DETAILED ACTION
Claims 1-22 are presented for examination
This office action is in response to submission of application on 28-JANURARY-2022.
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 .
Response to Amendment
The amendment filed on 29-DECEMBER-2025 in response to the final office action mailed 31-OCTOBER-2025 has been entered. Claims 1-20 remain pending in the application.
With regards to the 101 rejection, the rejection to claim 1 has been overcome by the applicant’s amendments.
With regards to the 103 rejections, the applicant’s amendments to the claims have not overcome the rejections to claims 1-22 as the newly added prior art D'AGOSTINO, in combination with already present prior art, sufficiently teaches the newly added limitations of the amended claims.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 3-4, 6-10, 11, 13-14, 16-20, 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over SHUKLA (U.S. Pub. No. US 20190202063 A1) in view of DOUEK (U.S. Pub. No. US 20200302263 A1) in view of BUHMANN (U.S. Pub. No. US 11416732 B2) in view of D'AGOSTINO (U.S. Pub. No. US 20180096322 A1)
Regarding claim 1, SHUKLA teaches the invention substantially as claimed, including:
A system comprising: a processing hardware and a memory storing a software code; the processing hardware configured to execute the software code to: receive input data describing an action ([59] During a conversation, an agent device may include one or more input mechanisms (e.g., cameras, microphones, touch screens, buttons, etc.) that allow the agent device to capture inputs related to the user or the local environment associated with the conversation. Such inputs may assist the automated companion to develop an understanding of the atmosphere surrounding the conversation (e.g., movements of the user, sound of the environment) and the mindset of the human conversant (e.g., user picks up a ball which may indicates that the user is bored) in order to enable the automated companion to react accordingly and conduct the conversation in a manner that will keep the user interested and engaging.) obtain the plurality of interaction profiles; ([0076]… For example, certain configurations related to a desired character for the agent device (a duck) may be accessed from, e.g., an open source database, that provides parameters (e.g., parameters to visually render the duck and/or parameters needed to render the speech from the duck).)simulate execution of the action with respect to each of the plurality of participants; ([0095] The third level is the reasoning level, which is used to perform high level reasoning based on analyzed sensor data. Text from speech recognition, or estimated emotion (or other characterization) may be sent to an inference program which may operate to infer various high level concepts such as intent, mindset, preferences based on information received from the second level. The inferred high level concepts may then be used by a utility based planning module that devises a plan to respond in a dialogue given the teaching plans defined at the pedagogy level and the current state of the user. )
wherein at least one of the plurality of responses is: (i) a physical act performed by one or more of the plurality of participants, or (ii) rendered to one or more of a display, an audio output device, or a robot. (([0099] In addition to speech style, the robot head of an automated dialogue companion may also be dynamically configured to have expressions when conveying a response to a user. For instance, when a user answers several questions correctly, the automated dialogue companion may be controlled to not only say “Excellent” but also render a smiling expression. Such an expression may be rendered on a display screen that may represent the face portion of the robot head. In another example, certain emotion of the robot may be expressed via physical movement of certain parts of the robot.))
While SHUKLA does teach receiving input from a user, obtaining an interaction profile, and using the interaction profile and user input to generate a response to the user, it does not explicitly teach:
and identifying a plurality of interaction profiles corresponding respectively to a plurality of participants in the action;
However, in analogous art that similarly uses a dialog system to interact with a user, DOUEK teaches:
and identifying a plurality of interaction profiles corresponding to a plurality of different personality types and demographic characteristics representative of a plurality of participants in the action, (([0024] A bot service to enable a consistent uninterrupted experience with recall from one tech apparatus (e.g., app, device, bot, dash, etc.) to the next, delivered through a user-friendly bot is described herein. In an aspect, the bot service is built for novice users and is consumer-facing. In a further aspect, the bot service plus an optional live agent with session-to-session recall enables the bot service to build a relationship with the user, analyze interactions plus other available data and create a dynamic ever-evolving user profile, to which the bot service adapts its user experience (UX) as well as command center UX around user's complete DNA/persona, user's stated preferences, and preferences inferred from interactions and available data. [0025] FIGS. 1A and 1B are block diagrams of aspects of a system 100, according to an exemplary embodiment. Referring further to FIG. 1A, the system 100 includes one or more user computing devices 102, a network 104, and one or more server computing devices 106. A bot service 108 and one or more data source services 110 execute on the one or more server computing devices 106. The system 100 may also include a live agent 112. A user 114 interacts with the system 100 via the one or more user computing devices 102. Although a single user is illustrated in FIGS. 1A and 1B for simplicity, those skilled in the art will understand that system 100 may be used concurrently by a plurality of users 114 each interacting with their respective one or more user computing devices 102. Referring further to FIG. 1B, the user 114 utilizes the user computing devices 102 to interact with the bot service 108 via one or more interaction channels 116 that each have their own human-machine user experience (UX) 118. The bot service 108 generates a personalized bot 120 that is personalized/customized for the user 114.)
