Patent Application 17835387 - METHODS AND SYSTEMS FOR DETERMINING MISSING - Rejection

Patent Application 17835387 - METHODS AND SYSTEMS FOR DETERMINING MISSING

Title: METHODS AND SYSTEMS FOR DETERMINING MISSING SLOTS ASSOCIATED WITH A VOICE COMMAND FOR AN ADVANCED VOICE INTERACTION

Application Information

• Invention Title: METHODS AND SYSTEMS FOR DETERMINING MISSING SLOTS ASSOCIATED WITH A VOICE COMMAND FOR AN ADVANCED VOICE INTERACTION
• Application Number: 17835387
• Submission Date: 2025-05-15T00:00:00.000Z
• Effective Filing Date: 2022-06-08T00:00:00.000Z
• Filing Date: 2022-06-08T00:00:00.000Z
• National Class: 704
• National Sub-Class: 232000
• Examiner Employee Number: 96925
• Art Unit: 2656
• Tech Center: 2600

Rejection Summary

• 102 Rejections: 0
• 103 Rejections: 4

Cited Patents

The following patents were cited in the rejection:

• US 9672812🔗
• US 9691379🔗

Office Action Text

    DETAILED ACTION
This office action is in response to Applicant’s RCE submission filed on 4/17/2025. Claims 1-2, 5-8 and 11-12 are pending and have been examined in the application. Applicant has amended claims 1, and 7 and cancelled claims 3 and 9.

A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection.  Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.  Applicant's submission filed on 4/17/2025 has been entered.

	
Response to Amendment and Arguments
Applicant’s amendments and arguments regarding 35 U.S.C. 101 Rejections are considered but are unpersuasive. 
This action is Final.

35 U.S.C. 101 Rejections
	Applicant argues in pg. 6, that the claims 1 and 7 is not a mental process and/or mathematical concept, and therefore not an abstract idea, that the claim recite a microphone to receive voice command from a user, that since voice is received through hardware configuration, its not a human action. Applicant further claims the idea of the invention is pertaining to an improvement in technology, that the claim integrates exception into a practical application, and the claims are patent eligible under prong two of step2A and step2B.  Those argument has been considered and are not persuasive. 
	Although Applicant argues that the use of microphone which is a hardware is not a human action, however, the use of a microphone is similar to using a generic or conventional computer component recited at a high level of generality. Simply reciting a generic microphone without any specifics, inventive and/or technical implementation does not overcome the abstract idea.  It does not appear the use of a microphone in the claim goes beyond just using it to process a speech input, its not particularly clear what the novelty of the claim is, or how the microphone it is being used in a innovative or a specific method, or what distinct advantage it involves to solving a specific problem.  Moreover, the Applicant has not provided further clear details, specific points or examples from the claim or the specification, other than general allegation that the claimed invention pertaining to an improvement in technology or how the abstract idea is being integrated into a practical application or even point to what that practical application is.  Therefore, the claim is not eligible under Prong two of Step 2A.  Further, Applicant’s argument under Prong two of Step 2B, is more of the general alleged statement without clearly and specifically pointing out how the particular combination of the elements recited in the pending claims are not simply “well-understood, routine, conventional” activities.   Therefore, the argument that these features, when viewed in combination, amounts to significantly more than the judicial exception is also not persuasive, and thus, the patent eligibility for subject matter concept under Step 2B also failed.  Hence, the claim is not patent eligible.  



35 U.S.C. 103 Rejections
Applicant argues in pg. 10 and 11 that Jaygarl reference criterion of dependency is not clear and limits cases where there are different endpoints, that argument is partially persuasive, therefore the rejection is withdrawn, however, new ground of rejection using Ramachandra is provided below.

