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 .
Response to Amendment
This office action is responsive to applicant’s remarks received on February 20, 2026. Claims 1-16 remain pending.
Response to Arguments
Applicant’s arguments with respect to amended the claims filed on February 20, 2026 have been fully considered but they are not persuasive.
A: Applicant’s Remarks
For applicant’s remarks “See Applicant Arguments/Remarks Made in an Amendment” filed on February 20, 2026.
A: Examiner’s Response
Applicant argues that the cited references either alone or in combination do not teach, disclose or suggest wherein the interactable interface comprises a suggestion generated based on a context corresponding to the one or more second users.
Examiner understands Applicant’s arguments but respectfully disagree. Carbune ‘129 at Paragraphs 0030 & 0060-0061 discloses wherein the interactable interface comprises a suggestion generated based on a context corresponding to the one or more second users. Here, the automated assistant can determine that the custom assistant response specified by the user is asking the user Jack “whether he finished his homework.” Additionally, the automated assistant can generate condition data characterizing a condition that the user Jack should come inside of the home in order for the automated assistant to provide the custom assistant response. When the one or more conditions have been satisfied, the method 500 can proceed to an operation 510 of causing the custom assistant response to be rendered at an interface of the computing device or another computing device. For instance, the automated assistant can determine that the user Jack has returned to inside of the home after having been outside of the home. In response to making this determination, the automated assistant can cause an interface of a computing device to provide an audible natural language output such as, “Hi Jack, did you finish your homework?” Alternatively, or additionally, the automated assistant 204 can render recorded audio characterizing at least a portion of the natural language input 230 provided by the other user 228. Thus, the cited references teach, disclose or suggest the Applicant’s claimed invention.
Accordingly, it is submitted that the present application is not in condition for allowance.
Claim Interpretations - 35 USC § 112(f)
(The previous claim interpretations are taken in consideration of applicant’s amendments.)
Claim Rejections - 35 USC § 103
1. 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.
2. 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.
3. Claims 1-5, 8-13 & 16 are rejected under 35 U.S.C. 103 as being unpatentable over Carbune et al. (US 20220013129 A1 hereinafter, Carbune ‘129) in view of Feuz et al (US 20190079724 A1 hereinafter, Feuz ‘724).
Regarding claim 9; Carbune ‘129 discloses a device (Fig. 4, Computing Device 402) for enabling indirect interactions among users in an Internet of Things (IoT) environment (i.e. This can include determining local and/or remote responses (e.g., answers) to the spoken utterance, interaction(s) with locally installed application(s) to perform based on the spoken utterance, command(s) to transmit to internet-of-things (IoT) device(s) (directly or via corresponding remote system(s)) based on the spoken utterance. Paragraph 0048),
the device comprising: at least one processor; and (i.e. Input Processing Engine 406):
a memory (Fig. 6, Memory 625) configured to store instructions (i.e. Memory 625 used in the storage subsystem 624 can include a number of memories including a main random access memory (RAM) 630 for storage of instructions and data during program execution and a read only memory (ROM) 632 in which fixed instructions are stored. Paragraph 0069) which, when executed by the at least one processor (i.e. These software modules are generally executed by processor 614 alone or in combination with other processors. Paragraph 0069)
cause the device to:
receive an utterance (Fig. 2A, Utterance 216) from a first user (Fig. 2A, User 214), wherein the utterance relates to at least one task that is to be performed by the first user (i.e. The user 214 can provide a spoken utterance 216 to a computing device 202, which provides access to the automated assistant 204. The spoken utterance 216 can be for example, “When Keith finishes eating, ask him whether he switched the laundry.” Paragraph 0027);
based on receiving the utterance, identify one or more second users (Fig. 2B, User 228) related to the at least one task (i.e. The automated assistant 204 can generate assistant data 206, which can characterize the process in which the automated assistant (i) provides the custom assistant response to the other user 228, (ii) determines whether the other user 228 replied to the custom assistant response, and then (iii) shares the reply with the user 214.” Paragraph 0027);
provide an interactable interface to one or more target devices which are located closer to the one or more second users than the device (i.e. The automated assistant 204 can cause an interface of another device 246, such as a display device, to render an audible output based on the natural language input 230 from the other user 228. For example, the other device 246 and the computing device 218 can be located in a home 238 of the user 214 and the other user 228. The computing device 218 and the other device 246 can communicate over a network. A natural language output 242 provided by the automated assistant 204 can be, for example, “Alina, Keith indicated that ‘yes,’ he did switch the laundry,” to which the user 214 can provide an acknowledging response 244, “Thank you.” Paragraph 0030);
