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 .
Status of Claims
This is a final rejection in response to remarks/amendments filed on 03/09/2026. Claims 1-8, and 14-16 have been amended. Claims 17-21 have been added. Claims 9-13 have been cancelled. Therefore, claims 1-8, and 14-21 are pending and are examined herein.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed on 01/09/2025, with priority to JP2021-120673 filed on 07/21/2021.
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 1-8, and 14-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Is the claim to a Process, Machine, Manufacture, or Composition of Matter?
Claim 1 Preamble: An information processing apparatus comprising: circuitry configured to:
Claim 15 Preamble: An information processing method comprising:
Claim 16 Preamble: A non-transitory computer-readable medium having embodied thereon a program, which when executed by a computer causes the computer to execute an information processing method, the method comprising:
Claims 1-8, and 14-21 are to at least one potentially eligible subject matter category, and are therefore to be further analyzed under step 2.
Step 2a Prong 1: Is the claim directed to a Judicial Exception (A Law of Nature, a Natural Phenomenon (Product of Nature), or An Abstract Idea?)
The claims under the broadest reasonable interpretation in light of the specification are analyzed herein. Representative claims 1, 15 and 16 are marked up, isolating the abstract idea from additional elements, wherein the abstract idea is set in bold and the additional elements have been italicized as follows:
Claim 1 Preamble: An information processing apparatus comprising: circuitry configured to:
Claim 15 Preamble: An information processing method comprising:
Claim 16 Preamble: A non-transitory computer-readable medium having embodied thereon a program, which when executed by a computer causes the computer to execute an information processing method, the method comprising:
Claim 1 Body (also representative of claims 15 and 16):
estimate a value caused by content on a basis of information of one or more of setting element set for generating the content;
generate correction information regarding correction of the setting element on a basis of comparing the estimated value with a target value;
store the content and correction information in a memory;
control a displaying of, on a display, the correction information for selection by an operation by a user by referring to the correction information stored in the memory;
control a displaying of, by the display and in response to the user performing the operation to select the correction information, the content corrected by the correction information by referring to the correction information stored in the memory and a user interface (UI) for selection by an operation by the user to revert the corrected content to the content before the correction is performed; and
control a displaying of, by the display and in response to the user performing the operation to revert the corrected content to the content before the correction is performed, the content before the correction is performed by referring to the content stored in the memory.
When evaluating the bolded limitations of the claims under the broadest reasonable interpretation in light of the specification, it is clear that representative claims 1, 15, and 16 recite the abstract idea category of certain methods of organizing human activity. This abstract idea grouping found in MPEP 2106.04(a)(2)(II) includes claims to “managing personal behavior or relationships or interactions between people” and includes social activities, teaching, and following rules or instruction The steps of estimating a value caused by content...,comparing the estimated value with a target value, and outputting correction information regarding correction of the setting element is merely an act of managing personal behavior since it results in a data output that merely recommends a user to make certain corrections to a setting element. For more context, the claims are read in view of the specification which states in [0016-0017], “there may be a target value such as a desire to create a video of a predetermined length that is likely to be popular, such as within 10 minutes....[0017] Therefore, in the present embodiment, information regarding correction of a setting element for content generation is output according to a target of a predetermined value generated by the content... at the stage of producing the scenario or deciding the setting of the story, a predetermined value (for example, temporal length, shooting cost, revenue, or the like) generated by the content (for example, video) as a result is estimated, the estimated value is compared with the target value, and correction of the setting element (addition or deletion of the setting element) is presented to the user on the basis of the comparison result. This can support creation of better content.” Therefore, performing estimations and comparing it to the target outcomes is an example of rules, teachings, or instructions, which manage the personal behavior, or interactions between individuals which is a “certain method of organizing human activity” in MPEP 2106.05(a)(2)(II)(C).
Even when considering the amended limitations store the content and correction information; control a displaying of the correction information for selection by an operation by a user by referring to the correction information stored; control a displaying of, the content corrected by the correction information by referring to the correction information stored for selection by an operation by the user to revert the corrected content to the content before the correction is performed; and control a displaying of the content before the correction is performed by referring to the content, these steps are no more than a set of instructions to carry out interactions between a user and a computer to ultimately manage interactions between people. MPEP 2106.04(a)(2)(II) states, “Finally, the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the "certain methods of organizing human activity" grouping. It is noted that the number of people involved in the activity is not dispositive as to whether a claim limitation falls within this grouping. Instead, the determination should be based on whether the activity itself falls within one of the sub-groupings.” Therefore, the mere fact that the activity involves interactions with an interface is not dispositive to whether the claims fall within the grouping, and the activity itself (which allows a user to perform corrections to interaction content) falls squarely within the subgrouping.
Furthermore, the bolded claims also consists of mental processes, found in MPEP 2106.05(a)(2)(III), which are steps that “can be performed in the human mind, or by a human using a pen and paper” considered to be an abstract idea. In their current plain language, the claims recite the estimation of a value caused by a setting element, which can be performed in the human mind through a series of observations, evaluations, judgments, and opinions. Comparing this estimated value to a target value and outputting correction information based on the comparison can also be performed in the human mind(where outputting correction information is just the communication of recommendations). Therefore, the claims recite an abstract idea and are to be further analyzed under step 2a Prong 2.
