ user can add, edit, delete, and/or view the script"), enabling to select manually more relevant media or use external services enabling to upload media or text or delete scenes or update the script (Schriber, Paragraph [0065] “A user can ... select a desired module and drag it to a desired point in the script on editing panel 302." [0024], “FIG. 5A is an example of a parse request message to an external processing component in accordance with various embodiments” [0072] “the script can be uploaded to the platform ... a script in a platform-specific format or other third party format can be uploaded ... the platform may perform a conversion from a non-native platform format to the native platform format.").
Regarding Claim 17. the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches wherein the user interface module is further configured user [[ approving final version and ]] enabling manual editing option (Schriber, Paragraph [0064]”Editipg panel 302 . .. A user can add, edit, delete, and/or view the script", [0060], [0062] “compiler 214 ... analyze a script for consistency ... generate one or more notifications ... suggesting .. . a call to action cue ... lighting change or audio cue to direct the audience").
But Schriber does not explicitly disclose user approving final version.
However, Mashrabov teaches the user interface module is further configured user approving final version and enabling manual editing option (Mashrabov, Paragraph [0058] “The processor may be further configured to play back the output video in a full screen mode prior to sending the output video” [0006], “the user may be provided with an option to change the input text to a further input text and the input text may be dynamically changed in the displayed output video”; it is noted that since user change and output the video which means the final version is approved by the user).
Mashrabov and Schriber are analogous since both of them are dealing with automated production of video content from user-provided input for rapid visual output. Schriber provided a way of letting the user manually edit script content in response to system suggestions. Mashrabov provided a way of previewing the rendered video, editing it, and only then sending it out. Therefore, it would have been obvious to one of ordinary skill in the art to include a preview-and-approval step like Mashrabov's playback-before-sending in Schriber’s editing workflow so that users can both edit and sign off on a final version before distribution.
Regarding Claim 19, the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches wherein the video generation server the further configured to define scenario parts or scene based on created determined script or user text (Schriber, Paragraph [0065]-[0066], "A script may include a series of scenes. Each scene can be thought of as containing elements referred to herein as 'modules.' Modules may describe each sentence of the script” “A location module sets new environment ... dialog module sets a spoken conversation .. . transition module sets a period of changing ... action module sets an expressive action taken by the characters of the scene").
Regarding Claim 20, the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches wherein the video generation server the further configured to select [[ multiple block template ]] of different scene (Schriber, Paragraph "[0065] A script may include a series of scenes ... ' modules.' ... A user can ... select a desired module and drag it to a desired point in the script on editing panel 302."; [0067]-[0068], "Location, dialog and action modules are provided with the option of choosing a camera shot. .. a list of options ... common type of shots, common angle shots and common camera movements ... users have the option to manually edit the selected camera shot. .. create a new camera shot. .. assign a name to their own personalized camera shot.").
But Schriber does not explicitly disclose multiple block template [[ of different scene ]].
However, Mashrabov teaches wherein the video generation server the further configured to select multiple block template of different scene (Mashrabov), Paragraph [0005], “The at least one processor may be configured to receive a video template. The video template may include a sequence of frame images and preset text parameters defining an animation of a text” [0006], “render an output video comprising the sequence of frame images featuring the input text rendered according to the text parameters” [0050], “frames 445 of a personalized video 440. The personalized video 440 may be generated in the form of an audiovisual media” [0023], “The video template may include a sequence of animated object images” [0046], “The video template 410 may further include… animated object images, and preset text parameters…. may further include a soundtrack.”)
Mashrabov and Schriber are analogous since both of them are dealing with automated production of video content from user-provided input for rapid visual output. Schriber provided a way of choosing and arranging per-scene building blocks (modules + camera shots) across different scenes. Mashrabov provided a way of instantiating scene content from reusable templates that define frame sequences, object imagery, and soundtrack. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate template blocks taught by Mashrabov into modified invention of Schriber’s such that multiple different scene blocks could each be realized as actual rendered segments in a final personalized video.
