DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is in response to applicant’s amendment filed on 12/31/2025.
Claims 1-2, 4-5, 7-9, 11-12, 14-16, 18-19 and 22-23 are pending and examined.
Claims 3, 6, 10, 13, 17 and 20-21 are cancelled.
Response to Arguments
Applicant's arguments filed 12/31/2025 with respect to 35 U.S.C. 103 have been fully considered but they are not persuasive. Applicant argues that “Russell, Zhou, Purves, and Li, singularly or in combination do not teach or suggest the above-presented features of independent claims 1, 8, and 15” and “that interchanging the various components of Russell to somehow include components of the geo-location device of Purves would render the prior art unsatisfactory for its intended purpose.” Examiner respectfully disagrees, see the 35 U.S.C. 103 rejections below for a detailed analysis. The examiner interprets Russell’s identification of the retailer which includes location information correlates to a location of the first user device. The funds request notification which includes the retailer identification is transmitted to the surrogate’s smart phone automatically correlates to forwarding the automated notification and the location of the first user device to the second user device. Although Russell does not explicitly teach that the location is determined via a geo-positioning system device, Purves is interpreted to address this limitation. In the example provided from Purves, John’s current location being tracked via WIVD GPS tracking correlates to using a geo-positioning system device to determine the location of the first user device. Purves additionally provides the example in the context of a fund transfer request (see paragraph 85), and therefore it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with Purves because the location of a user can be determined using GPS tracking to enable facial recognition or place virtual labels on unknown users. Wallet activities of users can also be used in combination with the current location of a user to send communications between multiple users. The type of communication may be based on the proximity of the users, which is determined using the GPS tracking location.
With regards to the other amended limitations, Zhou is interpreted to address the limitation of “wherein analyzing the audio communication further comprises parsing the audio communication to detect a plurality of words” because the voice recognition module converting the voice instruction sent by the user through speech recognition into corresponding text for processing correlates to the language processor parsing the audio communication to detect a plurality of words. Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with Zhou because voice analysis of transfer information can improve the accuracy and convenience of the transfer function by comparing the user’s voice instruction to historical transfer records to automatically record the name of the payee and associated account number. Additionally, Li is interpreted to address the limitation of “and generating, based on the plurality of words, a parse tree indicative of a language structure of the audio communication” because the search module determining a parse tree based on the user request representation, which converts audio input to a textual user request representation, correlates to generating a parse tree indicative of a language structure of the audio communication based on the plurality of words. Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with Li because natural language processing modules can be used to determine disambiguation data for ambiguous entities through parse trees. For example, requests for a specific target such as Portland can branch into all Portland locations.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 4-5, 7-9, 11-12, 14-16, 18-19 and 22-23 are rejected under 35 U.S.C. 103 as being unpatentable over Russell (US Patent No. US 12175473 B1), hereinafter “Russell” in view of Zhou et al. (CN Patent No. CN 111507698 A), hereinafter “Zhou,” Purves et al. (U.S. Patent No. US 20150073907 A1), hereinafter “Purves,” and Li et al. (U.S. Patent No. US 20220383872 A1), hereinafter “Li.”