Step 2A Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application?
Claims 1, 15, and 16 recite the following additional elements:
- apparatus comprising: circuitry in claim 1
- A non-transitory computer-readable medium having embodied thereon a program, which when executed by a computer causes the computer in claim 16
-memory in claims 1, 15 and 16
- a display, in claims 1, 15 and 16
- a user interface (UI) in claims 1, 15 and 16
The additional elements are no more than a recitation of the words “apply it” (or an equivalent) or mere instructions to implement an abstract idea or other exception on a computer on its ordinary capacity as outlined in MPEP 2106.05(f). In this case, the abstract idea of “estimate a value caused by content on a basis of information of one or more of setting element set for generating the content;
generate correction information regarding correction of the setting element on a basis of comparing the estimated value with a target value; store the content and correction information; control a displaying of the correction information for selection by an operation by a user by referring to the correction information stored; control a displaying of, the content corrected by the correction information by referring to the correction information stored for selection by an operation by the user to revert the corrected content to the content before the correction is performed; and control a displaying of the content before the correction is performed by referring to the content” is merely instructed to be performed as software functions on generic computing components such as circuitry, non-transitory computer readable media, computer, memory, display, and user interface. As stated in MPEP 2106.05(f), “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, whether analyzed individually or in combination, the additional elements do not integrate the claims into a practical application. Therefore, the claims are directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Claims 1, 15, and 16 recite the following additional elements:
Claims 1, 15, and 16 recite the following additional elements:
- apparatus comprising: circuitry in claim 1
- A non-transitory computer-readable medium having embodied thereon a program, which when executed by a computer causes the computer in claim 16
-memory in claims 1, 15 and 16
- a display, in claims 1, 15 and 16
- a user interface (UI) in claims 1, 15 and 16
The additional elements have also not been found to include significantly more in order to consider it an inventive concept for the same reasons set forth in Prong 2. The additional elements are no more than a recitation of the words “apply it” (or an equivalent) or mere instructions to implement an abstract idea or other exception on a computer on its ordinary capacity as outlined in MPEP 2106.05(f). More specifically, the use of generic computing components such as a circuitry, non-transitory computer readable media, computer, memory, display, and user interface to perform the abstract idea of “estimate a value caused by content on a basis of information of one or more of setting element set for generating the content; generate correction information regarding correction of the setting element on a basis of comparing the estimated value with a target value; store the content and correction information; control a displaying of the correction information for selection by an operation by a user by referring to the correction information stored; control a displaying of, the content corrected by the correction information by referring to the correction information stored for selection by an operation by the user to revert the corrected content to the content before the correction is performed; and control a displaying of the content before the correction is performed by referring to the content” does not amount to significantly more. These elements do not provide significantly more, because they do not meaningfully limit the use of the field on the abstract idea. Furthermore, improvements to the technology or technical field have not been purported. Please review MPEP 2106.05(a) for more information regarding improvements to computing devices(Section I), or technological fields(Section II). Therefore, the claims do not include additional elements even when considered separately and as an ordered combination, that provide significantly more in order to be considered as an inventive concept. Therefore, the claims are directed to an abstract idea without integration into a practical application or significantly more and are not patent eligible.
The dependent claims 2-14 are also given the full two-part analysis, individually and in combination with the claims they depend on, in the following analysis:
Claims 2, 3, 4, 5, 6 merely further limit the abstract idea by further specifying that setting elements are increased, decreased, added or deleted, as a result of difference between the estimated value and target value. More specifically, claim 4 recites that the addition or deletion of setting elements is determined using learning data of content generate in the past. This is more of the same abstract idea since it merely indicates the resulting output of the generally stated data processes. The output, whether it is a recommendation to increase/decrease/add/delete setting elements is still a set of instructions in order to manage personal behavior, therefore it still represents “certain methods of organizing human activity.” The fact that this is performed according to a difference between the target value and the estimated value, or by using learning data, is just an indication of the data collection steps. Furthermore, even when considering the dependent claims, the claims can still be performed in the human mind with a pen and paper, as one can use the learning data to guide their judgments/opinions, and use one’s personal experience to output the correction information. Furthermore, there are no further additional elements to consider, therefore the claims are not integrated into a practical application or amount to significantly more. Therefore, the claims are still directed to an abstract idea without an inventive concept.
Claim 7 merely further limits the abstract idea by defining the setting element as information of a character, a person correlation, a location, a period, a prop or a large prop of a story. This is more of the same abstract idea since a character is an individual, and a “person correlation” is the relationship between individuals, therefore, by outputting correction information regarding individuals or relationships, it is an act of “managing personal behavior or interactions between people.” Furthermore, there are no further additional elements to consider, therefore the claims are not integrated into a practical application or amount to significantly more. Therefore, the claims are still directed to an abstract idea without an inventive concept.
Claim 8 merely further limits the abstract idea by adding the step of extracting the information of the setting element from information of a scenario. Extraction of information is merely a data extraction step towards performing the abstract idea, which is also still certain methods of organizing human activity and can also be done by a human. Furthermore, there are no further additional elements to consider, therefore the claims are not integrated into a practical application or amount to significantly more. Therefore, the claims are still directed to an abstract idea without an inventive concept.