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 1-2, 5-8, and 11-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. 
Claim 1 recites a method that, under the broadest reasonable interpretation, claims limitations that cover performance of the limitations in the human mind with the assistance of physical aids (e.g., pen and paper), but for the recitation of generic computer components.  That is, other than reciting “a system”, nothing in these claim limitations precludes the steps from practically being performed in the mind.  As a whole, claim 1 pertains to analyzing an intent from a user by determining the possible missing elements in the associated query, which is a mental process that a human can do.  Individually, each of the limitations also pertains to a mental process, for example:
receiving, by a microphone of a system, the voice command from a user; (e.g., a human can receive a voice command, such as “please give me direction to ABC restaurant”) The microphone is a generic computer component, which is well known component for receiving voice or speech command.  More on the microphone and/or generic computer component are discussed below.
generating, by the system, a textual input from the voice command received from the user; (e.g., the human can mentally write down what is said or heard)
identifying, by the system, one or more intents, one or more slots and a relation between the one or more intents and the one or more slots associated with the textual input; (e.g., the human can mentally figure out an intent, what info is given and what is needed to carry out the task by looking at the transcript or text)
identifying, by the system, one or more key phrases associated with the textual input and one or more domains associated with the textual input based on the one or more key phrases; (e.g., the human can mentally identify particular words or phrases are associated with certain domain based on looking at the text, “please give me direction to ABC restaurant, which is related to direction or map.)
determining, by the system, one or more missing slots associated the one or more domains for the one or more intents based on fetching information associated with the one or more missing slots from a domain specific knowledge base,  (e.g., the human can mentally determine or with the assistance of pen and paper provide direction, the human can also use knowledge of the area to seek clarification from the requester, because driving, walking or public transit options are available and each may be a different direction.) Moreover, simply retrieving information from a knowledge base is insignificant pre-solution data gathering activity that is not sufficient to render the claims subject matter eligible.  MPEP 2106.05(g).  
determining, by the system, an operational dependency amongst the one or more intents and the one or more missing slots based on domain specific knowledge associated with the one or more intents fetched from the domain specific knowledge base, wherein the operational dependency determines an order to arrange the one or more intents for executing the textual input; (e.g., the human can figure out which action should be taken first by looking at the intents, the missing elements based on domain specific knowledge.) Moreover, simply retrieving information from a knowledge base is insignificant pre-solution data gathering activity that is not sufficient to render the claims subject matter eligible.  MPEP 2106.05(g).  
re-ordering, by the system, the one or more intents based on the operational dependency amongst the one or more intents and the one or more missing slots; (e.g., the human can re-order the sequence of intents based on the operation dependency and the missing information.)
and executing, by the system, the textual input based on the one or more intents, the order associated with the one or more intents, the one or more domains, the one or more key phrases, the one or more slots, and the one or more missing slots, (e.g., the human write down the intent from the user based on the intents, the order associated with the intents, the particular domain of the intent, the key phrases and the missing information.)
wherein the identifying of the one or more missing slot comprises: extracting, by the system, one or more missing slot classes for the one or more intents based on the textual input, the one or more key phrases, and the one or more domains from the domain specific knowledge base. (e.g., the human can determine and writing down what type of information is missing, by evaluating the input query along with the key phrases in view of the domain it is in.)
The judicial exception is not integrated into a practical application. In particular, the claims only recites generic computing components (such as a microphone). Such generic computing components are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of receiving, determining, or outputting information) such that they amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional limitations of using generic computer components amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Claim 1 is not patent eligible.
The examiner further notes that the use of claimed generic computer components (“system”) invokes such generic computer components “merely as a tool to perform an existing process”.  MPEP 2106.05(f).  MPEP 2106.05(f) further explains:
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. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). 

Claim 1 recites generic computer components (“system” and “microphone”) only in the preamble, with respect to performing tasks.  MPEP 2106.05(d) and (f) further provides examples of court decisions where the courts found generic computing components to be mere instructions to apply a judicial exception, and further explains “increased speed” (e.g., using a computer to increase the speed of an otherwise mental process) does not provide an inventive concept.  For example:
A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
A process for monitoring audit log data that is executed on a general-purpose computer where the increased speed in the process comes solely from the capabilities of the general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016) (emphasis added).
Performing repetitive calculations. Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.")

The following reference discloses a microphone, which without further specificity is considered to be a generic or general computer component model that is well known or conventional.  Additionally, it appears that the microphone is just being use to process an input to obtain an output without furthermore.  

US 20150317973

US 20170169818

US 20190180759

US 9691379

US 20170123757

US 9672812

US 20180211151

US 20190259389

Claim 7 recites a system that corresponds to the method of claim 1 and is therefore rejected under the same grounds as claim 1 above.  While claim 7 further recites a “memory” and “processor”, “program including instructions”, “a generation engine”, “a joint multi-tasking deep learning model”, “a key term and domain extractor”, “a missing slot extractor, and “an intent execution extractor”, as these are merely generic computer components recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component.  Therefore, none of these limitations (a) integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea or (b) amount to significantly more than the judicial exception, because in either case the additional limitations merely utilize generic computer components that amounts to no more than mere instructions to apply the exception using generic computer function.  Claim 7 is not patent eligible.  

