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 .
DETAILED ACTION
Status of Claims
This action is a first action on the merits in response to the application filed on 05/14/2025.
Claims 1 – 20 are currently pending and have been examined in this application.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112, (b)/second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Claim 1 recites, “the customer” at line 9. The phrase has not been previously introduced. There is insufficient antecedent basis for this limitation in the claim. Claims 16 and 20 are rejected under the same rationale. Claims 2-15 and 17-19 are rejected based on their dependency on Claims 1 and 16 respectively.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recites:
receiving audio data for at least a portion of a call between a call center representative and a call center user;
generating an audio-to-text transcription of the call upon processing the audio data; and
applying at least one generative model to the transcription to obtain: a text summary of the call;
answers to pre-defined questions relating to the customer and/or the call; and
at least one assessment score of the call.
The limitation under its broadest reasonable interpretation covers Certain Methods of Organizing Human Activities related to managing personal behavior or relationships or interactions between people, but for the recitation of generic computer components (e.g. a processor and memory). For example, receiving audio data of a call, generating audio to text transcription of the call, applying a generative model to transcript to obtain a text summary (answers to questions and score) involve managing interactions between people.. Accordingly, the claim recites an abstract idea of Certain Methods of Organizing Human Activity.
In addition, the claim could be seen as Mental Processes related to observation and evaluation of data.
Independent Claims 16 and 20 substantially recite the subject matter of Claim 1 and also include the abstract ideas identified above. The dependent claims encompass the same abstract ideas. For instance, Claim 2 is directed to applying a generative model to the transcript by providing pre-defined questions; Claim 3 is directed providing transcript to the generative model to generate text summary and answers; Claims 4 and 18 are directed to the generative model is used to generate text summary, answers and score; Claim 5 is directed to an LLM; Claim 6 and 19 are directed to output is applied as input to generative model; Claim 7 is directed to generating a signal to trigger remedial action; Claim 8 is directed to generating electronic signal during call in progress; Claim 9 is directed to remedial action includes prompting the call center rep; Claim 10 is directed to remedial action includes routing the call to another person; Claim 11 is directed to generating audio to text transcription; Claim 12 is directed to generating time stamp metadata for transcription; Claims 13 and 14 are directed to assessment score ; Claim 15 is directed to assessment score includes a lead score, financial readiness score and interest level score and Claim 17 is directed to interconnected plurality of call center.
The judicial exceptions are not integrated into a practical application. Claim 16 recites the additional elements of a processing subsystem that includes one or more processors and more or more memories. These are generic computer components recited at a high level of generality as performing generic computer functions (Spec see Figure 8 and ¶0138-¶0140).
For instance, the steps of receiving audio data for at least a portion of a call between a call center rep and a call center user is data gathering activity. The steps of generating an audio to text transcription of the call; applying generative AI model to obtain text summary of call, answers to predefined questions and assessment score involve analyzing data (collecting and analyzing data). The use of utilizing generative AI is seen as generically ‘apply it’ to the collected data.
Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer components (e.g. a processor). The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer components (e.g. a processor). The additional elements do not integrate the abstract ideas into a practical application because it does not impose meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As stated above, the additional elements of a processor and a memory are considered generic computer components performing generic computer functions that amount to no more than instructions to implement the judicial exception. Mere, instructions to apply an exception using generic computer components cannot provide an inventive concept.
The dependent claims when analyzed both individually and in combination are also held to be ineligible for the same reason above and the additional recited limitations fail to establish that the claims are not directed to an abstract. The additional limitations of the dependent claims when considered individually and as an ordered combination do not amount to significantly more than the abstract idea.
Looking at these limitations as an ordered combination and individually adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, to "apply" the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Therefore, Claims 1-20 are not patent eligible.
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-5, 14, 16, 18 and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Dempsey et al. (US 12113934).