Claims 17 and 18 merely further limit the abstract idea by defining the “value” as a temporal length of a video or a “shooting cost or revenue.” This is more of the same abstract idea because it still results in the same output of instructions to manage personal behavior, and can be performed mentally. Furthermore, these dependent claims add “commercial or legal interactions” in the form of estimating a cost, revenue, or time related to a video, which is a business interaction. Furthermore, there are no further additional elements to consider, therefore the claims are not integrated into a practical application or amount to significantly more. Therefore, the claims are still directed to an abstract idea without an inventive concept.
Claims 19 and 21 merely further define the abstract idea by adding the additional steps of “display the generated pieces of correction information on a display unit as a change proposal,” (claim 11) and “display a range of a scenario affected by execution of the correction information...”(claim 13). These are more of the same abstract idea since these steps merely specify how the correction information is displayed. In view of the specification, particularly Fig. 7, and Fig. 9 these are additional elements that are merely examples of “apply it” or instructions to perform the abstract idea on generic computing components such as a “display unit.” Displaying a range of the scenario or displaying the information as a change proposal does not provide an improvement to technology, as it is merely a generic data output. Therefore, the additional elements, whether analyzed individually, or in an ordered combination, do not integrate the abstract idea into a practical application or provide significantly more. Therefore, the claims are directed to an abstract idea without an inventive concept.
Claim 20 further limits the abstract idea by requiring the display of correction information to be a “card type UI.” The display of data is still more of the same abstract idea. The fact that it is done on a card type UI is no more than a general link to a particular technological environment or field of use, in this case to the field of graphical user interfaces. Generally linking the abstract idea to “card type user interfaces” does not meaningfully limit its use on the abstract idea. Therefore, the additional elements, whether analyzed individually, or in an ordered combination, do not integrate the abstract idea into a practical application or provide significantly more. Therefore, the claims are directed to an abstract idea without an inventive concept.
Claim 14 further defines the abstract idea by adding the steps of “determine importance of a component corresponding to the setting element on a basis of the information of the scenario, the importance being used to generate a simulation video on a basis of information of a scenario; and among one or more of the component, determine a component that is visualized that can be operated by a user according to the importance.” The bolded elements are more of the same abstract idea since it merely provides data processing and data output steps regarding the importance of a particular element in the context of a scenario, and generates a simulation. Generating a simulation, on its own, is still part of the same abstract idea since it still mainly a display of data. The fact that this simulation is a simulation video is merely an example “apply it” or instructions to perform the abstract idea on the generic computing devices listed above(display unit, processor, computer). In this case, recited as broadly as it is recited, generating a simulation is merely using the control unit and display unit in their ordinary capacity to perform functions such as generating and visualizing a video. Therefore, the additional elements, whether analyzed individually, or in an ordered combination, do not integrate the abstract idea into a practical application or provide significantly more. Therefore, the claims are directed to an abstract idea without an inventive concept.
Claim Rejections – 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 1-8, and 15-21 is rejected under 35 U.S.C. 103 as being unpatentable over in view of Ray (US 20190213253 A1), in view of Price et al. (US 9106812 B1) hereinafter Price.
Regarding Claims 1, 15, and 16:
Ray discloses an automated script content generator to suggest script changes and indicate the resulting affects to the script to help facilitate the pre-production process. Ray teaches:
Claim 1 Preamble: An information processing apparatus comprising: circuitry configured to:
(Ray [0093] The computer system 200 may include one or more processing units 212a, 212b (collectively 212), a system memory 214 and a system bus 216 that couples various system components including the system memory 214 to the processing units 212.)
Claim 15 Preamble: An information processing method comprising:(Ray [0093] processing unit [0089] FIG. 1 is a block diagram of a media production environment 100, in which systems, devices and methods for automated script generation and media production 200 may be a part, or in which they may be implemented, according to one illustrated embodiment.)
Claim 16 Preamble: A non-transitory computer-readable medium having embodied thereon a program, which when executed by a computer causes the computer to execute an information processing method, the method comprising: (Ray [0096] Program modules can be stored in the system memory 214, such as an operating system 236; one or more application programs 238; other programs or modules 240; program data, generated data and artificial neural network training data 242; and artificial neural network program 244. Application programs 238 along with the program data, generated data and artificial neural network training data 242, and artificial neural network program 244, may include instructions that cause the processor(s) 212 to automatically generate and suggest script content for a script;)
Claim 1 body as a representative claim also applicable to claims 15 and 16:
- estimate a value caused by content on a basis of information of one or more of setting element set for generating the content; (Ray [0005] estimate a scene length for each of the scenes, and wherein generating a script breakdown includes generating a script breakdown that represents the estimated scene length of each of the scenes. [0033] the categories of script elements including at least: i) scenes, ii) characters that appear in one or more scenes, iii) mise en scene elements, and iv) dialog for each of the characters; generating a script breakdown that represents at least: i) the scenes, and ii) any of one or more main characters that appear in each of the scenes; and generating an estimated budget for a production of the script based at least in part on the generated script breakdown and the corpus of budgets. [0034] Generating an estimated budget for a production of the script may include generating an estimated budget in the form of a tree structure with a plurality of line items as end nodes of the tree structure. Generating an estimated budget for a production of the script may include automatically generating respective estimates of costs for each of a plurality of line items that are below the line from the sample script.) The broadest reasonable interpretation (BRI) of “setting element” is any element of a scene such as dialogue, characters, props, storyline. The BRI of “estimating a value” also covers the scope of estimating a temporal length or potential cost of content. Therefore, Ray satisfies the limitation by estimating a scene length, or estimating the potential budget based on the elements in the scene.