With regards to Claim 1, Russell teaches:
A system for multi-channel cognitive virtual assistance for resource transfer requests, the system comprising:
at least one non-transitory storage device; and
at least one processor coupled to the at least one non-transitory storage device, wherein the at least one processor is configured to:
generate an automated notification based on the intent (Col. 6, lines 29-38, “In this embodiment, student 120 uses his smart phone 122 to transmit a request over the Internet 108 for approval to his mother 140 who is working in an office 104 at some remote location. The request/approval/denial process is managed by a secure Account Management Service (AMS) 110 which is based in the cloud. When the mother 140 receives the request on her smart phone 142 (or other device, such as a laptop computer or a tablet), she can approve the transaction or deny the request. Her decision may then be transmitted back to the student via AMS 110.” The AWS managing the fund transfer request from the student and transmitting the request over the internet to the mother’s smart phone correlates to generating an automated notification based on the intent to a second user device); determine a location of the first user device (Col. 8, lines 7-10 and 12-15, “request form 306 may include provisions for entering an amount 308 of the purchase, the category 310 of the contemplated purchase, the identification of the retailer 312 and the reason for the purchase 314… This information is transmitted via AMS 320 to the surrogate's smart phone 304. Thus the display 332 on her smart phone shows a funds request notification.” The identification of the retailer includes location information correlates to a location of the first user device); forward the automated notification and the location of the first user device to a second user device (Col. 8, lines 7-10 and 12-15, “request form 306 may include provisions for entering an amount 308 of the purchase, the category 310 of the contemplated purchase, the identification of the retailer 312 and the reason for the purchase 314… This information is transmitted via AMS 320 to the surrogate's smart phone 304. Thus the display 332 on her smart phone shows a funds request notification.” The identification of the retailer includes location information correlates to a location of the first user device. The funds request notification which includes the retailer identification is transmitted to the surrogate’s smart phone automatically correlates to forwarding the automated notification and the location of the first user device to the second user device);
receive an approval, denial, or change request in response to the automated notification (Col. 6, lines 34-38, “When the mother 140 receives the request on her smart phone 142 (or other device, such as a laptop computer or a tablet), she can approve the transaction or deny the request. Her decision may then be transmitted back to the student via AMS 110.” The mother approving or denying the request on her smart phone and the decision being transmitted back to the student via the AMS correlates to receiving an approval or denial request in response to the automated notification);
based on the approval, denial, or change request, initiate a resource action between the first resource account and the second resource account (Col. 6, lines 39-43, “If she approves the transaction, that approval is transmitted via AMS 110 to bank 150 through the bank's communications module 152, so that the funds can be withdrawn from the joint account 154 maintained in server 156 to pay the merchant who owns the retail store.” The approval request being transmitted via the AMS to the bank to withdraw funds from the joint account correlates to initiating a resource action between the first and second resource accounts based on the approval or denial).
Russell does not explicitly teach that the automated notification is based on the generated intent from a machine learning engine. However, machine learning engines are a popular method of identifying intent as evidenced by Zhou below (paragraph 69).
Russell also does not explicitly teach that the location of the first user device is determined via a geo-positioning system device. However, geo-positioning system devices are a popular method of determining a location as evidenced by Purves (paragraph 85, “For example, WIVD may form a query to a remote server, a cloud, etc., to inquire about John's current location via WIVD GPS tracking. As another example, WIVD may track John's current location via John's wallet activities (e.g., scanning an item, check-in at a merchant store, as discussed in FIGS. 2A-2C, etc.). If John 120b is remote to Jen's location, Jen may communicate with John via various messaging systems, e.g., SMS, phone, email, wallet messages, etc. For example, John 120b may receive a V.me wallet message indicating the fund transfer request 128.” John’s current location being tracked via WIVD GPS tracking correlates to using a geo-positioning system device to determine the location of the first user device).
Russell does not explicitly teach:
receive, from a first user device and via a receiver of a language processing module, an audio communication comprising a request to complete a resource transfer between a first resource account and a second resource account;
analyze, via a language processor of a language processing module, the audio communication to generate audio communication data, wherein analyzing the audio communication further comprises parsing the audio communication to detect a plurality of words and generating, based on the plurality of words, a parse tree indicative of a language structure of the audio communication;
retrieve, based on the audio communication data, additional data associated with the first resource account and the second resource account;
analyze, via a machine learning engine, the additional data and the audio communication data to generate an intent of the audio communication
However, Zhou teaches:
receive, from a first user device and via a receiver of a language processing module, an audio communication comprising a request to complete a resource transfer between a first resource account and a second resource account (Paragraph 66, “In operation S301, the user length according to the voice recognition button of mobile phone bank App, and speaking to the mobile phone microphone, sending voice instruction (e.g., to the Liu hui account 100 yuan). voice recognition module 301 by speech recognition of the speech content of the user, so as to convert the voice instruction sent by the user into the corresponding text, and the text is submitted to the text recognition module 302 to process.” The voice recognition module corresponds to a receiver of a language processing module and the text recognition module correlates to a language processing module. The user speaking through their mobile phone microphone to send a voice instruction to the voice recognition module correlates to receiving an audio communication comprising a request from a first user device via a receiver of a language processing module. The voice instruction including details for sending a specific account a specific amount of money from the user’s account correlates to a resource transfer request between a first and second resource account);
