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 action is responsive to the application filed 09/05/2024. Claims 1-20 are presented for examination.
Priority
Applicant’s claim for the benefit of prior filed application KR10-2023-0166765, filed 11/27/2023, is acknowledged.
Information Disclosure Statement
The information disclosure statement (IDS) submitted 09/05/2024 has been considered by the examiner.
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 therefore, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Step 1: The claim recites “A method of performing a context awareness and a response based on a multi-turn dialogue, the method comprising:”; therefore, it is directed to the statutory category of a process.
Step 2A Prong 1: The claim recites, inter alia:
performing prediction on a context awareness based on a multi-turn dialogue: These limitations recite a mentally performable process with the aid of pen and paper of using observation, judgement, and evaluation to perform a prediction on a context awareness based on a multi-turn dialogue.
calculating an uncertainty value for the prediction: These limitations recite mathematical calculations similar to an act of calculating using mathematical methods to determine a variable or number per MPEP 2106.04(a)(2)(I)(C).
and providing a response to a user within the multi-turn dialogue, based on a result of the prediction and the uncertainty value: These limitations recite methods of organizing human activity similar to communicating a notification to the user via a device or providing information to a person without interfering with the person’s primary activity per MPEP 2106.04(a)(2)(II)(C).
Thus, the claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
through an artificial intelligence (AI) model: These additional elements are recited at a high level of generality and amount to invoking computers or other machinery merely as a tool to apply the underlying judicial exception. See MPEP § 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking generic computer components to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 2
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 1.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein the uncertainty value includes at least one of a first uncertainty value whose value increases in a case of a dialogue in which topics of respondable context candidates are mixed, or a second uncertainty value whose value increases in a case of a dialogue in which topics are outside respondable context candidates: These additional elements are recited at a high level of generality and merely indicate a field of use or technological environment in which to apply a judicial exception, e.g. the uncertainty value, to a particular technological environment or field of use, e.g. includes at least one of a first uncertainty value whose value increases in a case of a dialogue in which topics of respondable context candidates are mixed, or a second uncertainty value whose value increases in a case of a dialogue in which topics are outside respondable context candidates. See MPEP 2106.05(h). Elements that use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include generally linking the use of the judicial exception to indicate a field of use or technological environment. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 3
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 2.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein, if the first uncertainty value is greater than a pre-configured criterion, the response corresponds to a feedback response for collecting additional information: These additional elements are recited at a high level of generality and merely indicate a field of use or technological environment in which to apply a judicial exception, e.g. if the first uncertainty value is greater than a pre-configured criterion, the response, to a particular technological environment or field of use, e.g. corresponds to a feedback response for collecting additional information. See MPEP 2106.05(h). Elements that use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include generally linking the use of the judicial exception to indicate a field of use or technological environment. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 4
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 2.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein, if the second uncertainty value is greater than a pre-configured criterion, the response corresponds to a feedback response for collecting additional information: These additional elements are recited at a high level of generality and merely indicate a field of use or technological environment in which to apply a judicial exception, e.g. if the second uncertainty value is greater than a pre-configured criterion, the response, to a particular technological environment or field of use, e.g. corresponds to a feedback response to convey to the user that the response corresponds to a context in which it is impossible to respond. See MPEP 2106.05(h). Elements that use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include generally linking the use of the judicial exception to indicate a field of use or technological environment. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 5
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 2.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein, if the first uncertainty value and the second uncertainty value are less than a pre-configured criterion, the provision of the response is performed using a database in which context-dependent responses are stored or a generative language model in which context-dependent responses are trained: These additional elements are recited at a high level of generality and merely indicate a field of use or technological environment in which to apply a judicial exception, e.g. if the first uncertainty value and the second uncertainty value are less than a pre-configured criterion, the provision of the response, to a particular technological environment or field of use, e.g. is performed using a database in which context-dependent responses are stored or a generative language model in which context-dependent responses are trained. See MPEP 2106.05(h). Elements that use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include generally linking the use of the judicial exception to indicate a field of use or technological environment. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 6