- generate correction information regarding correction of the setting element (Ray [0101] to suggest improvements in the exposition. [0112] The system for automated script generation and media production 200 may also suggest new or modified content to include based on the changes made. [0091] ...For example, the automated producer 110 of the system for automated script generation and media production 200 may break down the script to automatically generate storyboards, calendars, schedules and budgets and provides this as input to the pre-production operation 112 within the media production environment 100. The system for automated script generation and media production 200 may also provide information to affect and facilitate the greenlighting operation 106 and other operations in the media production environment 100 in an iterative script review and revision process as shown in FIG. 24. [0161] The system for automated script generation and media production 200 may also base the optimization on various other parameters, including, but not limited to, dates that represent when the pieces of equipment or props are available, predicted weather conditions for shoot location(s) and cost constraints. [0090] The forecasting operation 108 determines factors such as whether distribution of the movie would generate enough revenue to recover the costs of production and turn a profit and how to distribute the movie to generate enough revenue to recover the costs of production and turn a profit. [0170] The system for automated script generation and media production 200 improves the technology of automated media production by enabling production studios to more efficiently look at the effects of removing certain high-budget spectacles to see how that affects predicted outcomes) The BRI of correction information is any sort of recommendation or suggestion that would help the director improve towards a goal, such as reducing budget, in view of the present specification, Figs 4-5. Therefore, Ray’s suggestions/optimizations which may be based on a comparison between an estimated and actual budget, or other factors, satisfies the limitations.
on a basis of comparing the estimated value with a target value; (Ray [0168] The system for automated script generation and media production 200 may also compare the generated estimated budget for a production of the script to an actual budget for the production of the script and present a difference in costs between the generated estimated budget and the actual budget for the production of the script accordingly.) Ray’s actual budget is mapped to the “target value” since an actual budget is an example of a value that the director’s/producer’s intend to stick to.
store the content and correction information in a memory;(Ray 0146] The user selecting the user selectable annotation 1508 causes the system for automated script generation and media production 200 to store a logical relationship between the visually identified term and a value that represents the selected annotation 1508. Thus, during training, when the artificial deep neural network 1400 selects the sentiment “Frustration” to be associated with the term “roll his eyes” within the context of the script shown in FIG. 15B, it will be indicated and stored for future reference and training purposes during the training process as a correct categorization. [0009] Storing at least one data structure may include storing at least one data structure in which scenes and characters are represented as respective nodes, and respective relationships between respective pairs of the scenes and, or characters, are represented by respective edges.)
control a displaying of, on a display, the correction information for selection by an operation by a user by referring to the correction information stored in the memory;(Ray [0151] As shown in FIG. 18, this causes the system for automated script generation and media production 200 to open a text editor 1800 that shows the currently written scene represented by the selected node of the graph, and to make suggestions of dialog or fill in the details of a scene, such as the details of an action sequence. In the embodiment shown in FIG. 18, the system for automated script generation and media production 200 generates dialogues 1802 between the characters based on the nature of the interaction. The user may then use a cursor 1804 to select the dialogs 1802 to be inserted into the script in the script editor 1800. The dialogs 1802 may also be selected by the user touching, pressing, holding or performing other touch gestures on the user interface screen of the text editor 1800 with respect to the generated dialogs 1802.)
However, Ray fails to teach or suggest:
control a displaying of, by the display and in response to the user performing the operation to select the correction information, the content corrected by the correction information by referring to the correction information stored in the memory and a user interface (UI) for selection by an operation by the user to revert the corrected content to the content before the correction is performed; and
control a displaying of, by the display and in response to the user performing the operation to revert the corrected content to the content before the correction is performed, the content before the correction is performed by referring to the content stored in the memory.
Alternatively, Price discloses an automated creation of storyboards from screenplays to generate a rough draft from a storyboard to extract meaning from a screenplay. Price teaches:
control a displaying of, by the display and in response to the user performing the operation to select the correction information, the content corrected by the correction information by referring to the correction information stored in the memory and a user interface (UI) for selection by an operation by the user to revert the corrected content to the content before the correction is performed; and(Price [The preproduction module 318 may receive an indication of a genre for the screenplay 100 that is used by the automated storyboard producer 114 to select elements of the storyboard 112 (e.g., a soundtrack). If preproduction instructions are received after an initial analysis of the screenplay 100, the user may be presented with several suggested choices for various elements of the screenplay 100 (e.g., five choices for a character image 116, two choices for a background 118, etc.) and choose between the suggestions.[Col. 12 Lines 21-29] Changes made by the user 202 during editing may modify content selected by the automated storyboard producer 114 and/or content selected by the same or a different user 202. Various edits to the storyboard 112 may be saved and tracked in association with the user 202 who made the edits. Thus, if one of the users 202 does not like edits either made by himself or by the other user 202 those edits may be removed and the storyboard 112 may be reverted to an earlier version.)