The following reference discloses a joint multi-tasking deep learning model, which without further specificity is considered to be a generic or general model that is well known or conventional.  Additionally, it appears that the model is just being use to process an input to obtain an output without furthermore.  

Hakkani-Tur et al. US 20170372199 A1
Hashimoto et al. US 20180121799 A1
Huang et al. US 20210141862 A1
Makki Niri et al. US 20220414344 A1

Ni, P., Li, Y., Li, G., & Chang, V. (2020). Natural language understanding approaches based on joint task of intent detection and slot filling for IoT voice interaction. Neural Computing and Applications, 32, 16149-16166.

Abro, W. A., Qi, G., Ali, Z., Feng, Y., & Aamir, M. (2020). Multi-turn intent determination and slot filling with neural networks and regular expressions. Knowledge-Based Systems, 208, 106428.
Claims 2-3, 5-6, 8-9, and 11-12 depend from claim 1, do not remedy any of the deficiencies of claim 1, and therefore are rejected on the same grounds as claim 1 above.
	Claim 2 further recites the mental processes of: raising, by the system, one or more queries for the user based on the textual input, the one or more intents, the one or more domains in response to not identifying the one or more missing slots from the domain specific knowledge base; (e.g., a human can figure out what is missing and asking the user for the missing info.) 
and identifying, by the system, the one or more missing slots for the textual input based on a response received from the user corresponding to the query. (e.g., the human can identify the missing parameter of the query based on the response from the user.)
Claim 5 further recites the mental process of: extracting, by the system, a missing slot class value associated with the one or more missing slot classes based on information fetched from the domain specific knowledge base; (e.g., a human can note or write down the missing parameter value gathered from a knowledge base which could be the human’s own brain which can contains a lot of information.)
and determining, by the system, the one or more missing slots based on the missing slot class value associated with the one or more missing slots fetched from the domain specific knowledge base. (e.g., the human can figure out what the missing elements or information is based on the missing expected value from knowledge or a domain specific knowledge base which could be a book or encyclopedia)
	Claim 6 further recite mental processes: wherein extracting the missing slot class value is based on metadata associated with the domain specific knowledge base, the one or more missing slot classes, the textual input, and a past behavior obtained a training data set generated associated with previous textual inputs. (e.g., a human can determine the missing parameter class value from metadata which is context and information about the data within a particular domain, the missing parameter type, the text input, and from historical/previous interactions.)
Claim 8 is a system claim with limitations similar to the limitations of Claim 2 and is rejected under similar rationale.
Claim 11 is a system claim with limitations similar to the limitations of Claim 5 and is rejected under similar rationale.
Claim 12 is a system claim with limitations similar to the limitations of Claim 6 and is rejected under similar rationale.
In sum, claims 2, 5-6, 8, and 11-12 depend from claim 1 and 7 respectively, and further recite mental processes as explained above.  None of the additional limitations recited in claims 2, 5-6, 8, and 11-12 amount to anything more than the same or a similar abstract idea as recited in claim 1 and 7 respectively.  Nor do any limitations in claims 2, 5-6, 8, and 11-12: (a) integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea or (b) amount to significantly more than the judicial exception because the additional limitations of using generic computer components amounts to no more than mere instructions to apply the exception using generic computer components.  Claims 2, 5-6, 8, and 11-12 are not patent eligible.

Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. 

The following is a quotation of pre-AIA  35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.

The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art.  The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is invoked. 
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph:
(A)	the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; 
(B)	the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and 
(C)	the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. 
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. 
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. 
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.  Such claim limitation(s) is/are: “a generation engine”, “a key term and domain extractor”, “a missing slot extractor”, and “an intent execution extractor”, in claims 7-8, and 11-12.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, applicant may:  (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph.