Claim 1:
Dempsey discloses:
A computer-implemented method for natural language processing for a call center, the method comprising: receiving audio data for at least a portion of a call between a call center representative and a call center user; (see at least column 5, lines 21-28, speech transcription module converts the recorded speech into digitized text-based transcripts; see also Abstract)
generating an audio-to-text transcription of the call upon processing the audio data; and (see at least column 5, lines 21-28, speech transcription module converts the recorded speech into digitized text-based transcripts; see also column 1, lines 41-45)
applying at least one generative model to the transcription to obtain: a text summary of the call; (see at least column 7, lines 20-30, utilize LLM to generate a summary of the call transcript)
answers to pre-defined questions relating to the customer and/or the call; and (see at least column 6, lines 42-55, predefined questions are conditional questions that requires a yes or no answer)
at least one assessment score of the call. (see at least Abstract, scores represent degree of satisfaction; see also column 1, lines 50-60, inputting predefined questions and the transcript into a trained LLM to obtain scores for questions indicating satisfaction performance)
Claim 2:
Dempsey discloses claim 1. Dempsey further discloses:
wherein said applying at least one generative model to the transcription includes: providing the pre-defined questions to the at least one generative model. (see at least Abstract, scores represent degree of satisfaction; see also column 1, lines 50-60, inputting predefined questions and the transcript into a trained LLM to obtain scores for questions indicating satisfaction performance; see also column 6)
Claim 3:
Dempsey discloses claim 1. Dempsey further discloses:
wherein said applying at least one generative model to the transcription includes: providing the transcript to the at least one generative model to generate the text summary and the answers; and (see at least column 7, lines 20-25, utilize LLM to generate a summary of the call transcript; see also column 7, lines 21-30)
providing at least one of the text summary and the answers to the at least one generative model to generate the at least one assessment score. (see at least column 7, lines 21-30, LLM to predict answers to questions; see also column 6, lines, 43-46, AI score module assigns a score to each yes and no answers)
Claim 4:
Dempsey discloses claim 2. Dempsey further discloses:
wherein the same generative model is used to generate the text summary, the answers, and the at least one assessment score. (see at least column 3, lines 15-19, summary of call generated by LLM and generating scores for predefined questions; see also see also column 6, lines, 43-46, AI score module assigns a score to each yes and no answers; column 6, lines 18-42)
Claim 5:
Dempsey discloses claim 1. Dempsey further discloses:
wherein said at least one generative model includes a large language model. (see at least column 1, lines 53-55, LLM)
Claim 14:
Dempsey discloses claim 1. Dempsey further discloses:
wherein the at least one assessment score includes a plurality of assessment scores. (see at least column 6, lines 64-67- column 7, lines 1-2, calculate an overall score for the call agent)
Claim 16:
Dempsey discloses:
A computer-implemented system for natural language processing for a call center, the system comprising: (see at least column 5, lines 21-28, speech transcription module converts the recorded speech into digitized text-based transcripts; see also Abstract)
a processing subsystem that includes one or more processors and one or more memories coupled with the one or more processors, the processing subsystem configured to cause the system to: (see at least Figure 1 and associated text;
receive audio data for at least a portion of a call between a call center representative and a call center user; (see at least column 5, lines 21-28, speech transcription module converts the recorded speech into digitized text-based transcripts; see also Abstract)
generate an audio-to-text transcription of the call upon processing the audio data; (see at least column 5, lines 21-28, speech transcription module converts the recorded speech into digitized text-based transcripts; see also Abstract)
apply at least one generative artificial intelligence model to the transcription to obtain: a text summary of the call; (see at least column 7, lines 20-30, utilize LLM to generate a summary of the call transcript)
answers to pre-defined questions relating to the customer and/or the call; and (see at least column 6, lines 42-55, predefined questions are conditional questions that requires a yes or no answer)
at least one assessment score of the call. (see at least Abstract, scores represent degree of satisfaction; see also column 1, lines 50-60, inputting predefined questions and the transcript into a trained LLM to obtain scores for questions indicating satisfaction performance)
Claim 18:
Dempsey discloses claim 16. Dempsey further discloses:
wherein the same generative model is used to generate the text summary, the answers, and the at least one assessment score. (see at least column 3, lines 15-19, summary of call generated by LLM and generating scores for pre-defined questions; see also see also column 6, lines, 43-46, AI score module assigns a score to each yes and no answers; column 6, lines 18-42)
Claim 20:
Dempsey discloses:
A non-transitory computer-readable medium or media having stored thereon machine interpretable instructions which, when executed by a processing system, cause the processing system to perform a method for natural language processing for a call center, the method comprising: receiving audio data for at least a portion of a call between a call center representative and a call center user; (see at least column 5, lines 21-28, speech transcription module converts the recorded speech into digitized text-based transcripts; see also Abstract ;see also Figure 1 and associated text)
generating an audio-to-text transcription of the call upon processing the audio data; and(see at least column 5, lines 21-28, speech transcription module converts the recorded speech into digitized text-based transcripts; see also column 1, lines 41-45)
applying at least one generative model to the transcription to obtain: a text summary of the call; (see at least column 7, lines 20-30, utilize LLM to generate a summary of the call transcript)
answers to pre-defined questions relating to the customer and/or the call; and(see at least column 6, lines 42-55, predefined questions are conditional questions that requires a yes or no answer)
at least one assessment score of the call. (see at least Abstract, scores represent degree of satisfaction; see also column 1, lines 50-60, inputting predefined questions and the transcript into a trained LLM to obtain scores for questions indicating satisfaction performance)
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 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 6 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Dempsey et al. (US 12113934) further in view of Noor et al. (US 2025/0292262).