analyze, via a language processor of a language processing module, the audio communication to generate audio communication data (Paragraph 66, “voice recognition module 301 by speech recognition of the speech content of the user, so as to convert the voice instruction sent by the user into the corresponding text, and the text is submitted to the text recognition module 302 to process.” The voice recognition module converting the voice instruction sent by the user through speech recognition into corresponding text for processing correlates to the language processor of a language processing module analyzing the audio communication to generate audio communication data), wherein analyzing the audio communication further comprises parsing the audio communication to detect a plurality of words (Paragraph 66, “voice recognition module 301 by speech recognition of the speech content of the user, so as to convert the voice instruction sent by the user into the corresponding text, and the text is submitted to the text recognition module 302 to process.” The voice recognition module converting the voice instruction sent by the user through speech recognition into corresponding text for processing correlates to the language processor parsing the audio communication to detect a plurality of words);
retrieve, based on the audio communication data, additional data associated with the first resource account and the second resource account (Paragraphs 66 and 70, “voice recognition module 301 by speech recognition of the speech content of the user, so as to convert the voice instruction sent by the user into the corresponding text, and the text is submitted to the text recognition module 302 to process… Specifically, the text recognition module 302 combines the history transfer record of the resource transfer party account for speech recognition of the voice instruction, for example, in the history transfer record searching the payee name of the same tone with the payee name.” The text recognition module receives text corresponding to the voice instruction sent by the user. The text recognition module combining the history transfer record of the resource transfer party account, which includes a payee and resource transfer party account, correlates to retrieving additional data associated with the first and second resource account based on audio communication data) analyze, via a machine learning engine, the additional data and the audio communication data to generate an intent of the audio communication (Paragraphs 67-70, “Next, in operation S302, the text recognition module 302 receives the text, and analyzing the text data by semantic understanding model, outputting the intention analysis result and parameter. For example, analyzing the "giving Liu Hui account for 100 yuan"; identifying the operation of the user to be performed is "transfer account"; the name of the payee is "Liu Hui"; the transfer amount is "100 yuan". wherein the text recognition module 302 comprises a semantic understanding model established by natural language processing, machine learning and so on; the text recognition module further comprises a storage module for storing the mobile phone bank function information needed by establishing model, user search information and payee information and other business data… Specifically, the text recognition module 302 combines the history transfer record of the resource transfer party account for speech recognition of the voice instruction, for example, in the history transfer record searching the payee name of the same tone with the payee name.” The text recognition module comprising a semantic understanding model established by natural language processing and machine learning correlates to a machine learning engine. The text recognition module analyzing the text data and history transfer record through the semantic understanding module to output the intention analysis result correlates to analyzing the additional data and audio communication data via a machine learning engine to generate an intent of the audio communication)
Additionally, Li teaches:
and generating, based on the plurality of words, a parse tree indicative of a language structure of the audio communication (Paragraph 254, “For example, search module 902 employs natural language processing module 732 to determine a parse result for the natural language input (e.g., data representing a user intent, such as a parse tree) based on the user request representation. In examples where search module 902 receives the user request representation in audio form, search module 902 first causes ASR module 806 (e.g., if implemented on server system 900) to determine a textual user request representation. Search module 902 then employs natural language processing module 732 to determine the parse result based on the textual user request representation.” The search module determining a parse tree based on the user request representation, which converts audio input to a textual user request representation, correlates to generating a parse tree indicative of a language structure of the audio communication based on the plurality of words).
Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with receive, from a first user device and via a receiver of a language processing module, an audio communication comprising a request to complete a resource transfer between a first resource account and a second resource account; analyze, via a language processor of a language processing module, the audio communication to generate audio communication data, wherein analyzing the audio communication further comprises parsing the audio communication to detect a plurality of words; retrieve, based on the audio communication data, additional data associated with the first resource account and the second resource account; analyze, via a machine learning engine, the additional data and the audio communication data to generate an intent of the audio communication as taught by Zhou because voice analysis of transfer information can improve the accuracy and convenience of the transfer function by comparing the user’s voice instruction to historical transfer records to automatically record the name of the payee and associated account number (Zhou: paragraphs 40 and 44).