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(s) 1-2, and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Ramachandra (US 20190163785).
Regarding claim 1, Lee discloses: A method for determining one or more missing slots associated with a voice command for an advanced voice interaction, the method comprising: receiving, by a microphone ([0075] a microphone for receiving voice or spoken utterance) of a system, the voice command from a user; ([0012] A speech processing method according to an embodiment of the present disclosure may include receiving a spoken response utterance corresponding to a spoken query utterance fed back to a user, and determining any one electronic device to be operated and causing the determined electronic device to operate, when a voice command included in a spoken utterance of the user can be processed by a plurality of electronic devices.)
generating, by the system, a textual input from the voice command received from the user; ([0013] In detail, the speech processing method according to this embodiment of the present disclosure may include converting a user's spoken utterance including a voice command into a user utterance text,)
identifying, by the system, one or more intents, one or more slots and a relation between the one or more intents and the one or more slots associated with the textual input; ([0023] discover a domain to which the user utterance text belongs and an intent of the user utterance text by performing syntactic analysis or semantic analysis on the user utterance text, and discover at least one named entity as a result of recognizing a named entity included in the user utterance text; determine whether the user's spoken utterance is a complete spoken utterance or an incomplete spoken utterance according to a result of discovering the domain, the intent, and the named entity;)
identifying, by the system, one or more key phrases associated with the textual input and one or more domains associated with the textual input based on the one or more key phrases; ([0099] In an exemplary embodiment, the natural language understanding processor 152 may use a matching rule stored in the second database 157, that is, a natural language understanding database, in order to discover the domain and the intent. The natural language understanding processor 152 may recognize a meaning of a word (named entity) extracted from the user utterance text using linguistic features (for example, a syntactic element) of a morpheme, a phrase, or the like, and may match the recognized meaning of the word to the domain and the intent in order to discover the intent of the user.  Also see [0063, 0096])
determining, by the system, one or more missing slots associated the one or more domains for the one or more intents based on fetching information associated with the one or more missing slots from a domain specific knowledge base; ([0139] In operation S630, the speech processing apparatus 100 determines whether the spoken utterance of the user is a complete spoken utterance or an incomplete spoken utterance according to the domain, the intent, and the result of discovering the named entity. The speech processing apparatus 100 may determine, from the user utterance text, essential slots including the first slot related to the domain, the second slot related to the intent, and the third slot related to an amount-related named entity. The speech processing apparatus 100 may determine that the user spoken utterance is a complete spoken utterance when the essential slots are all filled with a named entity in the user utterance text, and may determine that the user spoken utterance is an incomplete spoken utterance when an essential slot lacking a named entity is present in the user utterance text.) [0112] discloses a knowledge base. [0099] discloses a domain specific knowledge base.
wherein the identifying the one or more missing slots comprises: extracting, by the system, one or more missing slot classes for the one or more intents based on the textual input, the one or more key phrases, and the one or more domains from the domain specific knowledge base. ([0099] The natural language understanding processor 152 may recognize a meaning of a word (named entity) extracted from the user utterance text using linguistic features (for example, a syntactic element) of a morpheme, a phrase, or the like, and may match the recognized meaning of the word to the domain and the intent in order to discover the intent of the user. For example, the natural language understanding processor 152 may discover the domain and the intent by calculating how many words (named entities) extracted from the user utterance text is included in each domain and intent.)
Lee does not explicitly, but Ramachandra discloses: further comprising: determining, by the system, an operational dependency amongst the one or more intents and the one or more missing slots based on domain specific knowledge associated with the one or more intents fetched from the domain specific knowledge base, wherein the operational dependency determines an order to arrange the one or more intents for executing the textual input; ([0029] In an embodiment, upon retrieving the one or more responses 110 to each of the one or more sub-queries 106, the response generation system 101 collates each of the one or more responses 110 to generate a single domain-specific response 112 to the user query 104. As an example, each of the one or more responses 110, corresponding to each of the one or more sub-queries 106, may be arranged in an order of the one or more sub-queries 106 present in the user query 104. Further, the response generation system 101 may check for completeness/sufficiency in the domain-specific response 112 before providing the response to the user 103. As an example, the sufficiency of the domain-specific response 112 may be determined by mapping each of the one or more responses 110 with each of the corresponding one or more sub-queries 106 and verifying that responses for each of the one or more sub-queries 106 have been retrieved from the one or more DQHs 109. [0045] In an embodiment, the query splitting module 215 may determine the dependency among the one or more sub-queries 106, along with a sequence of processing each of the one or more sub-queries 106. As an example, the query splitting module 215 may determine the dependency among the one or more sub-queries 106 by comparing the one or more domain-specific keywords in each of the one or more sub-queries 106.)
re-ordering, by the system, the one or more intents based on the operational dependency amongst the one or more intents and the one or more missing slots; ([0045] In an embodiment, the query splitting module 215 may determine the dependency among the one or more sub-queries 106, along with a sequence of processing each of the one or more sub-queries 106. As an example, the query splitting module 215 may determine the dependency among the one or more sub-queries 106 by comparing the one or more domain-specific keywords in each of the one or more sub-queries 106.) Also see [0029].
and executing, by the system, the textual input based on the one or more intents, the order associated with the one or more intents, the one or more domains, the one or more key phrases, the one or more slots, and the one or more missing slots. (([0029] In an embodiment, upon retrieving the one or more responses 110 to each of the one or more sub-queries 106, the response generation system 101 collates each of the one or more responses 110 to generate a single domain-specific response 112 to the user query 104. As an example, each of the one or more responses 110, corresponding to each of the one or more sub-queries 106, may be arranged in an order of the one or more sub-queries 106 present in the user query 104. Further, the response generation system 101 may check for completeness/sufficiency in the domain-specific response 112 before providing the response to the user 103. As an example, the sufficiency of the domain-specific response 112 may be determined by mapping each of the one or more responses 110 with each of the corresponding one or more sub-queries 106 and verifying that responses for each of the one or more sub-queries 106 have been retrieved from the one or more DQHs 109. [0045] In an embodiment, the query splitting module 215 may determine the dependency among the one or more sub-queries 106, along with a sequence of processing each of the one or more sub-queries 106. As an example, the query splitting module 215 may determine the dependency among the one or more sub-queries 106 by comparing the one or more domain-specific keywords in each of the one or more sub-queries 106.))
Lee and Ramachandra are considered analogous art.  Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to combine the teachings of Lee and Ramachandra.  As disclosed in Ramachandra, one of ordinary skill would have been motivated to do so in order to performing action based on importance and relevance of the user query and improve efficiency in resource allocation (para. 0101).