Regarding Claim 21. the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches wherein the user or entity defines length of video, wherein the defined length affects the selection of subjects based on priority, the focus in each subject and selection content for each subject to meet the time limit (Mashrabov, Paragraph [0006] ... The text parameters may include ... a number of lines of the text, a maximum length of the text. .. The scale may be adjusted ... determined to fit the input text into bounds of the frame images," and then "render an output video comprising the sequence of frame images featuring the input text rendered according to the text parameters"; it is noted this shows enforcing constraints so that content is sized/limited to fit requirements).
Mashrabov and Schriber are analogous since both of them are dealing with automated production of video content from user-provided input for rapid visual output. Schriber provided a way letting the user directly control the timing and overlap of dialog, action, and transitions on a timeline. Mashrabov provided a way of enforcing per-frame content limits (e.g., maximum length of displayed text) so the final output respects duration/space constraints. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate per-frame content limiting taught by Mashrabov into modified invention of Schriber’s such that so that overall runtime and per-scene emphasis could be tuned to fit a desired total time budget.
Regarding Claim 1, it recites limitations similar in scope to the limitations of Claim 13 but as a method and the combination of Schriber and Mashrabov teaches all the limitations as of Claim 13. Therefore is rejected under the same rationale.
Regarding Claim 3, it recites limitations similar in scope to the limitations of Claim 14 and therefore is rejected under the same rationale.
Regarding Claim 5, it recites limitations similar in scope to the limitations of Claim 16 and therefore is rejected under the same rationale.
Regarding Claim 6, it recites limitations similar in scope to the limitations of Claim 17 and therefore is rejected under the same rationale.
Regarding Claim 8, it recites limitations similar in scope to the limitations of Claim 19 and therefore is rejected under the same rationale.
Regarding Claim 9, it recites limitations similar in scope to the limitations of Claim 20 and therefore is rejected under the same rationale.
Regarding Claim 11, it recites limitations similar in scope to the limitations of Claim 21 and therefore is rejected under the same rationale.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Schriber et al. (US 20190155829 A1, hereinafter Schriber), in view of Mashrabov et al. (US 20200234483 A1, hereinafter Mashrabov) as applied to Claim 1 above and further in view of Galant et al. (US 20160365114 A1, hereinafter Galant)
Regarding Claim 2. the combination of Schriber and Mashrabov teaches the invention in Claim 1.
The combination further teaches generating multiple videos which implement selected or new video template using aggregating content wherein the generated video complies with all analyzed requirements (Mashrabov, Paragraph [0006], "The processor may be further configured to receive an input text and render an output video comprising the sequence of frame images featuring the input text rendered according to the text parameters. The rendering may be performed based on the configuration file. The processor may be further configured to play back the output video in a full screen mode prior to sending the output video ... the user may be provided with an option to change the input text to a further input text and the input text may be dynamically changed in the displayed output video ... "; [0043]-[0047], "The system 250 may generate ... frames 445 of a personalized video 440 ... add the soundtrack ... "), wherein each video use different template or using different content or properties of objects (Mashrabov, Paragraph [0005]-[0006], "The ... processor may be configured to receive a video template ... The preset text parameters may describe visual effects ... font ... color. .. position ... letter animation ... gradient 11. .. shadow ... glow ... [0024], “he computing device may further generate, based on the image of the face and one of the pre-generated video templates” [0006] The processor may ... generate a configuration file ... text parameters ... scale ... rotation ... number of lines ... maximum length ... [and] render an output video comprising the sequence of frame rages featuring the input text rendered according to the text parameters"); enabling entity to select one of the videos (Mashrabov, Paragraph [0046],“the user may have access to an interface that allows to customize personalized videos not only by adding text and changing parameters of the text, but also by selecting other parameters”),
The combination does not explicitly disclose but Galant teaches - enabling entity to select one of the videos, saving entity history choice (Galant, Paragraph [0060], “A video capture, highlighting, editing, storage, sharing and viewing system is described. The system records or otherwise captures and/or receives from one or more other capture devices raw video and generates or receives metadata or signal information associated with the video and or certain portions thereof. The system then, via adaptable editing, generates one or several versions of videos (e.g., movies), which may include one or several variant versions of the rough-cut of the raw video data and one or several versions variants of the final-cut. The process of determining the rough-cut and or the final-cut is based on the metadata generated” [0063], “A variety of rough-cut or final-cut video versions may be generated based on different interpretation of the signal data by different stakeholders, systems