wherein the interactable interface comprises a suggestion generated based on a context corresponding to the one or more second users (i.e. The automated assistant can determine that the custom assistant response specified by the user is asking the user Jack “whether he finished his homework.” Additionally, the automated assistant can generate condition data characterizing a condition that the user Jack should come inside of the home in order for the automated assistant to provide the custom assistant response. When the one or more conditions have been satisfied, the method 500 can proceed to an operation 510 of causing the custom assistant response to be rendered at an interface of the computing device or another computing device. For instance, the automated assistant can determine that the user Jack has returned to inside of the home after having been outside of the home. In response to making this determination, the automated assistant can cause an interface of a computing device to provide an audible natural language output such as, “Hi Jack, did you finish your homework?” Paragraphs 0030 & 0060-0061);
receive one or more inputs corresponding to the at least one task from the one or more second users through the interactable interface (i.e. The automated assistant 204 can cause an interface of another device 246, such as a display device, to render an audible output based on the natural language input 230 from the other user 228. For example, the other device 246 and the computing device 218 can be located in a home 238 of the user 214 and the other user 228. Paragraph 0030);
and append the received one or more inputs to the at least one task (i.e. A natural language output 242 provided by the automated assistant 204 can be, for example, “Alina, Keith indicated that ‘yes,’ he did switch the laundry,” to which the user 214 can provide an acknowledging response 244, “Thank you.” Paragraph 0030).
Examiner reasonably believes that Carbune ‘129 discloses each and every limitation as expressed above. In addition, Examiner cites Feuz ‘724 to enhance Carbune ‘129 and remedy any proposed deficiencies of Carbune ‘129.
Feuz ‘724 at the Abstract discloses wherein techniques are described related to improved intercom-style communication using a plurality of computing devices distributed about an environment. In various implementations, voice input may be received, e.g., at a microphone of a first computing device of multiple computing devices, from a first user. The voice input may be analyzed and, based on the analyzing, it may be determined that the first user intends to convey a message to a second user. A location of the second user relative to the multiple computing devices may be determined, so that, based on the location of the second user, a second computing device may be selected from the multiple computing devices that is capable of providing audio or visual output that is perceptible to the second user. The second computing device may then be operated to provide audio or visual output that conveys the message to the second user.
Carbune ‘129 and Feuz ‘724 are combinable because they are from same field of endeavor of speech systems (Feuz ‘724 at “Background”).
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the speech system as taught by Carbune ‘129 by adding the limitations as taught by Feuz ‘724. The motivation for doing so would have been advantageous to enable multiple users to leverage the distributed nature of a plurality of computing devices to facilitate communication between the multiple users. Therefore, it would have been obvious to combine Carbune ‘129 with Feuz ‘724 to obtain the invention as specified.
Regarding claim 10; Carbune ‘129 discloses wherein the instructions, when executed by the at least one processor further cause the device to: predict at least one context based on the utterance received from the first user (i.e. In response to receiving the spoken utterance 216, the automated assistant 204 can process input data 208 characterizing the spoken utterance 216. Based on this processing, the automated assistant 204 can determine that the spoken utterance 216 includes an assistant response request 210. Furthermore, the automated assistant 204 can generate condition data 212 that characterizes one or more conditions (e.g., a contextual condition, non-verbal activity, voice signature, etc.) that should be satisfied in order for the automated assistant 204 to provide a custom assistant response to another user 228. Paragraph 0027)
and identify the one or more second users related to the predicted at least one context (i.e. Furthermore, the automated assistant 204 can generate assistant data 206, which can characterize the process in which the automated assistant (i) provides the custom assistant response to the other user 228, (ii) determines whether the other user 228 replied to the custom assistant response, and then (iii) shares the reply with the user 214. Paragraph 0027).