control a displaying of, by the display and in response to the user performing the operation to revert the corrected content to the content before the correction is performed, the content before the correction is performed by referring to the content stored in the memory.(Price [Col. 12 Lines 27-35] Thus, if one of the users 202 does not like edits either made by himself or by the other user 202 those edits may be removed and the storyboard 112 may be reverted to an earlier version. Similarly, if different users or groups of users have divergent creative visions, there may be multiple versions of the storyboard 112 existing simultaneously (e.g., both as part of the project 214). At some point the different versions of the storyboard 112 may be presented to a third party and the third party may select the version to make into a movie, television show, etc. [Col. 4 Lines 30-41] The automated storyboard producer 114 may be stored in the computer-readable media 212 at a single location, redundantly in multiple locations, or in a distributed storage format in which parts of the automated storage board producer 114 are stored in separate physical memory units. The automated storyboard producer 114 may manage one or more projects 214 that each contains content which may be used to create storyboards for the respective projects. The project 214 may be stored in the computer-readable media 212 or otherwise accessible by the shared computing resources 208. Contents of the project 214 may be freely available to the users 202 for viewing and/or editing.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present disclosure to further modify Ray by adding the teachings of Price, particularly, the ability, after performing the changes made in a correction, to revert those changes back to previous versions stored in memory, effectively undoing the change. One of ordinary skill in the art would have been able to implement this feature within Ray’s system and arrived at the predictable outcome of the claimed invention. One of ordinary skill in the art would have been motivated to combine by Price’s benefit of allowing multiple versions to exist so that a part can select the best version. (Price [Col. 12 Lines 29-35] Similarly, if different users or groups of users have divergent creative visions, there may be multiple versions of the storyboard 112 existing simultaneously (e.g., both as part of the project 214). At some point the different versions of the storyboard 112 may be presented to a third party and the third party may select the version to make into a movie, television show, etc.
Regarding Claim 2:
The combination of Ray and Price teach the information processing apparatus according to claim 1,
Furthermore, Ray teaches:
- wherein the correction information is information regarding an increase or decrease in the number of the setting elements. (Ray [0091] For example, the automated script content generator 102 of the system for automated script generation and media production 200 may generate and suggest script content for the script 104 and indicate effects changes to the script 104 would have on the scenes, characters, interactions and other entities of the script. [0117] addition of an instance of new content to the sample script would have on an aspect of a character relationship represented in the sample script. [0118] Examples of such modifications include, but are not limited to: removing a character, adding a character, changing an event or nature of interaction between events or characters.)
Regarding Claim 3:
The combination of Ray and Price teach the information processing apparatus according to claim 2,
Furthermore, Ray teaches:
- wherein the circuitry is further configured to determine a setting element to be added or deleted according to a difference between the estimated value and the target value. (Ray [0042] The method of operation of a computational system that implements at least one artificial neural network to perform pre-production operations including script breakdown may further include presenting a difference in costs between the generated estimated budget for a production of the script to an actual budget for the production of the script. See also [0091] an iterative script review and revision process as shown in FIG. 24. [0112] The system for automated script generation and media production 200 will then indicate on the graph 302 what possible effects such changes may have on the various entities, such as the scenes, relationships and other aspects of the narrative. The system for automated script generation and media production 200 may also suggest new or modified content to include based on the changes made. [0170] enabling production studios to more efficiently look at the effects of removing certain high-budget spectacles to see how that affects predicted outcomes... more efficiently see the effect of adding a female lead to the story, and how that impacts the chances of signing up distributors. [0165] may also base the optimization on various other parameters, including, but not limited to, dates that represent when the pieces of equipment or props are available, predicted weather conditions for shoot location(s) and cost constraints. ) Part of the process in Ray includes presenting a difference in cost, therefore, performing an optimization based on cost constraints, falls within the scope of determining a setting element to be added or deleted according to the difference between the estimated and target value (cost constraints).
Regarding Claim 4:
The combination of Ray and Price teach the information processing apparatus according to claim 3,
Furthermore, Ray teaches:
- wherein the circuitry is further configured to determine the setting element to be added or deleted by using learning data of content generated in a past. (Ray See [0112] and [0170] for content added and deleted. [0101] a process that ingests text, extracts key elements, visualizes the story and uses natural language processing methods trained on data to suggest improvements in the exposition...also infers the effects of changes in the script or text on the overall quality of the story and may also infer the effects on characters or events in a later temporal stage... generates appropriate dialogues or interactions using deep learning. The system for automated script generation and media production 200 learns by using a training corpus or database of scripts or stories (e.g., film, TV, interactive games). [0103] The natural language processor of the system for automated script generation and media production 200 may use supervised learning in that the data set used for training may be a set of labeled or annotated scripts used as training examples. [0150] This labeled training data is then stored as new instances of labeled training data in labeled training data storage 1702, to be used in the training process, thus providing reinforcement learning and feedback in the system for automated script generation and media production 200. )
Regarding Claim 5:
The combination of Ray and Price teach the information processing apparatus according to claim 4,
Furthermore, Ray teaches:
- wherein the circuitry is further configured to determine a setting element to be deleted from the one or more of the setting element. (Ray [0118] Examples of such modifications include, but are not limited to: removing a character, adding a character, changing an event or nature of interaction between events or characters. As shown in FIG. 6, the system for automated script generation and media production 200 may identify such a change to the scene represented by node 404 by causing node 404 to be displayed as an empty node. [0170] enabling production studios to more efficiently look at the effects of removing certain high-budget spectacles to see how that affects predicted outcomes.)