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 1.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein the response is based on one or more of a sentence generation function or a text-to-speech (TTS) function: These additional elements are recited at a high level of generality and merely indicate a field of use or technological environment in which to apply a judicial exception, e.g. the response, to a particular technological environment or field of use, e.g. is based on one or more of a sentence generation function or a text-to-speech (TTS) function. See MPEP 2106.05(h). Elements that use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include generally linking the use of the judicial exception to indicate a field of use or technological environment. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 7
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 1.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein the AI model corresponds to a model trained to perform the prediction on the context awareness based on prediction of an evidence vector: These additional elements recite only the idea of an AI model trained to perform a context awareness prediction based on an evidence vector and attempts to cover any implementation of trained AI models without any restriction as to the specific type of training used on the AI model or how the AI model is trained, or specifically how the evidence vector is used by the AI model to perform a prediction. These additional elements do not meaningfully limit the claim and does not integrate the judicial exception into a practical application because this type of recitation is equivalent to the words “apply it”. See MPEP 2106.05(f). Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include adding words equivalent to "apply it" with the judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 8
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas as the judicial exception of claim 7.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of the claim are as follows:
wherein the evidence vector is produced based on 1) a result of applying dialogue augmentation and a pre-trained natural language model to the multi-turn dialogue and 2) an extra feature extracted from extra information other than the multi-turn dialogue: These additional elements are recited at a high level of generality and merely indicate a field of use or technological environment in which to apply a judicial exception, e.g. the evidence vector, to a particular technological environment or field of use, e.g. is produced based on 1) a result of applying dialogue augmentation and a pre-trained natural language model to the multi-turn dialogue and 2) an extra feature extracted from extra information other than the multi-turn dialogue. See MPEP 2106.05(h). Elements that use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Thus, the way in which the additional elements use or interact with the judicial exception do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include generally linking the use of the judicial exception to indicate a field of use or technological environment. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP § 2106.05.
Claim 9
Step 1: A process, as above.
Step 2A Prong 1: The claim recites the abstract ideas of claim 7 as well as, inter alia:
wherein the AI model is trained using a loss function such as a following Equation,
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and wherein, in the Equation, f represents a model, θ represents a model parameter, x represents an input, y represents an actual value, and B represents a beta distribution: These limitations recite mathematical calculations similar to calculating a number representing an alarm limit value using the mathematical formula per MPEP 2106.04(a)(2)(I)(C)(ii).
Thus, the claim recites a judicial exception.
Step 2A Prong 2 & Step 2B: There are no additional elements recited so the claim does not provide a
practical application and is not considered to be significantly more. As such, the claim is patent
ineligible.
Claims 10-18
Step 1: These claims are directed to “An apparatus of performing a context awareness and a response based on a multi-turn dialogue, the apparatus comprising:”; therefore, it is directed the statutory category of a process.
Step 2A Prong 1: Claims 10-18 recite the same judicial exception as Claims 1-9, respectively.
Step 2A Prong 2: The judicial exception recited in these claims are not integrated into a practical application. The analysis at this step for Claims 10-18 mirrors that of Claims 1-9, respectively.
Step 2B: The additional elements from Step 2A Prong 2 do not contain significantly more than the judicial exception for these claims. The analysis at this step for Claims 10-18 mirrors that of Claims 1-9, respectively.
Claims 19-20
Step 1: This claim recites "A non-transitory computer readable medium storing one or more instructions, wherein the one or more instructions are executed by one or more processors and control an apparatus for performing a context awareness and a response based on a multi-turn dialogue to:"; therefore, it is directed to the statutory category of an article of manufacture.
Step 2A Prong 1: Claims 19-20 recite the same judicial exception as Claims 1-2, respectively.
Step 2A Prong 2: The judicial exception recited in these claims are not integrated into a practical application. The only difference between Claims 19-20 and Claims 1-2, is that Claims 19-20 are directed to "A non-transitory computer readable medium storing one or more instructions, wherein the one or more instructions are executed by one or more processors and control an apparatus for performing a context awareness and a response based on a multi-turn dialogue to”. However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a non-transitory computer readable medium storing one or more instructions, wherein the one or more instructions are executed by one or more processors and control an apparatus for performing a context awareness and a response based on a multi-turn dialogue to, cannot meaningfully integrate the judicial exception into a practical application. See MPEP 2106.05(f). With that exception, the analysis at this step for Claims 19-20 mirrors that of Claims 1-2, respectively.