or people. That is, the system allows different editors to create and ultimately view different, personalized versions of a movie. Therefore, when a video recording is made, the different versions ultimately generated from the video recording are not limited to a fixed result, but a dynamically malleable "movie" that can be modified based on the interpretation of the meta data using the preferences of different users), learning personalized entity preferences (Galant, Paragraph [0113] "session interpreter 325 has access to .. . previous highlight list data 230 of an individual user ... determines if a session should be members of a given theme ... create theme compilation master highlight list 340," [0121]-[0122] "the highlights of the individual sessions are ranked by score, tagged by type ... rules ... can be set by a stakeholder (originator, intermediary, viewer) ... These compilations movies are presented to the viewer ... "); creating Ai model by learning plurality of user's choice, training video editing rules (Galant, Abstract "a machine learning module operable to access data from memory and operable to generate settings to control the editing processing logic ... using one or more machine learning algorithms," Paragraph [0147]-[0151] "machine learning logic 551 ... generates settings to control the editing processing logic ... applying ... machine learning algorithms to data collected regarding previous edits made by ... an originator. .. an intermediary ... and a viewer .. . [and] viewing information associated with viewing performed on raw, rough cut clips or final cut clips").
Galant and Schriber are analogous since both are directed to automated generation of personalized video outputs for a user by software running on processors Schriber provided a way of generating personalized video on automatically producing multiple personalized video variants from templates and user specific visual/text parameters. Galant provided a way of generating video focuses on producing multiple final cut clips / versions, letting stakeholders drive which version is preferred, storing stakeholder highlight/selection data. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate Galant's machine learning module into Schriber 's system such that after generating those multiple personalized videos, the system records which version the user prefers and uses that stored selection history to train/adjust editing rules for future automatically generated personalized videos.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Schriber et al. (US 20190155829 A1, hereinafter Schriber), in view of Mashrabov et al. (US 20200234483 A1, hereinafter Mashrabov) as applied to Claim 1 above and further in view of Dayan et al. (US 20150332666 A1, hereinafter Dayan) and Dorner et al. (US 11375256 B1, hereinafter Dorner).
Regarding Claim 10. the combination of Schriber and Mashrabov teaches the invention in Claim 1.
The combination further teaches further comprising the step of: generating content [[ using designated AI model ]] by determining context and/or content (Schriber, Paragraph [0060]-[0063], "compiler 214 ... analyze a script for
consistency ... contextual errors ... story-based inconsistencies ... determine that an interaction exists between two or more characters in a particular portion of a scene."), [[ emotion, theme number, type and properties of content objects, layout of video frames, ]] order, sequence of disapplying content (Schriber, Paragraph [0065]-[0068], [0073]-[0078] "A script may include a series of scenes ... 'modules' ... transition module sets a period of changing from one state to another ... ," and "There are lines and controls for each character, camera, and smart object. .. elements ... can also be dragged into different positions and overlapping positions ... The time duration of a transition can also be extended or reduced”),
functionality of objects (Schriber, Paragraph [0062]-[0063], "determine that a call to action cue should be provided ... such as a lighting change or audio cue to direct the audience to that interaction”).
Schriber does not explicitly disclose but Mashrabov teaches type and properties of content objects, layout of video frames (Mashrabov, Paragraph [0005]-[0006], “the ... video template ...may include a sequence of frame images and preset text parameters defining an animation of a text. The preset text parameters may describe visual effects applied to the text and include a font. .. a color. .. a position of the text in at least one of the frame images ... The text parameters may include a scale ... a rotation ... a number of lines ... a maximum length" "a position of the text in at least one of the frame images," "displaying the text al9ng a path," "sequence of frame images," "render an output video comprising the sequence of frame images featuring the input text rendered according to the text parameters.").
Mashrabov and Schriber are analogous since both of them are dealing with automated production of video content from user-provided input for rapid visual output. Schriber provides a way of turning use-written or spoken storyline into structured scenes with modules, camera shorts and timing to build a storyboard and timeline. Mashrabov provides a way of automatically rendering those organized scenes into a finished personalized video by applying determined type and properties of content objects, layout of video frames to the aggregated media content. Therefore, it would ha e been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the multi parameter affect like type and properties of content objects, layout of video frames into taught by Mashrabov into the system of Schriber such that a user’s described scenes and creative choices could be converted by using multiple factors which increase the functionality of the sytem.