Regarding Claim 6:
The combination of Ray and Price teach the information processing apparatus according to claim 4,
Furthermore, Ray teaches:
- wherein the circuitry is further configured to determine a setting element to be added from one or more of setting element of the content generated in the past. (Ray [0128] The auto-encoder 900 is used for learning generative models of data to generate the suggested next steps in the narrative of the sample script and the respective likelihood of each suggested next step, generate additional instances of new content to include in the narrative of the sample script, and determine the effect that additional instances of new content will have on the entities and relationships represented in the narrative of the sample script.)
Regarding Claim 7:
The combination of Ray and Price teach the information processing apparatus according to claim 1,
Furthermore, Ray teaches:
- wherein the information of the setting element includes information of a character, a person correlation, (Ray [0151] FIG. 18 is example user interface screen of a text editor 1800 in the system for automated script generation and media production 200 that shows the currently written scene and generates dialogues between the characters based on the nature of their interaction, according to one illustrated embodiment. [0117] may determine an effect that an addition of an instance of new content to the sample script would have on an aspect of a character relationship represented in the sample script. Such an effect may be regarding various different aspects of the narrative. For example, this may be regarding one or more of: a relationship between a pair of characters, a sentiment of a character... a character... and a characterization of an interaction between two or more characters.)
-a location, (Ray [0155] “Small City/Large Town—Street” scene. [0165] For example, on October 20th, scenes “1 Bakery” 2206, “44 Bakery” 2208 and “60 Bakery” 2210 are scheduled to be shot at the bakery location that day. Individual)
-a period, (Ray [0203] At 3208, the system for automated script generation and media production 200 performs an optimization on at least a combination of the ingested schedule or calendar of the cast members; and the dates that represent when the respective shoot locations are available.)
-a prop, or a large prop of a story. (Ray [0155] For example, props in the scene 1904 are identified for by the system for automated script generation and media production 200 coloring the text in the script red that identifies the props. Examples of these identified props are “pastries” 1908, “display case” 1912, “chocolate croissant” 1910, “register” 1916 and “empty mugs” 1914.)
Regarding Claim 8:
The combination of Ray and Price teach the information processing apparatus according to claim 7,
Furthermore, Ray teaches:
- wherein the circuitry is further configured to perform a process of extracting the information of the setting element from information of a scenario. (Ray [0101] To generate the graph 302, the system for automated script generation and media production 200 performs a process that ingests text, extracts key elements, visualizes the story and uses natural language processing methods trained on data to suggest improvements in the exposition. [0115] Based on the natural language processing of the script and extraction of key entities by the system for automated script generation and media production 200, the system for automated script generation and media production 200 may automatically detect various aspects of the script, including, but not limited to, plot holes and lack of character exposition.)
Regarding Claim 17:
The combination of Ray and Price teach the information processing apparatus according to claim 8,
Furthermore, Ray teaches:
-wherein the value caused by the content is a temporal length of a video. (Ray [0005] processing the at least one of the sample script or the portion of the sample script via the at least one artificial neural network to estimate a scene length for each of the scenes, generating a script breakdown that represents the estimated scene length of each of the scenes. [0089] This may include production of the script into various types of media, including, but not limited to, production in to a film, short film, television show or series, web series, video game, or interactive game, virtual reality media, or augmented reality media. Production of a film will be used in the present example.) The estimation of scene length in Ray, in the context of film, indicates the duration(temporal length) of a video.
Regarding Claim 18:
The combination of Ray and Price teach the information processing apparatus according to claim 8,
Furthermore, Ray teaches:
- wherein the value caused by the content is a shooting cost or revenue. (Ray [0089] The financing operation 108 often provides input to the greenlighting operation 108 and affects whether a script is approved for production because there is often a cost analysis performed to determine whether there exists enough money for production of the script. [0090] The forecasting operation 108 determines factors such as whether distribution of the movie would generate enough revenue to recover the costs of production and turn a profit and how to distribute the movie to generate enough revenue to recover the costs of production and turn a profit.)
Regarding Claim 19:
The combination of Ray and Price teach the information processing apparatus according to claim 1,
Furthermore, Ray teaches:
- wherein the circuitry is further configured to generate one or more pieces of the correction information and (Ray [0091] For example, the automated script content generator 102 of the system for automated script generation and media production 200 may generate and suggest script content for the script. )
- display the generated one or more pieces of the correction information on a display unit as a change proposal. (Ray [0151] As shown in FIG. 18, this causes the system for automated script generation and media production 200 to open a text editor 1800 that shows the currently written scene represented by the selected node of the graph, and to make suggestions of dialog or fill in the details of a scene, such as the details of an action sequence. In the embodiment shown in FIG. 18, the system for automated script generation and media production 200 generates dialogues 1802 between the characters based on the nature of the interaction.)