Step 2B: The additional elements from Step 2A Prong 2 do not contain significantly more than the judicial exception for these claims. The only difference between Claims 19-20 and Claims 1-2, is that Claims 19-20 are directed to "A non-transitory computer readable medium storing one or more instructions, wherein the one or more instructions are executed by one or more processors and control an apparatus for performing a context awareness and a response based on a multi-turn dialogue to”. However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a non-transitory computer readable medium storing one or more instructions, wherein the one or more instructions are executed by one or more processors and control an apparatus for performing a context awareness and a response based on a multi-turn dialogue to, cannot amount to significantly more than the judicial exception. See MPEP 2106.05(f). With that exception, the analysis at this step for Claims 19-20 mirrors that of Claims 1-2, respectively.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 10, & 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tonetti et al. (US 11170770 B2, published 11/09/2021), hereafter Tonetti.
Regarding independent claim 1, Tonetti teaches a method comprising:
performing prediction on a context awareness based on a multi-turn dialogue, through an artificial intelligence (AI) model ([Col. 6, Lines 46-51 & Fig. 2-4] discusses performing context awareness based on the dialogue of the user through an automatic classification system);
calculating an uncertainty value for the prediction through the AI model ([Col. 6, Lines 51-54 & Fig. 2-4] discusses the AI model calculating a confidence value for the prediction);
and providing a response to a user within the multi-turn dialogue, based on a result of the prediction and the uncertainty value ([Col. 2, Lines 56-62 & Fig. 2-4] discusses if the uncertainty is above a threshold, providing a response to the user based on the prediction).
Regarding claim 10, claim 10 is a system claim that is substantially the same as the method of claim 1. Therefore, claim 10 is rejected for the same reasons as claim 1.
Regarding claim 19, claim 19 is a computer-readable storage medium claim that is substantially the same as the method of claim 1. Therefore, claim 19 is rejected for the same reasons as claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2-4, 11-13, & 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tonetti, as applied in claims 1, 10, & 19, and in view of Hu et al. ("Multidimensional Uncertainty-Aware Evidential Neural Networks", UT Dallas, arXiv) (Year: 2021), hereafter Hu.
Regarding dependent claim 2, Tonetti teaches the claimed invention as claimed in claim 1, including the use of uncertainty values compared to a confidence and disambiguous threshold ([Col. 3, Lines 16-22] discusses a confidence and disambiguation threshold set to be compared to an uncertainty value).
Tonetti does not explicitly teach wherein the uncertainty value includes at least one of a first uncertainty value whose value increases in a case of a dialogue in which topics of respondable context candidates are mixed, or a second uncertainty value whose value increases in a case of a dialogue in which topics are outside respondable context candidates.
However, in a similar field of endeavor, Hu teaches a method for prediction using uncertainty wherein one of the uncertainty values increases when a dialogue has mixed context candidates ([Pg. 3] discusses increasing an uncertainty value when topics of context candidates are mixed, causing a higher dissonance).
Because Tonetti teaches the use of uncertainty values; and Hu teaches an uncertainty value that increases when a dialogue has mixed context candidates, accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate an uncertainty value that increases when a dialogue has mixed context candidates as taught by Hu into Tonetti’s method, with a reasonable expectation of success, to teach wherein the uncertainty value includes at least one of a first uncertainty value whose value increases in a case of a dialogue in which topics of respondable context candidates are mixed, or a second uncertainty value whose value increases in a case of a dialogue in which topics are outside respondable context candidates. This combination would have been motivated by the desire to improve confidence by identifying out of scope samples (Hu [Pg. 2]).
Regarding dependent claim 3, the combination of Tonetti and Hu teaches the claimed invention as claimed in claim 2, including wherein, if the first uncertainty value is greater than a pre-configured criterion, the response corresponds to a feedback response for collecting additional information (Tonetti [Col. 5, Lines 30-38] discusses sending a feedback response to collect additional information if the uncertainty value is greater than a criterion threshold).
Regarding dependent claim 4, the combination of Tonetti and Hu teaches the claimed invention as claimed in claim 2, including wherein, if the second uncertainty value is greater than a pre-configured criterion, the response corresponds to a feedback response to convey to the user that the response corresponds to a context in which it is impossible to respond (Tonetti [Col. 6, Lines 14-24] discusses sending a feedback response conveying a context is impossible to respond to, given the uncertainty value is greater than a criterion threshold).
Regarding claims 11-13, claims 11-13 are system claims that are substantially the same as the method of claims 2-4, respectively. Therefore, claims 11-13 are rejected for the same reasons as claims 2-4, respectively.