The combination does not explicitly disclose but Dayan teaches theme number (Dayan, Paragraph [0018], [0063]-[0064], "movie characteristics are selected from among: speed; tempo; colors and fonts; sentiment; look and feel ; and site properties; type of visual representation; and type of video output," and elaborates "Look and feel (Themes and which media templates to use) ... Site properties")
Dayan and Schriber are analogous since both of them are dealing with automated video creation systems with scene level customization. Schriber provided a way of automated video creation systems with user-driven scene editing and personalization. Dayan provided a way of using different parameter like theme number reflect branding during the automated video creation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate the theme number parameter taught by Dayan into the modified invention of Schriber such that in the automated video creation, systems will be able to using theme number to properly categorize the proper scene in order to create more accurate video based on the them determined.
The combination does not explicitly disclose but Dorner teaches generating content using designated AI model (Dorner, Column 1, Line 55-60, “Using artificial intelligence or machine learning systems to build and use computer models for identifying or predicting intensity of emotional reactions elicited by a particular video”) determining emotion (Dorner, Column 1, Line 59-61, “determine which particular emotional reaction corresponds to certain times during the video”, Column 22, Line 42-45, “generate category-specific intensity timelines…represent the intensity of specific emotional reactions elicited at various timecodes throughout the video” , Column 18, Line 32-35, “The category-specific intensity timelines 274 can be stored in association with the video in the video's profile in the video profiles data 35 repository 210”, Column 22, Line 52-53, “as a graphical representation of a plot tension timeline)”.
Dorner and Schriber are analogous since all are directed to automated video generation or automated video structuring Schriber provided a way of parsing user-authored story content into scenes/modules with timeline control and attention cues. Dorner provided a way of using machine learning models to generate emotion timelines by scene/timecode, i.e. assigning emotional intensity and category to specific time segments of a video. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the AI emotion timeline modeling taught by Dorner into modified invention of Schriber such that a designated AI model can generate content while determining context/content, emotion, theme, object properties, frame layout, temporal order/sequence, and functional cues for objects.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Schriber et al. (US 20190155829 A1, hereinafter Schriber), in view of Mashrabov et al. (US 20200234483 A1, hereinafter Mashrabov) as applied to Claim 1, 13 above respectively and further in view of Dayan et al. (US 20150332666 A1, hereinafter Dayan).
Regarding Claim 15. the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches wherein all scene media parts are customized and personalized (Schriber, Paragraph [0067]-[0068], "Location, dialog and action modules are provided with the option of choosing a camera shot. .. a list of options ... common type of shots, common angle shots and common camera movements ... users have the option to manually edit the selected camera shot. .. [and) create a new camera shot ... assign a name to their own personalized camera shot."). [[ based entity or entity branding/profile data, the branding can be provided by entity or by smart analyzing any entity content. ]]
But, the combination does not explicitly disclose based entity or entity branding/profile data, the branding can be provided by entity or by smart analyzing any entity content.
However, Dayan teaches wherein all scene media parts are customized and personalized based entity or entity branding/profile data (Dayan, Paragraph [0016], “data is extracted from the input text and from other sources of information relevant to it, so that the text can be analyzed as a whole and with respect to its main content” “the information extracted from a text may include: images and video from the source page; meta-data; page-links; tweets; author details; date; comments; CSS; and rating” [0017], “the analysis ... is performed according to the criteria of: content categorization; entities and data elements extraction and mapping ... defining the general properties of the text: main subject, main entity, location, event, etc.; and sentiment analysis of the entire text source and specific entities" [0018], “In an embodiment of the invention the movie characteristics are selected from among: speed; tempo; colors and fonts; sentiment; look and feel; and site properties; type of visual representation; and type of video output”), the branding can be provided by entity or by smart analyzing any entity content (Dayan, Paragraph [0018], “the movie characteristics are selected from among: speed; tempo; colors and fonts; sentiment; look and feel; and site properties; type of visual representation; and type of video output” [0059]-[0064], Speed (animations, soundtrack, etc.); Tempo; Colors and fonts; Sentiment; Look and feel (Themes and which media templates to use)-News, sports, entertainment, recipes, manuals, education, e-commerce, advertisements etc.; Site properties).