Regarding Claim 20:
The combination of Ray and Price teach the information processing apparatus according to claim 11,
Furthermore, Ray teaches:
- wherein the circuitry is further configured to control displaying of, by the display, the one or more pieces of the correction information as a card type UI. (Ray [0151] FIG. 18 is example user interface screen of a text editor 1800 in the system for automated script generation and media production 200 that shows the currently written scene and generates dialogues between the characters based on the nature of their interaction, according to one illustrated embodiment. As described above, the artificial neural network of system for automated script generation and media production 200 may be trained on a corpus of one or more annotated scripts or portions of annotated scripts. The system for automated script generation and media production 200 then receives a sample script and processes the sample script, generating a graph of the narrative, for example, as shown in any of FIGS. 3-8. The system for automated script generation and media production 200 may then generate, via the artificial neural network, a number of instances of new content for the sample script... In the embodiment shown in FIG. 18, the system for automated script generation and media production 200 generates dialogues 1802 between the characters based on the nature of the interaction. The user may then use a cursor 1804 to select the dialogs 1802 to be inserted into the script in the script editor 1800. The dialogs 1802 may also be selected by the user touching, pressing, holding or performing other touch gestures on the user interface screen of the text editor 1800 with respect to the generated dialogs 1802.) The BRI of card type UI, is a user interface similar to Fig. 10 of the present application, wherein the recommendations are displayed on a rectangular container. As seen in Fig. 18, Ray’s dialog change recommendations are shown on a card type UI 1802.
Regarding Claim 21:
The combination of Ray and Price teach the information processing apparatus according to claim 1,
Furthermore, Ray teaches:
- wherein the setting element is extracted from information of a scenario, and (Ray [0152] FIG. 19 is an example user interface screen 1900 of the system for automated script generation and media production 200 showing a sample script and various script elements identified and extracted during a process of breaking down the script for automated media production, according to one illustrated embodiment.)
- the circuitry is further configured to control displaying of, by the display, a range of a scenario affected by execution of the correction information in a case where the correction information is adopted by a user. (Ray [0151] As shown in FIG. 18, this causes the system for automated script generation and media production 200 to open a text editor 1800 that shows the currently written scene represented by the selected node of the graph, and to make suggestions of dialog or fill in the details of a scene, such as the details of an action sequence.) The BRI of displaying a range of a scenario affected by execution, in view of the specification, is a rectangular box indicating the portion of the script that will be affected by the implementation of the corrections. For example, in the present application Fig. 9, this range is indicated by 422. Therefore, the rectangle surrounding the line “But surely that is foolishness!” in Fig. 18 is mapped to this limitation.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over in view of Ray (US 20190213253 A1), in view of Price et al. (US 9106812 B1) hereinafter Price, further in view of Haohong Wang (US 20220101880 A1) hereinafter Wang.
Regarding Claim 14:
The combination of Ray and Price teach The information processing apparatus according to claim 1, wherein the circuitry is further configured to:
Furthermore, Ray teaches:
-- determine importance of each component of a plurality of components corresponding to the setting element on a basis of the information of a scenario,(Ray [0107] The edges each respectively represent a respective relationship between a respective pair of the key entities which are each represented by respective nodes. Each edge may include a visual representation of a level of significance of the scene, the event, the action sequence, the dialog or the character interaction represented by the respective nodes. [0114] FIG. 5 shows an example expanded portion 500 of the graph 400 of FIG. 4 that may be presented on a user interface screen of a system for automated script generation and media production 200 with dotted lines that represent detected aspects of key entities and relationships between the entities represented by the nodes, according to one illustrated embodiment. The width or other characteristic of the edges of the graph 500 represent the significance of the events. In particular, the edge 506 between nodes 504 and 508 with greater width represents a major change between the scenes represented by nodes 504 and 508, for example, a pivotal moment of the story in the script which graph 500 represents. Similarly, the edge 512 between nodes 510 and 514 with greater width represents a major change between the scenes represented by nodes 510 and 514.) Ray’s level of significance, determining by the extracted key entities and key characters, is an example of determining the importance of an element based on the information of the scenario.
- generate a simulation (image) on a basis of information of a scenario;(Ray [0013] Classifying the respective shot as one of a plurality of shot types may include processing dialog from the at least one of the sample script or the portion of the sample script that corresponds to the respective shot via a text-to-image classifier... Finding a representative image based on the respective shot type may include searching an archival database of archival images. Generating a storyboard using the identified representative images may include generating a storyboard where at least one shot is represented by two images. Generating a storyboard using the identified representative images may include generating a storyboard where at least one shot is represented by two user selectable image options.) Ray teaches generating a simulation image, but not a simulation video.
However, neither Ray nor Price teach or suggest:
- the importance being used to generate a simulation video on a basis of information of a scenario;
- and among one or more of the component, determine a component that is visualized that can be operated by a user according to the importance.
Alternatively, Wang discloses a method obtaining a screenplay of a movie, rendering 3D data of scenes, and generating a 2D video of the movie. Wang teaches:
- the importance being used to generate a simulation video on a basis of information of a scenario; (Wang [0024] the instant animation video generated. [0036] As shown in FIG. 2 and FIG. 3, the Write-A-Movie system 200 takes the script of a Scene, i.e., Scene script, to go through an NLP engine 202 which automatically converts the script into a list of actions, i.e., an action list. An action correction component 204 is optionally involved for a user to revise action attributes, and/or fix the errors that could be introduced due to the script understanding capability of the NLP engine 202. When receiving a user-verified action list, a 3D rendering engine 206 can generate 3D data that reflects performances of characters in 3D scene(s)..The combination of the 2D frames output by the optimization engine is a 2D video, which is a movie generated by the Write-A-Movie system. [0059] In Write-A-Movie, every writer/user implicitly becomes a director, who can decide what is important (e.g., who is Protagonist whose action has substantial impact, which object reflects non-negligible clues, and so on), the scene vibe (e.g., audience perceived intensity, conflict and emotional intensity, and so on), the attention model (e.g., character fear intensity, bad guy intensity, handheld intensity, and so on), and many other factors that may directly impact to the perception of the audiences.) Wang teaches a generated animation video based on the script, in which the importance is used to determine aspects of the simulation such as the scene vibe, attention model, etc.