It would have been obvious to a person skilled in the art before the effective filing date of the
invention to have combined with DOUEK‘s teaching of bots personalized to user and, with SHUKLA‘s teaching of receiving input, selecting a profile based on the input, and generating a response with the input and profile selection, to realize, with a reasonable expectation of success, a system that takes in user input, selects a profile, and generates a response to the user, as in SHUKLA, where the profile is corresponds to a user, as in DOUEK. A person of ordinary skill would have been motivated to make this combination to aid in the building of a connection with the profile (DOUEK [0003]).
While SHULAK, as modified by DOUEK, does teach identifying interaction profiles based on personalities, it does not explicitly teach:
wherein the action is one of a same speech directed to each of the plurality of participants, or a same activity performed by each of the plurality of participants;
However, in analogous art that similarly teaches multiple participants interaction with a system, BUHMANN teaches:
wherein the action is one of a same speech directed to each of the plurality of participants, or a same activity performed by each of the plurality of participants; ( (Col 4, lines 40-52) By way of overview, and referring back to FIG. 1, it is noted that, in some exemplary implementations, guests 126a and 126b may interact with respective characters 146a and 146b that may inhabit a story world (W) of a story having a timeline and a narrative arc or plot. Story world W is a blend of a virtual world and the real world, and can be changed by guests 126a and 126b as well as characters 146a and 146b. Software code 110 providing virtual agent 150/350, when executed by hardware processor 104, may control virtual agent 150/350 to simulate human-like affect-driven behavior, such as a human-like social interaction by one or both of characters 146a and 146b with respective guests 126a and 126b.
(Col 4, lines 53-64) It is further noted that, in some implementations, characters 146a and 146b may be different characters, while in other implementations, characters 146a and 146b may be different versions or instantiations of the same character. It is also noted that, in some implementations, even in lieu of an interaction between a character and one or more guests or guest object(s), the affective state of the character, including for example a personality profile, a mood, a physical state, an emotional state, and a motivational state of the character, can continue to evolve with advancement of the story including the character.)
It would have been obvious to a person skilled in the art before the effective filing date of the
invention to have combined with BUHMANN‘s teaching of participants interacting with the same activity and, with SHUKLA‘s, as modified by DOUEK, teaching of receiving input, selecting a profile based on the input, and generating a response with the input and profile selection, to realize, with a reasonable expectation of success, a system where participants interact with a same speech or activity, as in BUHMANN, where the profiles correspond to users, as in SHUKLA, as modified by DOUEK. A person of ordinary skill would have been motivated to make this combination to aid in the human like qualities of the system (BUHMANN BACKGROUND ).
While SHULAK, as modified by DOUEK and BUHMANN, does teach identifying interaction profiles based on personalities, it does not explicitly teach:
and generate in parallel, using the plurality of interaction profiles concurrently, a respective response to the action for each of the plurality of participants to provide a plurality of responses
However, in analogous art that similarly teaches multiple participants interaction with a system, D'AGOSTINO teaches:
and generate in parallel, using the plurality of interaction profiles concurrently, a respective response to the action for each of the plurality of participants to provide a plurality of responses ([[0064] The context aggregator module 400 receives or determines context data for interaction sessions that have been completed or that are taking place in system 140 for one or more users 110. The context data for an interaction session can include numerous information related to the interaction session, such as the purpose, task and/or subject of an interaction session, the identity of the user 110 and/or client device 104 involved in the interaction session, the type of interaction channel used, the start and finish times/dates of the interaction session, the location of user 110 and/or client device 104, references to other related interaction sessions, other metadata, etc.