Regarding claim 2, Lee in view of Ramachandra discloses: The method as claimed in claim 1, 
Lee further discloses: further comprising: raising, by the system, one or more queries for the user based on the textual input, the one or more intents, the one or more domains in response to not identifying the one or more missing slots from the domain specific knowledge base; ([0029] When generating the query text, the one or more processors may be configured to: generate a query text related to the domain when a named entity is missing in the first slot; generate a query text related to the intent when a named entity is missing in the second slot after the first slot is filled with a named entity; and generate a query text related to a slot lacking an amount-related named entity when a named entity is missing in the third slot after the second slot is filled with a named entity.)
and identifying, by the system, the one or more missing slots for the textual input based on a response received from the user corresponding to the query. ([0030] Furthermore, when constructing the complete spoken utterance, the one or more processors may be configured to: fill essential slots lacking a named entity with a named entity by repeating feedback of the spoken query utterance and reception of the user's spoken response utterance; and complete, as the complete spoken utterance, a user's spoken utterance in which the essential slots lacking a named entity are all filled with a named entity.)

Regarding claim 5, Lee in view of Ramachandra discloses: The method as claimed in claim 1, 
Lee further discloses: further comprising: extracting, by the system, a missing slot class value associated with the one or more missing slot classes based on information fetched from the domain specific knowledge base; ([0018] The generating the spoken query utterance may include determining a slot lacking a named entity among required slots in the user utterance text on the basis of a pre-established state table including a required slot in a user command text according to the domain and the intent, and a query text to be requested corresponding to the required slot; generating the query text corresponding to the slot lacking a named entity on the basis of the state table; and converting the generated query text into a spoken query utterance and feeding the spoken query utterance back to the user.  Also see [0019] and claim 5.)
and determining, by the system, the one or more missing slots based on the missing slot class value associated with the one or more missing slots fetched from the domain specific knowledge base. ([0020] The generating the query text may include generating a query text related to domain when a named entity is missing in the first slot, generating a query text related to intent when a named entity is missing in the second slot after the first slot is filled with a named entity, and generating a query text related to a slot lacking an amount-related named entity when a named entity is missing in the third slot after the second slot is filled with a named entity.  Also see [0018-0019] and claim 5.)

Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Ramachandra and further in view of Johnson (US 20210082414 A1), hereinafter referenced as Johnson.
Regarding claim 6 Lee in view of Ramachandra discloses: The method as claimed in claim 5,  
Lee further discloses: wherein extracting the missing slot class value is based on metadata associated with the domain specific knowledge base, the one or more missing slot classes, the textual input, and a past behavior obtained a training data set generated associated with previous textual inputs. ([0063] The server 30 may receive the spoken utterance of the user from the speech processing apparatus 100, and convert the spoken utterance into the user utterance text. The server 300 may perform syntactic analysis or semantic analysis on the user utterance text to discover a domain to which the user utterance text belongs and an intent of the user utterance text, and may discover at least one named entity as a result of recognizing a named entity included in the user utterance text. Here, the server 300 may perform a machine learning algorithm to perform the syntactic analysis or semantic analysis on the user utterance text. The server 300 may determine whether the spoken utterance of the user is a complete spoken utterance or an incomplete spoken utterance according to the domain, the intent, and the result of discovering the named entity. When the spoken utterance of the user is incomplete, the server 300 may generate a spoken query utterance that requests information for completing the incomplete spoken utterance as a complete spoken utterance. [0117] The natural language understanding processor 152 may add (406) a named entity obtained from the current user utterance text (“air conditioner”) to the domain, intent, and named entity obtained from the previous user utterance text (“further decrease the temperature”).)
Lee and Ramachandra do not explicitly, but Johnson discloses: meta data ([0022] Techniques described herein improve the efficiency of dialog processing tasks by using historical dialog data stored in association with different context levels for different users. Embodiments enable access to historical queries including associated contexts, logical forms, execution results, date and time, and other metadata.)
Johnson also discloses: past behavior ([0022] Techniques described herein improve the efficiency of dialog processing tasks by using historical dialog data stored in association with different context levels for different users. Embodiments enable access to historical queries including associated contexts, logical forms, execution results, date and time, and other metadata.)
Lee, Ramachandra and Johnson are considered analogous art.  Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to combine the teachings of Lee and Ramachandra.  As disclosed in Johnson, one of ordinary skill would have been motivated to do so in order to provide “techniques are described for using data stored for a user in association with context levels to improve the efficiency and accuracy of dialog processing tasks” e.g., improve interaction with dialogue assistant (Abstract).

Claim 7-8, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Firdaus, and further in view of Ramachandra.

Regarding claim 7, Lee discloses: A system for determining one or more missing slots associated with a voice command for an advanced voice interaction, the system comprising: a memory storing at least one program; and at least one processor coupled to the memory, wherein the at least one program is configured to be executed by the at least one processor, the at least one program including instructions for: (See fig 2 for the system with processor and memory)
Lee also discloses: a deep learning-model ([0092] The controller 170 may include an ANN, such as a deep neural network (DNN) including a CNN, an RNN, a DBN, and so forth, and may train the DNN. As a machine learning method for such an artificial neural network, both unsupervised learning and supervised learning may be used. The controller 170, after learning according to the setting, may control such that a speech tone recognition artificial neural network structure is updated.)
	Although Lee discloses deep learning model, it does not explicitly, but Firdaus discloses: a joint multi-tasking deep learning model (see fig. 2 for the joint multi-task deep learning model)
Lee and Firdaus are considered analogous art.  Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to combine the teachings of Lee and Firdaus.  As disclosed in Firdaus, one of ordinary skill would have been motivated to use their model because it “outperforms the state-of-the-art approaches for the SLU tasks.” e.g., improve interaction with dialogue assistant (Abstract).
As for the rest of the claim, they recite the elements of claim 1, therefore the rationale applied in rejection of claim 1 is equally applicable.

Regarding claim 8, although in different statutory category, but it recites the elements of method of claim 2 as a system, therefore the rationale applied in the rejection of claim 2 is equally applicable to claim 8.

Regarding claim 11, although in different statutory category, but it recites the elements of method of claim 5 as a system, therefore the rationale applied in the rejection of claim 5 is equally applicable to claim 11.

Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Firdaus, further in view of Ramachandra, and furthermore in view of Johnson (US 20210082414 A1), hereinafter referenced as Johnson.
Regarding claim 12, although in different statutory category, but it recites the elements of method of claim 6 as a system, therefore the rationale applied in the rejection of claim 6 is equally applicable to claim 12.

Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Thota US 20120272225 – discloses “The computer system optimizes the generated list of actions by grouping actions that are performable together in the same group, and sorts the grouped actions according to a processing order that respects existing constraints between the entities. The computer system also generates a domain-specific executable function that, when executed, upgrades the entities of the first instance to the second instance according to the entities' groupings and sorted processing order.” See para 0013 and figs 3-4 for additional details.
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/PHILIP H LAM/            Examiner, Art Unit 2656