Additionally, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with and generating, based on the plurality of words, a parse tree indicative of a language structure of the audio communication as taught by Li because natural language processing modules can be used to determine disambiguation data for ambiguous entities through parse trees. For example, requests for a specific target such as Portland can branch into all Portland locations (Li: paragraphs 254-255).
Lastly, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with determining a location of a first user device using a geo-positioning system device as taught by Purves because the location of a user can be determined using GPS tracking to enable facial recognition or place virtual labels on unknown users. Wallet activities of users can also be used in combination with the current location of a user to send communications between multiple users. The type of communication may be based on the proximity of the users, which is determined using the GPS tracking location (Purves: paragraphs 84-86).
With regards to Claims 8 and 15, the system of Claim 1 performs the same steps as the machine and method of Claims 8 and 15 respectively, and Claims 8 and 15 are therefore rejected using the same rationale set forth above in the rejection of Claim 1.
With regards to Claim 2, Russell in view of Zhou, Purves and Li teaches the system of claim 1 above. Russell further teaches:
The system of claim 1, wherein the first resource account and the second resource account are managed by a common entity system (Fig. 2, Col. 7, lines 53-62 and Col. 10, lines 56-60, “Although FIG. 1 and FIG. 2 show the AMS as being based in the cloud, the AMS may be based in other locations, such as at a server in the bank or financial institution, a server in a dedicated facility for housing an AMS application or at some other server or device connected via wired, cable, or wireless connections, or a combination of the foregoing to the primary account holder's device, the secondary account holder's device, to the one or more surrogates' devices and to the financial institution hosting the account from which funds are to be withdrawn, for example… As shown in FIG. 2, an account management system (or AMS) may be used to control and direct the traffic and flow of information between the secondary account holder's smart phone, the surrogate's smart phone and the financial institution's server.” The AMS controlling and directing traffic between the primary, secondary and surrogate accounts correlates to the first and second resource account being managed by a common entity system).
With regards to Claims 9 and 16, the system of Claim 2 performs the same steps as the machine and method of Claims 9 and 16 respectively, and Claims 9 and 16 are therefore rejected using the same rationale set forth above in the rejection of Claim 2.
With regards to Claim 4, Russell in view of Zhou, Purves and Li teaches the system of claim 1 above. Russell further teaches:
The system of claim 1, wherein the automated notification further comprises a description of the resource transfer of the request in addition to one or more contextual details (Col. 8, lines 2-10, “In this example, the secondary account holder has filled out a request form 306, which is shown on both the display of his smart phone as he is filling it out, and on the display of the surrogate's smart phone as she is viewing the request. For example, request form 306 may include provisions for entering an amount 308 of the purchase, the category 310 of the contemplated purchase, the identification of the retailer 312 and the reason for the purchase 314.” The request form sent to the surrogate’s smart phone including details such as the category, identification of the retailer, and the reason for the purchase correlates to the automated notification comprising a description of the resource transfer of the request and one or more contextual details).
With regards to Claims 11 and 18, the system of Claim 4 performs the same steps as the machine and method of Claims 11 and 18 respectively, and Claims 11 and 18 are therefore rejected using the same rationale set forth above in the rejection of Claim 4.
With regards to Claim 5, Russell in view of Zhou, Purves and Li teaches the system of claim 1 above. Russell further teaches:
The system of claim 1, wherein the request further comprises a resource amount and one or more products or services (Col. 8, lines 2-10, “In this example, the secondary account holder has filled out a request form 306, which is shown on both the display of his smart phone as he is filling it out, and on the display of the surrogate's smart phone as she is viewing the request. For example, request form 306 may include provisions for entering an amount 308 of the purchase, the category 310 of the contemplated purchase, the identification of the retailer 312 and the reason for the purchase 314.” The request form sent to the surrogate’s smart phone including details such as the amount of the purchase and the category of the purchase correlates to a resource amount and one or more products or services),
and determine that the request is within a historical range of resource amount or matches products or services of one or more historical resource transfers (Fig. 6, Col. 10, lines 19-22 and 25-29, “FIG. 6 is a schematic diagram 600 illustrating the different automatic or discretionary responses that might be available to the primary account holder (List P, 602) and to a surrogate (list S, 604) … Thus, list P automatically approves requests for $25 or less; requests for purchases of textbooks; requests for disbursements at hospitals; requests for car repair; and requests for payments of tuition, as shown in “Approved” list 606.” The automatic approval of requests for routine payments such as tuition, car repair and purchases of textbooks correlates to the system determining the request matches products or services of one or more historical transfers).