Claim 6:
While Dempsey discloses claim 1, Dempsey does not explicitly disclose the following limitation; however, Noor does disclose:
wherein an output of the at least one generative model is applied as an input to the at least one generative model in subsequent processing (see at least ¶0051, neural networks, can have multiple layers of intermediate nodes with different configurations, can be a combination of models that receive different parts of the input and/or input from other parts of the deep neural network , or are convolutions-partially using output from previous iterations of applying the model as further input to produce results for the current input.)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the generating text summaries using LLM of Dempsey with the neural network of Noor since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the neural network for document summaries of the secondary reference for the LLM generating text summaries of the primary reference.
Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious. Claim 19 for a system substantially recites the subject matter of Claim 6 for a method and is rejected based on the same rationale.
Claims 7-11 are rejected under 35 U.S.C. 103 as being unpatentable over Dempsey et al. (US 12113934) further in view of Can (US 2024/0073321).
Claim 7:
While Dempsey discloses claim 1, Dempsey does not explicitly disclose the following limitation; however, Can does disclose:
further comprising: upon said applying, generating an electronic signal to trigger remedial action. (see at least ¶0022, alerting a call agent in real time for a possible complaint; see also ¶0043, the system provides real-time support to call agents in the form of alerts or current call dialog suggestions; see also ¶0156)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the performance evaluation of a customer calls that are transcribed to text of Dempsey with the automated call center assistance system for alerting agents and re-routing calls of Can to assist in providing customers with a positive experience and address issues quickly (see ¶0018).
Claim 8:
While Dempsey discloses claim 7, Dempsey does not explicitly disclose the following limitation; however, Can does disclose:
wherein said generating said electronic signal is during a call in progress. (see at least ¶0043, the system provides real-time support to call agents in the form of alerts or current call dialogue suggestions; see also ¶0156, triggering alerts based on categories and agent may select alert and receive suggested actions)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the performance evaluation of a customer calls that are transcribed to text of Dempsey with the automated call center assistance system for alerting agents, providing suggestions and re-routing calls of Can to assist in providing customers with a positive experience and address issues quickly (see ¶0018).
Claim 9:
While Dempsey and Can disclose claim 7, Dempsey does not explicitly disclose the following limitation; however, Can does disclose:
wherein said remedial action includes prompting the call center representative to follow a particular script portion. (see at least ¶0025, suggest phrases that agent can use during the current call; see also ¶0043, call dialogue suggestions (e.g. phrases)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the performance evaluation of a customer calls that are transcribed to text of Dempsey with the automated call center assistance system for alerting agents, providing suggestions and re-routing calls of Can to assist in providing customers with a positive experience and address issues quickly (see ¶0018).
Claim 10:
While Dempsey and Can disclose claim 7, Dempsey does not explicitly disclose the following limitation; however, Can does disclose:
wherein said remedial action includes routing the call to another person. (see at least ¶0022, routing calls based on customer issue; see also ¶0038, providing future call routing to the call agent or manager; see also ¶0043)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the performance evaluation of a customer calls that are transcribed to text of Dempsey with the automated call center assistance system for alerting agents, providing suggestions and re-routing calls of Can to assist in providing customers with a positive experience and address issues quickly (see ¶0018).
