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
The present invention application contains 19 claims. Claims 1, 10 and 11 are independent. Claims 1-19 are examined and rejected by the following detail action.
Claim Objections.
Claims 6 and 16 recite the limitations "ingesting deal summary data…;", “classifying the ingested deal summary data base on a deal stage”; …”causing a display of the deal summary” that with the bold term never being introduced before or in the parents claims. Thus, there is insufficient antecedent basis for these limitations in the claims. Appropriate correction is required.
Examiner Notes
The prior art rejections below cite particular paragraphs, columns, and/or line numbers in the references for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art.
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 of this title, 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 1-5 and 10-15 are rejected under 35 U.S.C. 103 as being unpatentable over ASI et al. (“ASI”, US PG-Pub. 2022/0392434 A1) in view of Schlesinger et al. (“Schlesinger”, US PG-Pub. 2018/0090135 A1) and Cai et al. (“Cai”, US Patent 12436984 B2).
Re-claim 1,
ASI teaches a method for efficiently generating a brief of a call summary, the method comprising:
ingesting at least one simplified transcript, wherein a simplified transcript is a summarization of a transcript of a call and includes a plurality of bullet points of at least one main subject; representing each bullet point of the plurality of bullet points of the simplified transcript as an embedded vector using an embedding technique; determining at least one grouping of the plurality of bullet points based on the embedded vector, wherein the at least one grouping includes at least one bullet point (Fig. 1, [0019, 0025]. ASI describes the communication transcripts 108 (as a simplified transcript) is generated from the call recording 104 (i.e. the sentences of the transcript 108 may be represented as the bullet points of the communication main subject). The transcript segmentation 110 identifies each sentence (i.e. bullets) of the transcript 108 and vectorizes the identifier sentences into vectors using BERT techniques or the like and each of sentence vectors of the transcript 108 may then be split into groups based on the similarity and all sentences (i.e. vectors) in a group are related to a particular topic resulting as a communication segment 112 for each group);
feeding the at least one grouping into a generative language model to generate a summarized content for each of the at least one grouping; and generating a summarized brief based on the summarized content of the at least one grouping, wherein the summarized brief is generated as natural language textual data (Fig. 1, [0026-0028]. ASI describes the communication segments 112 are provided to the summary generator 114 using the generative language model (GLM) 116 to generate the segment summaries 122 in text-based format).
ASI fails to teach a trained rephrasing model to generate a rephrased content.
However, Schlesinger teaches:
a trained rephrasing model to generate a rephrased content ([0111]. Schlesinger describes a concept of rephrasing one user message to another new message using a machine-trained rephrasing model).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the call recording generated summaries teaching of ASI with the machine-trained rephrasing model teaching of Schlesinger to fine-tuned the conversation information into concise summaries for user easily and quickly understand the conversation information.
Modified ASI fails to teach:
wherein the summarized brief is generated as natural language textual data below a predetermined length.
However, Cai teaches:
wherein the summarized brief is generated as natural language textual data below a predetermined length (Fig. 1, col. 5 lines [20-37]. Cai describes the concept of setting a parameter for the “maximum length of a target summary” into pre-training language model to generate content’s summaries in a predetermined length) .
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the call recording generated summaries teaching of modified ASI with the preset target summary length teaching of Cai to provide the concise target summaries for user quickly obtaining the conversation information.
Re-claim 2,
In addition to what ASI-Schlesinger-Cai teaches the method in claim 1, ASI also teaches the method, further comprising: causing a display of the generated summarized brief via a user device (Fig. 6, [0063, 0065]. ASI describes the segment summaries 122 are displayed the AI Generated Summary section 608).
Re-claim 3,
In addition to what ASI-Schlesinger-Cai teaches the method in claim 1, ASI also teaches the method, further comprising:, further comprising: classifying a bullet point of the plurality of bullet points into a predefined conversation highlight using a trained machine learning model, wherein the at least one grouping of the at least one of the plurality of the bullet points is classified as a same conversation highlight (Fig. 1, [0025]. ASI describes each of sentence vectors (i.e. bullets) of the transcript 108 may then be split into groups based on the similarity (i.e. classification) and all sentences (i.e. vectors) in a group are related to a particular topic resulting as a communication segment 112 for each group. Thus, the topic of the group may be considered as conversation highlight).
Re-claim 4,
In addition to what ASI-Schlesinger-Cai teaches the method in claim 3, ASI also teaches the method, wherein the conversation highlight is any one of: an action item, a customer pain point, a customer request, and a customer question (Fig. 6, [0065]. ASI describes the conversation highlight is an action item (i.e. “<AGENT PROVIDES ANSWER>”) or a customer request (i.e. “<CUSTOMER EXPLAINS PROBLEM>”)).