Zhou further teaches:
and the system is further configured to:
compare the request to a resource transfer history between the first resource account and the second resource account (Paragraphs 68-70, “Specifically, the text recognition module 302 combines the history transfer record of the resource transfer party account for speech recognition of the voice instruction, for example, in the history transfer record searching the payee name of the same tone with the payee name. For example, the name of the payee identified by the text is "Liu Hui"; the mobile phone bank system compares the history transfer record of the resource transfer side account without the related transfer record of the "Liu Hui"; but there is the related transfer record of the "Liu Hui" together with the payee, At this time, the name of the payee identified by the text can be recorded as "Liu Hui" to replace the "Liu Hui." The payee name identified from the text input to the text recognition module correlates to the request between the first and second resource account. The history transfer record of the resource transfer party account being compared to the payee name for related transfer records correlates to comparing the request to a resource transfer history between the first and second resource accounts);
Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with and the system is further configured to: compare the request to a resource transfer history between the first resource account and the second resource account as taught by Zhou because comparing the user’s voice instruction to historical transfer records by voice analysis of transfer information to automatically record the name of the payee and associated account number can improve the accuracy and convenience of the transfer function (Zhou: paragraphs 40 and 44).
With regards to Claims 12 and 19, the system of Claim 5 performs the same steps as the machine and method of Claims 12 and 19 respectively, and Claims 12 and 19 are therefore rejected using the same rationale set forth above in the rejection of Claim 5.
With regards to Claim 7, Russell in view of Zhou, Purves and Li teaches the system of claim 1 above. Russel further teaches:
wherein the system is further configured to transmit a final approval request to the second user device prior to initiating the resource action between the first resource account and the second resource account (Col. 6, lines 34-46, “When the mother 140 receives the request on her smart phone 142 (or other device, such as a laptop computer or a tablet), she can approve the transaction or deny the request. Her decision may then be transmitted back to the student via AMS 110… If she approves the transaction, that approval is transmitted via AMS 110 to bank 150 through the bank's communications module 152, so that the funds can be withdrawn from the joint account 154 maintained in server 156 to pay the merchant who owns the retail store. If the primary account holder approves the request, the student may enter a PIN to confirm his identity as an authorized user of the chip card.” The mother receiving a request on her phone and approving the transaction, which is then transmitted to the bank in order to enable withdrawing funds subject to primary account holder approval, correlates to transmitting a final approval request to the second user device prior to initiating the resource action between the first and second resource accounts).
With regards to Claim 14, the system of Claim 7 performs the same steps as the machine of Claim 14, and Claim 14 is therefore rejected using the same rationale set forth above in the rejection of Claim 7.
With regards to Claim 22, Russell in view of Zhou, Purves and Li teaches the system of claim 1 above. Li further teaches:
where the system is further configured to analyze the parse tree to detect the intent of the audio communication (Paragraph 254, “For example, search module 902 employs natural language processing module 732 to determine a parse result for the natural language input (e.g., data representing a user intent, such as a parse tree) based on the user request representation. In examples where search module 902 receives the user request representation in audio form, search module 902 first causes ASR module 806 (e.g., if implemented on server system 900) to determine a textual user request representation. Search module 902 then employs natural language processing module 732 to determine the parse result based on the textual user request representation.” The search module using a parse tree based on the audio form of user request representation to determine a parse result representing a user intent, correlates to analyzing the parse tree to detect the intent of the audio communication).
Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with where the system is further configured to analyze the parse tree to detect the intent of the audio communication as taught by Li because natural language processing modules can be used to determine disambiguation data for ambiguous entities through parse trees. For example, requests for a specific target such as Portland can branch into all Portland locations. Audio forms of user request representation can further be processed into a textual form for determining parse results for the natural language input (Li: paragraphs 254-255).