[0065] In an example embodiment, the context data may be determined by the applicable servers of system 140, agent device 180 and/or agent 182, at the time of performing transactions within the interaction session, and recorded as part of the transaction data 204 stored in data storage 152. In this example embodiment, context aggregator module 400 can request or access such transaction data 204 from data storage 152. A local copy of the context data retrieved from data storage 152 can be stored in context data storage 420 for increased performance of the context server 170.
[0067] In this way, the context aggregator module 400 can track and process in parallel multiple interaction sessions concurrently taking place (e.g., all interaction sessions concurrently taking place between a user 110 and system 140). Context aggregator module 400 can generate in parallel context data associated with all such interaction sessions, and make the context data of each interaction session available for use in the other interaction sessions concurrently taking place, as well as for use in future interaction sessions. The context data may be accessed in parallel by multiple interaction sessions and/or when processing multiple interaction requests.)
It would have been obvious to a person skilled in the art before the effective filing date of the
invention to have combined with D'AGOSTINO‘s teaching of parallel response generation using interaction data and, with SHUKLA‘s, as modified by DOUEK and BUHMANN, teaching of receiving input, selecting a profile based on the input, and generating a response with the input and profile selection, to realize, with a reasonable expectation of success, a system generates a response in parallel using concurrent interaction data, as in D'AGOSTINO, where the profiles correspond to users, as in SHUKLA, as modified by DOUEK and BUHMANN. A person of ordinary skill would have been motivated to make this combination to improve user experience (D'AGOSTINO [0003] ).
Regarding claim 3, SHUKLA further teaches:
The system of claim 1, wherein the action comprises the same speech directed to each of the plurality of participants. ([0098] For instance, a robot head may be configured with a profile selected for a woman user with, e.g., parameters that correspond to a woman's speech with a high pitch voice, a British accent, and average speech speed. A different profile may be configured for a man with parameters that can be used to generate a man's voice with low pitch and American accent.)
Regarding claim 4, SHUKLA further teaches:
The system of claim 1, wherein the at least one of the plurality of responses is the physical act, and the physical act comprises at least one of a speech, a gesture, another action, or a behavior performed by the one or more of the plurality of participants. ([0089] The modal-data understanding generated at layer 2 may be used by DM 510 to determine how to respond… To deliver a response to the user, the DM 510 may also formulate a way that the response is to be delivered. The form in which the response is to be delivered may be determined based on information from multiple sources, e.g., the user's emotion (e.g., if the user is a child who is not happy, the response may be rendered in a gentle voice), the user's utility (e.g., the user may prefer speech in certain accent similar to his parents'), or the surrounding environment that the user is in (e.g., noisy place so that the response needs to be delivered in a high volume). DM 510 may output the response determined together with such delivery parameters.
[0090] In some embodiments, the delivery of such determined response is achieved by generating the deliverable form(s) of each response in accordance with various parameters associated with the response. In a general case, a response is delivered in the form of speech in some natural language. A response may also be delivered in speech coupled with a particular nonverbal expression as a part of the delivered response, such as a nod, a shake of the head, a blink of the eyes, or a shrug. There may be other forms of deliverable form of a response that is acoustic but not verbal, e.g., a whistle.)
R00egarding claim 7, SHUKLA further teaches:
The system of claim 1, wherein the plurality of participants comprises one or more human beings. ([0075] The estimated mindsets of parties, whether related to humans or the automated companion (machine), may be relied on by the dialogue management at layer 3, to determine, e.g., how to carry on a conversation with a human conversant.)
Regarding claim 8, DOUEK further teaches:
The system of claim 1, wherein the plurality of participants comprises one or more fictional characters. ([0063] In an embodiment, the distributed network includes one bot(i.e. a generated personality/fictional character) per verified human/entity. In the distributed network, the bots communicate(i.e. receive input and send responses to one another, which is the criteria for a participant) and protect the user/entities' identities.)
Regarding claim 9, DOUEK further teaches:
The system of claim 1, wherein the processing hardware is further configured to execute the software code to: obtain at least some of the plurality of interaction profiles by generating, using the input data, the at least some of the plurality of interaction profiles. ([0006] In another example embodiment, a method includes receiving data from a user. A user persona is created for the user based on the received data. The received data is analyzed to determine at least one communication style of the user and at least one learning style of the user. A personalized bot is created for the user based on the user persona, the communication style of the user, and the learning style of the user. )
Regarding claim 10, SHUKLA further teaches:
The system of claim 1, wherein the input data further describes a context for the action, and wherein generating the respective response to the action for each of the plurality of participants further uses the context for the action. ([0061]… In some embodiments, the user interaction engine 140 may be configured to obtain various sensory inputs such as, and without limitation, audio inputs, image inputs, haptic inputs, and/or contextual inputs, process these inputs, formulate an understanding of the human conversant, accordingly generate a response based on such understanding.)