Dayan and Schriber are analogous since both of them are dealing with automated video creation systems with scene level customization. Schriber provided a way of automated video creation systems with user-driven scene editing and personalization. Dayan provided a way of deriving style (colors, fonts, themes) from entity content to reflect branding during the automated video creation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate the entity-driven style attribution taught by Dayan into the modified invention of Schriber such that in th e automated video creation, systems will be able to ensure the generated video retains a consistent brand appearance for the entity.
Regarding Claim 4, it recites limitations similar in scope to the limitations of Claim 15 and therefore is rejected under the same rationale.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Schriber et al. (US 20190155829 A1, hereinafter Schriber), in view of Mashrabov et al. (US 20200234483 A1, hereinafter Mashrabov) as applied to Claim 1, 13 above respectively and further in view of Henderson (US 20220292543 A1).
Regarding Claim 18, the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination further teaches where the video generation server the further configured to determine script or story board (Schriber [0063], "As alluded to above, the disclosed platform provides ... the ability to generate storyboards," and [0065]-[0068] Examples of modules may be any of the following: location, dialog, transition, or action… A transition module sets a period of changing from one state to the other, normally used at the beginning and the end of each scene … [0069], “Each module, and therefore each camera shot, will create a frame for a storyboard that can be generated.”),
Schriber does not explicitly disclose but Mashrabov teaches define style [[ by a designated AI model ]] based on user text [[ using external AI system and ]] user/company profile [[ and branding ]] (Mashrabov, Paragraph [0005], “The video template may include a sequence of frame images and preset text parameters defining an animation of a text … include a font of the text, a color of the text, and a position of the text… The visual effects may include… a gradient fill of the text, adding a shadow and a glow to the text, adding a directional glow to the text, a flash appearance of the text, adding a perspective shadow to the text, applying a dynamic glow to the text, displaying a distorted shadow or an outline of the text, outlining the text, applying colored font assets to the text, and so forth [0006], “The processor may be further configured to generate a configuration file based on the text and the preset text parameters…The text parameters may include.. scale ... rotation ...number of lines ... maximum length ... render an output video ... featuring the input text rendered according to the text parameters).
The combination does not explicitly disclose the define style by a designated AI model [[ based on user text ]] using external AI system and user/company profile and branding.
However, Henderson teaches the define style by a designated AI model based on user text using external AI system and user/company profile and branding (Henderson, Paragraph [0015], “This method may further comprise of a repurposing recommendation machine learning system designed to generate and provide suggestions” [0005], “using a social graph learning database comprised of the recording keeping or business registration data input criteria, of the master account user interface” “engineer datasets that represent a target market or consumer user profile, according to data obtentions such as but not limited to, user statistics” [0012], “The method further comprising a staging technique which may be used to add scaled virtualizations of product inventory items or branding materials”
Henderson and Schriber are analogous since both of them are dealing with real time video content processing from user-provided input. Schriber provided a way of choosing and arranging per-scene building blocks (modules + camera shots) across different scenes. Henderson provided a way of using machine learning model to train and process the video generation process. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate machine learning process taught by Henderson into modified invention of Schriber’s such that when generating the video content in real time, system will be able to use machine learning model to efficiently adjust the video content for the finest result suitable for user to view.
Regarding Claim 7, it recites limitations similar in scope to the limitations of Claim 18 and therefore is rejected under the same rationale.
Claim(s) 12, 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Schriber et al. (US 20190155829 A1, hereinafter Schriber), in view of Mashrabov et al. (US 20200234483 A1, hereinafter Mashrabov) as applied to Claim 1, 13 above respectively and further in view of Rathod (US 20210042724 A1).
Regarding Claim 22, the combination of Schriber and Mashrabov teaches the invention in Claim 13.