Regarding claim 11; Carbune ‘129 discloses wherein the instructions, when executed by the at least one processor further cause the device to: perform the predicting of the at least one context and the identifying of the one or more second users using a trained learning method (i.e. The automated assistant 404 can be initialized based on processing of contextual data 436 using one or more trained machine learning models. The contextual data 436 can characterize one or more features of an environment in which the automated assistant 404 is accessible, and/or one or more features of a user that is predicted to be intending to interact with the automated assistant 404. Paragraph 0041)
Regarding claim 12; Carbune ‘129 discloses wherein the instructions, when executed by the at least one processor further cause the device to: obtain IoT data (i.e. This can include determining local and/or remote responses (e.g., answers) to the spoken utterance, interaction(s) with locally installed application(s) to perform based on the spoken utterance, command(s) to transmit to internet-of-things (IoT) device(s) (directly or via corresponding remote system(s)) based on the spoken utterance, and/or other resolution action(s) to perform based on the spoken utterance. Paragraph 048)
determine location history of at least one device which was last accessed by the one or more second users, based on the IoT data (i.e. The automated system determines the respective locations of the users. Paragraph 0027-0031).
and determine a current location of the one or more second users based on the location history (i.e. The automated system determines the respective locations of the users. The automated assistant can determine that the user Jack has returned to inside of the home after having been outside of the home. In response to making this determination, the automated assistant can cause an interface of a computing device to provide an audible natural language output such as, “Hi Jack, did you finish your homework?” Paragraphs 0027-0031 & 0061).
Regarding claim 13; Carbune ‘129 discloses wherein the instructions, when executed by the at least one processor further cause the device to: select the one or more target devices based on an availability of the one or more target devices, and a capability of the one or more target devices for performing at least one of delivering and receiving messages (i.e. The automated system determines selects the devices that are available. The automated assistant can determine that the user Jack has returned to inside of the home after having been outside of the home. In response to making this determination, the automated assistant can cause an interface of a computing device to provide an audible natural language output such as, “Hi Jack, did you finish your homework?” Paragraphs 0027-0031 &b 0061).
Regarding claims 1 & 16; Claims 1 & 16 contain substantially the same subject matter as claim 9. Therefore, claims 1 & 16 is rejected on the same grounds as claim 9.
Regarding claim 2; Claim 2 contains substantially the same subject matter as claim 10. Therefore, claim 2 is rejected on the same grounds as claim 10.
Regarding claim 3; Claim 3 contains substantially the same subject matter as claim 11. Therefore, claim 3 is rejected on the same grounds as claim 11
Regarding claim 4; Claim 4 contains substantially the same subject matter as claim 12. Therefore, claim 4 is rejected on the same grounds as claim 12.
Regarding claim 5; Claim 5 contains substantially the same subject matter as claim 13. Therefore, claim 5 is rejected on the same grounds as claim 13.
Regarding claim 8; Carbune ‘129 discloses wherein the one or more inputs comprise at least one of a requirement corresponding to the at least one task and an action content to be performed according to the at least one task (i.e. In response to receiving the spoken utterance 216, the automated assistant 204 can process input data 208 characterizing the spoken utterance 216. Based on this processing, the automated assistant 204 can determine that the spoken utterance 216 includes an assistant response request 210. Furthermore, the automated assistant 204 can generate condition data 212 that characterizes one or more conditions (e.g., a contextual condition, non-verbal activity, voice signature, etc.) that should be satisfied in order for the automated assistant 204 to provide a custom assistant response to another user 228. Furthermore, the automated assistant 204 can generate assistant data 206, which can characterize the process in which the automated assistant (i) provides the custom assistant response to the other user 228, (ii) determines whether the other user 228 replied to the custom assistant response, and then (iii) shares the reply with the user 214. When the automated assistant 204 successfully processes the assistant response request 210, the automated assistant 204 can provide an output 222 via a computing device 202, such as a stand-alone computer device 218. Paragraphs 0027-0031)
Allowable Subject Matter
1. Claims 6, 7, 14 & 15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
2. Claim 7 depends on indicated objected claim 6. Therefore, by virtue of its dependency, Claim 7 is also indicated as objected subject matter.