Regarding claim 20, claim 20 is a computer-readable storage medium claim that is substantially the same as the method of claim 2. Therefore, claim 20 is rejected for the same reasons as claim 2.
Claims 5 & 14 are rejected under 35 U.S.C. 103 as being unpatentable over Tonetti, in view of Hu, as applied in claims 2 & 11, and further in view of DiMascio et al. (US 11164562 B2, published 11/02/2021), hereafter DiMascio.
Regarding dependent claim 5, the combination of Tonetti and Hu teaches the claimed invention as claimed in claim 2, including wherein, if the first uncertainty value and the second uncertainty value are less than a pre-configured criterion, the provision of the response is performed (Tonetti [Col. 6, Lines 14-24] discusses generating a response from a dialogue manager when the confidence and disambiguity values meet a pre-configured criterion).
The combination of Tonetti and Hu does not explicitly teach the provision of the response is performed using a database in which context-dependent responses are stored or a generative language model in which context-dependent responses are trained.
However, in a similar field of endeavor, DiMascio teaches a method for clarification in conversation services wherein responses used are stored in a database ([Col. 4, Lines 11-29] discusses storing information in a database that can be used for context-dependent responses).
Because the combination of Tonetti and Hu teaches provisioning a response when both uncertainty conditions are met; and DiMascio teaches provisioning a response using a database in which responses and information is stored, accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate provisioning a response using a database in which responses and information is stored as taught by DiMascio into the combination of Tonetti and Hu’s method, with a reasonable expectation of success, to teach wherein, if the first uncertainty value and the second uncertainty value are less than a pre-configured criterion, the provision of the response is performed using a database in which context-dependent responses are stored or a generative language model in which context-dependent responses are trained. This combination would have been motivated by the desire to expand the model’s ability to respond to a wide range of topics, due to storing information in a repository and using it to respond to utterances (DiMascio [Col. 4]).
Regarding claim 14, claim 14 is a system claim that is substantially the same as the method of claim 5. Therefore, claim 14 is rejected for the same reasons as claim 5.
Claims 6 & 15 are rejected under 35 U.S.C. 103 as being unpatentable over Tonetti, as applied in claims 1 & 10, and in view of DiMascio et al. (US 11164562 B2, published 11/02/2021), hereafter DiMascio.
Regarding dependent claim 6, Tonetti teaches the claimed invention as claimed in claim 1, including providing a response to a user within the multi-turn dialogue, based on a result of the prediction and the uncertainty value ([Col. 2, Lines 56-62 & Fig. 2-4] discusses if the uncertainty is above a threshold, providing a response to the user based on the prediction).
Tonetti does not explicitly teach wherein the response is based on one or more of a sentence generation function or a text-to-speech (TTS) function.
However, in a similar field of endeavor, DiMascio teaches a method for clarification in conversation services wherein responses are based on a sentence generation function and TTS function ([Col. 5, Lines 1-13] discusses generating a response using a text generation module and a speech synthesis modules; thus, a sentence generation function and TTS function).
Because Tonetti teaches providing a response; and DiMascio teaches providing responses based on a sentence generation function or a TTS function, accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate providing responses based on a sentence generation function or a TTS function as taught by DiMascio into Tonetti’s method, with a reasonable expectation of success, to teach wherein the response is based on one or more of a sentence generation function or a text-to-speech (TTS) function. This combination would have been motivated by the desire to implement the model into a conversational form using speech generation (DiMascio [Abstract & Background]).
Regarding claim 15, claim 15 is a system claim that is substantially the same as the method of claim 6. Therefore, claim 15 is rejected for the same reasons as claim 6.
Claims 7, 9, 16, & 18 are rejected under 35 U.S.C. 103 as being unpatentable over Tonetti, as applied in claims 1 & 10, and in view of Sensoy et al. ("Evidential Deep Learning to Quantify Classification Uncertainty", 32nd Conference on Neural Information Processing Systems, NeurIPS) (Year: 2018), hereafter Sensoy.
Regarding dependent claim 7, Tonetti teaches the claimed invention as claimed in claim 1, including performing prediction on a context awareness based on a multi-turn dialogue, through an artificial intelligence (AI) model ([Col. 6, Lines 46-51 & Fig. 2-4] discusses performing context awareness based on the dialogue of the user through an automatic classification system).