- and among one or more of the component, determine a component that is visualized that can be operated by a user according to the importance. (Wang [0061] The script breakdown 802 may be implemented by the NLP engine 202 and/or the action correction component 204 to produce an action list... A content preview 8122 may then be presented to the user on a user interface, and the user may make adjustments on the user interface based on importance and correlation 8124 of the actions (e.g., a user interface depicting an importance curve of the actions). Users can repetitively make adjustment to the output of the automatic camera sequence after previewing 820 the camera sequence of the optimization algorithm. Users can change the arrangement of the camera sequence in different time periods indirectly through the intuitive hint translators, or they can add user defined free cameras in the 3D animation environment...A user of the disclosed system can decide whether or not to provide these director hint inputs to impact the movie making. The director hints can affect the automatic-cinematography process at different stages, such as when determining which camera(s) to use to shoot a scene, what camera configuration to be employed to shoot a scene, whether to include certain portions of a shot scene into the final movie, etc.) The user can make adjustments on the user interface based on importance, and the adjustment to the camera sequence is an example of a component that is visualized that can be operated by a user according to the importance. In the present application [0141], the disclosure provides an example within the scope of the limitation above, such as controlling the camerawork based on importance or selecting certain portions of the scene to be deleted or kept. Wang also teaches this in the paragraph above.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present disclosure to further modify Ray by adding the features of generating a simulation video based on the importance of the scene and operating components based on the importance as taught by Wang. Since Ray already implements a text-to-image storyboard generation feature, it would have been obvious to substitute the image for a video generation, resulting in the predictable outcome of generating a simulation video based on the importance. One would have been motivated by the benefit of simulations videos over images in better portraying the script and simplifying the story writing process. (Wang [0067])
Response to Arguments
Applicant's arguments filed 03/09/2026 have been fully considered but they are not persuasive.
The applicant’s remarks regarding the objections to claim 15 have been considered and the objection has been withdrawn in view of the amendments.
The applicant’s remarks regarding the invocation of 112(f) of claims 1, 3-6, 8, and 14 has been considered and the claims no longer are interpreted under 112(f).
The applicant’s remarks over the rejection of claim 16 as being directed to non-statutory subject matter under 35 U.S.C. has been considered, and the claims remain rejected under 35 U.S.C. 101 but for being directed to an abstract without significantly more.
The applicant’s arguments over 35 U.S.C. 101 for being directed to an abstract idea without significantly more have been fully considered but are not persuasive for the following reasons: The applicant’s references to the Desjardins decision, in pages 12 – 14 are acknowledged by the examiner. The applicant’s argument in page 14 merely recites the claim language verbatim, and then alleges that similar to Example 37, the claims provide a specific improvement over prior systems, resulting in an improved user interface for electronic devices. However, this argument is not persuasive because the present claims merely use user interfaces in their ordinary capacity to perform the abstract idea of allowing a user to modify corrections (of user interactions) on a computer. The features of reverting back to previous versions (pre-correction) is not an improvement to user interface technology. Furthermore, the applicant’s argument that with the additional elements “it may not be possible that a user can adopt the correction or rollback the correction in response to a user operation to refer to the correction information or content stored in memory,” however, this argument is not persuasive because the applicant has not demonstrated, via the specification or the remarks, that it would be apparent to one of ordinary skill in the art that an improvement to technology is reflected within the scope of the claims. The applicant has not set forth the state of the art and has not described the improvement in a manner that would convince one of ordinary skill in the art that there is an improvement over technology. Therefore, the claims remain rejected under 35 U.S.C. 101.
Regarding the applicant’s arguments over rejections under prior art, the applicant’s arguments have been fully considered, however, the amendments necessitate an updated search and consideration, and the claims are now rejected under 35 U.S.C. 103 for being obvious over Ray in view of Price. This means the applicant’s arguments are now moot in view of the new grounds of rejections. Therefore, while Ray does not teach the underlined amendments in page 17 of the remarks, Price remedies the deficiency by suggesting the exact feature not taught by Ray. Therefore, claims 1-8, 15, 16, 17-21 are rejected under 35 U.S.C. 103 in view of Ray and Price. Claim 14 is rejected under 35 U.S.C. 103 in view of the combination of Ray, Price, and Wang.
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 NICO LAUREN PADUA whose telephone number is (703)756-1978. The examiner can normally be reached Mon to Fri: 8:30 to 5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jessica Lemieux can be reached at (571) 270-3445. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NICO L PADUA/ Junior Patent Examiner, Art Unit 3626 /JESSICA LEMIEUX/ Supervisory Patent Examiner, Art Unit 3626
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