The combination does not explicitly disclose but Rathod teaches further teaches
wherein the function of the object is call to action including: hyperlink of communication network, payment or purchase button (Rathod, Paragraph [0030], “selecting one or more types of controls or objects including actions, call-to-actions, reactions from list of controls… enabling to associating or attaching or integrating or embedding said selected one or more types of one or more controls, objects, functions” [0002], “call-to-actions, wherein various types of call-to-actions comprises … Like us on Facebook, subscribe to channel, view our photos, add us, connect on LinkedIn, follow us on Twitter < read on hyperlink >” [0460], “User can enter amount 3810 and can tap on payment button 3820. In the event of tapping on payment button 3820, server module 154 retrieves and decode encrypted information in QR code 3815 including merchant account details” [0463], “electronic catalogue(s) of products and services, possibly directed to the user, via a communication network, such as via a mobile communication device”).
Rathod and Schriber are analogous since both of them are dealing with automated production of video content from user-provided input for rapid visual output including call to action. Schriber provided a way letting the user directly control the timing and overlap of dialog, action, and transitions on a timeline. Rathod provided a way of communicate with user using hyperlink and/or payment/purchase button during video process. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate hyperlink and purchase/payment call button taught by Rathod into modified invention of Schriber’s such that during the video process, system will be able to provide additional functionalities like hyperlink and call button for payment/purchase which provide more user friendly and easy to access system.
Regarding Claim 12, it recites limitations similar in scope to the limitations of Claim 22 and therefore is rejected under the same rationale.
Response to Arguments
Applicant’s arguments with respect to claim 1, 13, filed on 01/29/2026, with respect to rejection under 35 USC § 103 have been considered but is not persuasive.
Applicant asserts that prior art Schriber does not teach a trained AI analysis engine for analyzing natural language instructions.
In response to the argument, prior art Schriber teaches in Paragraph [0016] and [0123], [0041] that system provided a way of parsing structured natural language text based on a trained analytics engine to analyze the words, action and relevant information which means compiler 214 (the rule-based checker) and analytics engine 206/212 (the NLP-trained metadata extractor) explicitly states the analytics engine is trained using domain-representative words for character, action, and location extraction from natural language scripts. Since the claim language of amended claim does not require that instructions be entirely unstructured, hence the combination of prior arts fully anticipate the limitation. Therefore, applicant remark cannot be considered persuasive.
Applicant further assert that the prior arts does not teaches autonomous template selection based on AI-determined requirements.
In response to the argument, prior art Schriber teaches in Paragraph [0068], [0112], [0118] that system provided with creative workflow with detail validation of data and executing them fully independently which is performed autonomously and can recommending the most appropriate and common shot for the given module. Mashrabov further teaches in Paragraph [0025]-[0026] that the system is automated template-driven rendering pipeline. Hence the prior art combination fully anticipate the limitations, therefore, applicant remark cannot be considered persuasive.
Applicant further asserts the proposed combination lacks proper motivation.
In response to the argument, as stated in the rejection above in Claim 13, both Schriber and Mashrabov are directed to automated multimedia video generation from user-provided input. Schriber explicitly discloses parsing natural language scripts and generating storyboards and pre-visualizations, but acknowledges that its output stops at pre-visualization and storyboards. Mashrabov provides precisely the missing final rendering step by taking structured input and generating a finished personalized video using templates. Combining a known NLP-analysis front-end from Schriber with a known template-driven rendering back-end by Mashrabov to fill this recognized gap. It must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In regard to Claims 2-12, 14-22, they directly/indirectly depends on independent Claim 1, 13 respectively. Applicant does not argue anything other than the independent claim 1, 13. The limitations in those claims in conjunction with combination previously established as explained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20240095987 A1 CONTENT GENERATION
US 20230385541 A1 METHOD AND SYSTEM FOR PRODUCING UNIFIED NATURAL LANGUAGE PROCESSING OBJECTS
US 20220309715 A1 IMAGE ENTITY EXTRACTION AND GRANULAR INTERACTIVITY ARTICULATION
US 20220156823 A1 SYSTEM AND METHOD FOR PRODUCT SEARCHING BASED ON NATURAL LANGUAGE PROCESSING
US 20190279432 A1 METHOD AND DEVICE FOR EDITING VIRTUAL SCENE, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM
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/YuJang Tswei/Primary Examiner, Art Unit 2614
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