Regarding claim 21, BUHMANN further teaches:
The system of claim 1, wherein the action comprises the same activity performed by each of the plurality of participants. ( (Col 4, lines 40-52) By way of overview, and referring back to FIG. 1, it is noted that, in some exemplary implementations, guests 126a and 126b may interact with respective characters 146a and 146b that may inhabit a story world (W) of a story having a timeline and a narrative arc or plot. Story world W is a blend of a virtual world and the real world, and can be changed by guests 126a and 126b as well as characters 146a and 146b. Software code 110 providing virtual agent 150/350, when executed by hardware processor 104, may control virtual agent 150/350 to simulate human-like affect-driven behavior, such as a human-like social interaction by one or both of characters 146a and 146b with respective guests 126a and 126b.
(Col 4, lines 53-64) It is further noted that, in some implementations, characters 146a and 146b may be different characters, while in other implementations, characters 146a and 146b may be different versions or instantiations of the same character. It is also noted that, in some implementations, even in lieu of an interaction between a character and one or more guests or guest object(s), the affective state of the character, including for example a personality profile, a mood, a physical state, an emotional state, and a motivational state of the character, can continue to evolve with advancement of the story including the character.)
Regarding claims 11, 13-14, 17-20, and 22 they comprise of limitations similar to those of claims 1, 3-4, 7-10, and 21 and are therefore rejected for similar rationale.
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over SHUKLA (U.S. Pub. No. US 20190202063 A1) and DOUEK (U.S. Pub. No. US 20200302263 A1) BUHMANN (U.S. Pub. No. US 11416732 B2) D'AGOSTINO (U.S. Pub. No. US 20180096322 A1) in further view of KATZ (U.S Pub. No. US 20200234181 A1)
While SHUKLA, as modified by DOUEK, does teach claim 1, which is dependent upon, it does not explicitly teach:
The system of claim 1, wherein at least one of the plurality of responses is used to train an artificial intelligence (Al) system.
However, in analogous art that similarly uses a dialog system to interact with users, KATZ teaches:
The system of claim 1, wherein at least one of the plurality of responses is used to train an artificial intelligence (Al) system. ([0037] In accordance with features of the invention, the personality model is sufficient for orchestrating the emotional response of the user so that it is consistent. To further train the system, some or all of the interactions(The interaction includes the response of the machine) can be annotated with a desired emotional response.)
It would have been obvious to a person skilled in the art before the effective filing date of the
invention to have combined with KATZ‘s training a system using the responses and, with SHUKLA‘s, as modified by DOUEK, teaching of receiving input, selecting a profile based on the input, and generating a response with the input and profile selection, to realize, with a reasonable expectation of success, a system that takes in user input, selects a profile, identifying a profile corresponding to a user, and generates a response to the user, as in SHUKLA, as modified by DOUEK, where the response is used to train a system, as in KATZ. A person of ordinary skill would have been motivated to increase the efficiency and effectiveness of the training (KATZ [0004]).
Regarding claim 15, it comprises of limitations similar to those of claim 5, and is therefore rejected for similar rationale.
Response to Arguments
Applicant’s arguments filed 29-DECEMBER-2025 have been fully considered, but they are found to be non-persuasive
With regards to the applicant’s remarks regarding the 103 rejection in the non-final action, the applicant argues that the prior art does not teach the newly amended claims 1 and 11. The examiner acknowledges this argument and has adjusted the prior art of SHUKLA and DOUEK to disclose the newly added limitations while adding D'AGOSTINO. Namely, DOUEK has been adjusted to show that it does have a plurality of interaction profiles as it has a plurality of users with unique interaction profiles. D'AGOSTINO has been added to disclose a parallel generation of responses using the interaction profiles concurrently. Further, the examiner has adjusted all dependent claims accordingly.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SKIELER A KOWALIK whose telephone number is (571)272-1850. The examiner can normally be reached 8-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mariela D Reyes can be reached at (571)270-1006. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SKIELER ALEXANDER KOWALIK/Examiner, Art Unit 2142
/Mariela Reyes/Supervisory Patent Examiner, Art Unit 2142
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