3. Claim 15 depends on indicated objected claim 14. Therefore, by virtue of its dependency, Claim 15 is also indicated as objected subject matter.
Examiners Statement of Reasons for Allowance
The cited reference (Carbune ‘129) teaches wherein implementations set forth herein relate to an automated assistant that can be customized by a user to provide custom assistant responses to certain assistant queries, which may originate from other users. The user can establish certain custom assistant responses by providing an assistant response request to the automated assistant and/or responding to a request from the automated assistant to establish a particular custom assistant response. In some instances, a user can elect to establish a custom assistant response when the user determines or acknowledges that certain common queries are being submitted to the automated assistant—but the automated assistant is unable to resolve the common query. Establishing such custom assistant responses can therefore condense interactions between other users and the automated assistant. Furthermore, as such interactions are more immediately resolved, the automated assistant can avoid wasteful consumption of computational resources that may otherwise occur during prolonged assistant interactions.
The cited reference (Feuz ‘724) teaches wherein techniques are described related to improved intercom-style communication using a plurality of computing devices distributed about an environment. In various implementations, voice input may be received, e.g., at a microphone of a first computing device of multiple computing devices, from a first user. The voice input may be analyzed and, based on the analyzing, it may be determined that the first user intends to convey a message to a second user. A location of the second user relative to the multiple computing devices may be determined, so that, based on the location of the second user, a second computing device may be selected from the multiple computing devices that is capable of providing audio or visual output that is perceptible to the second user. The second computing device may then be operated to provide audio or visual output that conveys the message to the second user.
The cited references fail to disclose wherein the at least one processor is further configured to provide the interactable interface to the one or more target devices by generating at least one of an interaction and a suggestion to provide to the one or more second users and wherein to generate the at least one of the interaction and the suggestion, the at least one processor is further configured to: obtain user context data and environment context data; and correlate the user context data and the environment context data with the predicted at least one context; based on at least a portion of the user context data and the environment context data being matched with the predicted at least one context, generate at least one suggestion, wherein the at least one suggestion is provided based on data stored in the one or more target devices or is provided as a recommendation that is relevant to the predicted at least one context; and based on the at least the portion of the user context data and the environment context data being not matched with the predicted at least one context, generate at least one interaction for directly conveying a message based on the utterance. As a result, and for these reasons, Examiner indicates Claims 6, 7, 14 & 15 as allowable subject matter.
Relevant Prior Art References Not Relied Upon
Zalewski et al. (US 2020 0244297 A1) - Energy harvesting Internet of Things (IOT) devices are shown including configurations involving a persistent memory, microcontroller, and flat antenna for electromagnetic RF harvesting. In one embodiment, multiple cycles of energy harvesting are performed by an IOT device, where power harvested via the flat antenna is transferred to a power storage of the device such that when the power storage has an amount of power the microcontroller performs processing resulting in state data stored to persistent memory, then during an additional cycle or cycles of energy harvesting, the device completes a process resulting in a payload that is sent to an end node via wireless transmission. Additional energy harvesting may be provided via an energy harvesting input that provides device input and causes additional energy for harvesting. Configurations include ones where energy harvesting is performed by the device, based on capturing vocal energy from a human voice spoken to the device. Configurations also include IOT devices coupled to cloud processing and cloud storage, cloud IOT device state setting, cloud IOT device state getting, cloud provisioning, etc.
Conclusion
THIS ACTION IS MADE FINAL. 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 MARCUS T. RILEY, ESQ. whose telephone number is (571)270-1581. The examiner can normally be reached 9-5 M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hai Phan can be reached at 571-272-6338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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MARCUS T. RILEY, ESQ.
Primary Examiner
Art Unit 2654
/MARCUS T RILEY/Primary Examiner, Art Unit 2654
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