Claim 11:
While Dempsey and Can disclose claim 1, Dempsey does not explicitly disclose the following limitation; however, Can does disclose:
wherein said generating the audio-to-text transcription includes generating speaker attribution metadata. (see at least ¶0039, customer profile may contain both metadata related to the customer collected in an offline manner and by various predictive models which are iteratively updated as call proceeds)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the performance evaluation of a customer calls that are transcribed to text of Dempsey with the customer metadata of Can to provide customer aggregated data to determine trends scores over time (see ¶0039)
Claims 12 are rejected under 35 U.S.C. 103 as being unpatentable over Dempsey et al. (US 12113934) further in view of Martinsen et al. (US 2024/0020463).
Claim 12:
While Dempsey discloses claim 1, Dempsey does not explicitly disclose claim 1 the following limitation; however, Martinsen does disclose:
wherein said generating the audio-to-text transcription includes generating time stamp metadata. (see at least ¶0016, each transcribed audio may be associated with speaker identifier, a time stamp and/or other metadata)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine converting of audio recordings of a call to text based transcript of Dempsey with the timestamp metadata for audio recordings of Martinsen since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claims 13 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Dempsey et al. (US 12113934) further in view of Fink (US 2021/0304107).
Claim 13:
While Dempsey discloses claim 1, Dempsey further discloses a call center (see Figure 3 and associated text, an environment with multiple agents), Dempsey does not explicitly disclose the following limitation; however, Fink does disclose:
wherein the at least one assessment score is indicative of a quality of a business opportunity associated with the call center user. (see at least ¶0140 call center; see also ¶0023, employee performance metrics are connected to desired outcome such as successful sale, resolving customer complaint or upselling; see also ¶0041)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the call assessment of Dempsey with the employee performance metrics related to a desired outcome of Fink in order to monitor employee performance and the effectiveness of scripts utilized (see Spec ¶0023).
Claim 15:
While Dempsey discloses claim 1, Dempsey further discloses a call center (see Figure 3 and associated text, an environment with multiple agents), Dempsey does not explicitly disclose the following limitation; however, Fink does disclose:
wherein the at least one assessment score includes at least one of a lead score, a financial readiness score, and an interest level score. (see at least ¶0140 call center; see also ¶0023, employee performance metrics are connected to desired outcome such as successful sale, resolving customer complaint or upselling; see also ¶0041)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the call assessment of Dempsey with the employee performance metrics related to a desired outcome of Fink in order to monitor employee performance and the effectiveness of scripts utilized (see Spec ¶0023).
Claims 17 are rejected under 35 U.S.C. 103 as being unpatentable over Dempsey et al. (US 12113934) further in view of Petropoulos et al. (US 11671535).
Claim 17:
While Dempsey discloses claim 16, Dempsey does not explicitly disclose the following limitation; however, Petropoulos does disclose:
wherein the system is interconnected by way of a network with a plurality of call centers, and said audio data are among data received by way of the network from said plurality of call centers. (see at least column 10, lines 1-12, receiving data from multiple call centers)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the call agent evaluation system of Dempsey with receiving customer related call center data for one or more call centers through call center networks since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
The prior art made of record and not relied upon is considered relevant but not applied:
Britt et al. (US 2024/0144089) discloses interaction summarization system generates a transcript from an interaction including written text and audio speech attributed to participant interaction and generates an interaction summary.
Churgin et al. (US 2024/0371367) discloses processing call transcripts to determine the utterances and corresponding speakers in a customer service call. Feature vectors are generated through a trained intent model to assign intent labels.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Renae Feacher whose telephone number is 571-270-5485. The Examiner can normally be reached Monday-Friday, 9:00 am - 5:00 pm. If attempts to reach the examiner by telephone are unsuccessful, the Examiner's supervisor, Beth Boswell can be reached at 571-272-6737.
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/Renae Feacher/
Primary Examiner, Art Unit 3625
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