Re-claim 5,
In addition to what ASI-Schlesinger-Cai teaches the method in claim 1, ASI also teaches the method, wherein the at least one grouping includes a subset of the plurality of bullet points that are clustered based on respective embedded vectors (Fig. 1, [0025]. ASI describes each of sentence vectors (i.e. bullets) of the transcript 108 may then be split into groups based on the similarity (i.e. classification) and all sentences (i.e. vectors) in a group are related to a particular topic resulting as a communication segment 112 for each group. Thus, the communication segment 112 group/cluster includes a subset of sentence vectors (i.e. bullets)).
Re-claim 10,
it is a medium claim having similar limitations in scope of claim 1; therefore, it is rejected under similar rationale.
Re-claim 11,
it is a system claim having similar limitations in scope of claim 1; therefore, it is rejected under similar rationale.
Re-claim 12,
in addition to what ASI-Schlesinger-Cai teaches the method in claim 11, claim 12 is a system claim having similar limitations in scope of claim 2; therefore, it is rejected under similar rationale.
Re-claim 13,
in addition to what ASI-Schlesinger-Cai teaches the method in claim 11, claim 13 is a system claim having similar limitations in scope of claim 3; therefore, it is rejected under similar rationale.
Re-claim 14,
in addition to what ASI-Schlesinger-Cai teaches the method in claim 13, claim 14 is a system claim having similar limitations in scope of claim 4; therefore, it is rejected under similar rationale.
Re-claim 15,
in addition to what ASI-Schlesinger-Cai teaches the method in claim 11, claim 15 is a system claim having similar limitations in scope of claim 5; therefore, it is rejected under similar rationale.
Claims 6-9 and 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over ASI in view of Schlesinger, Cai, and further in view of Ronen et al. (“Ronen”, US PG-Pub. 2022/0391591 A1).
Re-claim 6,
in addition to what ASI-Schlesinger-Cai teaches the method in claim 1, claim 6 is a method claim having similar limitations in scope of claims 1 and 2 on summarizing a call transcript and display the call summary; therefore, it is rejected under similar rationale.
Modified ASI fails to teach a deal or sale call.
However, Ronen teaches a deal or sale call ([0045]. Ronen describes the deal or sales call transcript is used on a trained generative summarization model).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the call recording generated summaries teaching of modified ASI with the sales call transcripts teaching of Ronen to summarize the sale communication data.
Re-claim 7,
in addition to what ASI-Schlesinger-Cai-Ronen teaches the method in claim 6, ASI also teaches the method, wherein the call summary data includes at least one of: deal data, customer data, and message data (Fig. 6, [0065]. ASI describes the call summary data includes a customer data (i.e. “<CUSTOMER EXPLAINS PROBLEM>”)).
Re-claim 8,
ASI-Schlesinger-Cai-Ronen teaches the method in claim 6, but ASI fails to teach a method, wherein the trained language model is a specific-trained language model that is specific to a customer.
However, Ronen teaches wherein the trained language model is a specific-trained language model that is specific to a customer (Fig. 1, [0044, 0045]. Ronen describes the sales call transcript is used on a trained generative summarization model specific to the customer of the sale call).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the call recording generated summaries teaching of modified ASI with the sales call transcripts teaching of Ronen to summarize the sale communication data.
Re-claim 9,
in addition to what ASI-Schlesinger-Cai-Ronen teaches the method in claim 6, claim 9 is a method claim having similar limitations in scope of claims 6 and 8; therefore, it is rejected under similar rationale.
Re-claim 16,
in addition to what ASI-Schlesinger-Cai teaches the method in claim 11, claim 16 is a system claim having similar limitations in scope of claim 6; therefore, it is rejected under similar rationale.
Re-claim 17,
in addition to what ASI-Schlesinger-Cai-Ronen teaches the method in claim 16, claim 17 is a system claim having similar limitations in scope of claim 7; therefore, it is rejected under similar rationale.
Re-claim 18,
in addition to what ASI-Schlesinger-Cai-Ronen teaches the method in claim 16, claim 18 is a system claim having similar limitations in scope of claim 8; therefore, it is rejected under similar rationale.
Re-claim 19,
in addition to what ASI-Schlesinger-Cai-Ronen teaches the method in claim 16, claim 19 is a system claim having similar limitations in scope of claim 9; therefore, it is rejected under similar rationale.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TUAN S NGUYEN whose telephone number is (571)270-7612. The examiner can normally be reached Monday-Friday (9-5).
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/TUAN S NGUYEN/Primary Examiner, Art Unit 2179
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