Tonetti does not explicitly teach wherein the AI model corresponds to a model trained to perform the prediction on the context awareness based on prediction of an evidence vector.
However, in a similar field of endeavor, Sensoy teaches a method for evidential deep learning in which a prediction is based on an evidence vector ([Abstract] discusses computing a continuous output as an evidence vector, mapped to Dirichlet parameters to perform predictions on context awareness).
Because Tonetti teaches performing prediction on a context awareness; and Sensoy teaches computing an evidence vector to be used in a prediction, accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate computing an evidence vector to be used in a prediction as taught by Sensoy into Tonetti’s method, with a reasonable expectation of success, to teach wherein the AI model corresponds to a model trained to perform the prediction on the context awareness based on prediction of an evidence vector. This combination would have been motivated by the desire to achieve improved uncertainty estimation and success on detection of out-of-distribution queries and endurance against adversarial perturbations (Sensoy [Abstract]).
Regarding dependent claim 9, the combination of Tonetti and Sensoy teaches the claimed invention as claimed in claim 7, including wherein the AI model is trained using a loss function such as a following Equation
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wherein, in the Equation, f represents a model, θ represents a model parameter, x represents an input, y represents an actual value, and B represents a beta distribution (Sensoy [Pg. 5 & Eq. 4-5] discusses training the AI model using the loss function recited in claim 9).
Regarding claims 16 & 18, claims 16 & 18 are system claims that are substantially the same as the method of claims 7 & 9, respectively. Therefore, claims 16 & 18 are rejected for the same reasons as claims 7 & 9, respectively.
Claims 8 & 17 are rejected under 35 U.S.C. 103 as being unpatentable over Tonetti, in view of Sensoy, as applied in claims 7 & 16, and further in view of Chen et al. ("GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation", ASAPP, arXiv) (Year: 2021), hereafter Chen.
Regarding dependent claim 8, the combination of Tonetti and Sensoy teaches the claimed invention as claimed in claim 7, including generating an evidence vector (Sensoy [Abstract] discusses computing a continuous output as an evidence vector, mapped to Dirichlet parameters to perform predictions on context awareness).
The combination of Tonetti and Sensoy does not explicitly teach wherein the evidence vector is produced based on 1) a result of applying dialogue augmentation and a pre-trained natural language model to the multi-turn dialogue and 2) an extra feature extracted from extra information other than the multi-turn dialogue.
However, in a similar field of endeavor, Chen teaches a method for training dialogue predictions wherein an evidence vector is produced by dialogue augmentation applied with a natural language model, and extra features are extracted ([Abstract] discusses performing data augmentation by applying a natural language model to train and produce an out of scope detector, which acts as an evidence vector for the method; this process is also done by extracting samples from an auxiliary dataset, which is extra information other than the multi-turn dialogue).
Because the combination of Tonetti and Sensoy teaches generating an evidence vector; and Chen teaches an evidence vector is produced by dialogue augmentation applied with a natural language model, and extra features are extracted, accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate an evidence vector produced by dialogue augmentation applied with a natural language model, and extra features are extracted as taught by Chen into the combination of Tonetti and Sensoy’s method, with a reasonable expectation of success, to teach wherein the evidence vector is produced based on 1) a result of applying dialogue augmentation and a pre-trained natural language model to the multi-turn dialogue and 2) an extra feature extracted from extra information other than the multi-turn dialogue. This combination would have been motivated by the desire to train a model by augmenting existing data to train better OOS detectors operating in low-data regimes (Chen [Abstract]).
Regarding claim 17, claim 17 is a system claim that is substantially the same as the method of claim 8. Therefore, claim 17 is rejected for the same reasons as claim 8.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
DiMascio et al. (US 2020/0227025 A1, published 07/16/2020) ([Abstract] A system for entity-level clarification in conversation services includes a memory having instructions therein. The system also includes at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to receive a conversation services training example set, build an entity usage map using the conversation services training example set, receive a user utterance, and, responsive to a reception of the user utterance, generate a clarification response using the entity usage map. The at least one processor is also configured to execute the instructions to provide the clarification response to a user).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RILEY S ACOSTA whose telephone number is (571)272-8714. The examiner can normally be reached Monday-Thursday 6am-4pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer N Welch can be reached at (571)272-7212. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RILEY S ACOSTA/Examiner, Art Unit 2143
/JENNIFER N WELCH/Supervisory Patent Examiner, Art Unit 2143