With regards to Claim 23, Russell in view of Zhou, Purves and Li teaches the system of claim 1 above. Zhou further teaches:
wherein the system is further configured to:
determine, via the generated intent and using the language processor, a service associated with the audio communication to invoke (Paragraph 73, “then, in the operation S303, the service processing module 303 receives the text identification module outputs the intention analysis result data, and the intention result data into account transfer function jump request data can be identified by the mobile phone bank system, and the request carries the payee name "Liu Hui," The transfer amount "100 yuan" is the two transfer parameters.” The service processing module receiving the intention analysis result data from the text identification module and inputting the data into the mobile phone bank system to carry out the request correlates to determining a service associated with the audio communication to invoke based on the generated intent language processor);
identify, using the language processor, one or more parameters required to complete the service (Paragraphs 67 and 73, “Next, in operation S302, the text recognition module 302 receives the text, and analyzing the text data by semantic understanding model, outputting the intention analysis result and parameter… then, in the operation S303, the service processing module 303 receives the text identification module outputs the intention analysis result data, and the intention result data into account transfer function jump request data can be identified by the mobile phone bank system, and the request carries the payee name "Liu Hui," The transfer amount "100 yuan" is the two transfer parameters” The service processing module identifying the parameters received from the text recognition module such as transfer amount and payee name correlates to identifying one or more parameters required to complete the service using the language processor;
generate, via a service invoker of the language processing module, a command associated with the service and the one or more parameters (Paragraph 67-68 and 73, “Next, in operation S302, the text recognition module 302 receives the text, and analyzing the text data by semantic understanding model, outputting the intention analysis result and parameter. For example, analyzing the "giving Liu Hui account for 100 yuan"; identifying the operation of the user to be performed is "transfer account"; the name of the payee is "Liu Hui"; the transfer amount is "100 yuan"… then, in the operation S303, the service processing module 303 receives the text identification module outputs the intention analysis result data, and the intention result data into account transfer function jump request data can be identified by the mobile phone bank system, and the request carries the payee name "Liu Hui," The transfer amount "100 yuan" is the two transfer parameters.” The text recognition module outputting the intention analysis result data including operations of the user to be performed that further include parameters to the service processing module correlates to the service invoker of the language processing module generating commands associated with the service and one or more parameters); and
transmit, via the service invoker, the command to invoke the service (Paragraphs 73-74, “then, in the operation S303, the service processing module 303 receives the text identification module outputs the intention analysis result data, and the intention result data into account transfer function jump request data can be identified by the mobile phone bank system, and the request carries the payee name "Liu Hui," The transfer amount "100 yuan" is the two transfer parameters. Then, in operation S304, the mobile phone bank system reads the name of the payee, "Liu Hui", the account transfer amount is more than 100 yuan, and searching the account of the payee associated with the user input from the history transfer record of the resource transfer side account, entering the transfer information recording interface, and automatically recording the payee name "Liu Hui", The account of the payee "China Construction Bank 6217 * *** 3051"; the transfer amount is "100 yuan".” The service processing module carrying out an account transfer function jump request to the mobile phone bank system correlates to the service invoker transmitting the command to invoke the service).
Therefore, it would have been obvious to one of ordinary skill in the art to which said subject matter pertains before the effective filing date of the claimed invention to combine Russell with wherein the system is further configured to: determine, via the generated intent and using the language processor, a service associated with the audio communication to invoke; identify, using the language processor, one or more parameters required to complete the service; generate, via a service invoker of the language processing module, a command associated with the service and the one or more parameters; and transmit, via the service invoker, the command to invoke the service as taught by Zhou because identifying relevant parameters for a request allows a user to easily confirm a transfer amount and target for the desired transfer before initiating the transfer (Zhou: paragraph 72).
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Kendall (U.S. Patent No. US 20180232258 A1); teaching a system of verifying resource transfers in real-time through the use of a quantum optimizer and classical computer apparatus. The quantum optimizer generates a model for verifying resource transfers using historical resource transfer information. Upon receipt of a new transfer request, the classical computer apparatus transfers request information to the quantum optimizer for verification prior to processing the resource transfer request.
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 SELINA HU whose telephone number is (571)272-5428. The examiner can normally be reached Monday-Friday 8:30-5:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chat Do can be reached at (571) 272-3721. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SELINA ELISA HU/Examiner, Art Unit 2193
/Chat C Do/Supervisory Patent Examiner, Art Unit 2193