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
Claims 1-20 are canceled. Claims 21-40 are pending.
This action is response to the application filed on January 09, 2025.
CROSS-REFERENCE TO RELATED APPLICATIONS
This application is a continuation of U.S. Application Serial No. 18/278,777, filed on August 24, 2023, which is a National Stage application under 35 U.S.C. § 371 of International Application No. PCT/US2022/018198, having an International Filing Date of February 28, 2022, which claims priority to U. S. Provisional Patent Application No. 63/154,498, filed on February 26, 2021, the disclosures of which are hereby incorporated by reference in their entirety.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/09/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Interpretation; Broadest Reasonable Interpretation
CLAIMS MUST BE GIVEN THEIR BROADEST REASONABLE INTERPRETATION IN LIGHT OF THE SPECIFICATION
During patent examination, the pending claims must be "given their broadest reasonable interpretation consistent with the specification." The Federal Circuit’s en banc decision in Phillips v. AWH Corp., 415 F.3d 1303, 1316, 75 USPQ2d 1321, 1329 (Fed. Cir. 2005) expressly recognized that the USPTO employs the "broadest reasonable interpretation" standard: The Patent and Trademark Office ("PTO") determines the scope of claims in patent applications not solely on the basis of the claim language, but upon giving claims their broadest reasonable construction "in light of the specification as it would be interpreted by one of ordinary skill in the art.".
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.
Claims 21-40 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Byrd et al (US 2010/0274618 A1).
With respect to claims 21, 30 and 39, Byrd et al teaches
obtaining a transcript of a current legal interaction (FIG. 8, [0018] communicating by telephone, an automatic speech recognition system will capture the speech (as a "speech record") and perform real-time speech transcription to produce a text transcript (as a "text record"). [0025] Dialogs based on the interaction context (e.g., conversations that involve mention of an attorney or a law suit to the legal department));
processing contextual information of the current legal interaction and the transcript using a language processing machine learning model to generate a representation of the transcript (FIG. 8, [0018] "speech record" and perform real-time speech transcription to produce a text transcript. [0025] Dialogs based on the interaction context (e.g., conversations that involve mention of an attorney or a law suit to the legal department). [0055] using machine learning by analyzing a large number of interaction logs. [0058] FIG. 8 step 802, the system obtains the text stream. the text stream obtained from a speech recognition system);
searching data comprising one or more legal documents using a query generated using the representation of the transcript to identify portions of legal documents relevant to the current legal interaction ([0025] documents that are relevant to the customer interaction. The documents identified by doing an automated search using the text of identified issues as search terms based on the interaction context (e.g., mention of an attorney or a law suit to the legal department). [0027] Paragraphs from a document that is relevant. The document may be determined using query);
ranking the identified portions of the legal documents based on a relevance to the current legal interaction ([0045] The scoring can be used to rank results. [0027] Paragraphs from a document that is relevant. The document may be determined using query answering); and
providing a representation of the ranked portions via an interface ([0042] FIG. 5 Presentation Generator 119. The Presentation Generator receives the identified issues, to provide results. [0045] The scoring can be used to rank results. [0027] Paragraphs from a document that is relevant. The document may be determined using query answering).
With respect to claims 22, 31 and 40, Byrd et al teaches
generating a deposition summary of the current legal interaction based on the representation of the transcript, wherein the deposition summary includes a condensed representation of key topics discussed during the current legal interaction, and highlights of critical testimony, questions, or objections; and displaying the deposition summary via the interface ([0004] speech, e-mail text, a chat transcript, or any other content that is used for communication with the customer to maintain customer interaction information, including the interaction summaries).
With respect to claims 23 and 32, Byrd et al teaches transcript of the current legal interaction is obtained after the current legal interaction has concluded ([0055] maintain customer interaction information, including the interaction summaries maintained. machine learning by analyzing a large number of interaction logs).
With respect to claims 24 and 33, Byrd et al teaches transcript of the current legal interaction is obtained while the current legal interaction is ongoing ([0018] communicating by telephone, an automatic speech recognition system will capture the speech (also referred to as a "speech record") and perform real-time speech transcription to produce a text transcript (also referred to as a "text record") of the interaction).
With respect to claims 25 and 34, Byrd et al teaches performing a speech-to-text conversion to generate the transcript from audio signal obtained during the current legal interaction ([0058] FIG. 8 At step 802, the system obtains the text stream, the text stream may be obtained from a speech recognition system. [0018] communicating by telephone, an automatic speech recognition system (will capture the speech (also referred to as a "speech record") and perform real-time speech transcription to produce a text transcript (also referred to as a "text record") of the interaction).
With respect to claims 26 and 35, Byrd et al teaches displaying the representation of the transcript via the interface; receiving, via the interface, a user feedback regarding the representation; and providing content based at least on the representation and the user feedback ([0042] Feedback Storage component 115 based on implicit and explicit feedback. received positive feedback for interactions wit h similar issues in the past and score generated by the Rule Based Scorer for responses that received negative feedback).
With respect to claims 27 and 36, Byrd et al teaches discoveries or evidences; motion practice; interparty communications; hearings; trials; work products; third party information; evidence from previous cases; user feedback deponent information; case type information of the current legal interaction; or judge information of the current legal interaction ([0030] based on the interaction context (e.g., conversations that involve mention of an attorney or a law suit to the legal department). [0031] displayed as a "hint" on the agent's computer screen (e.g., "this call needs to be handled by the legal department").
With respect to claims 28 and 37, Byrd et al teaches processing an input comprising data characterizing the respective identified portion using a feature extraction machine learning model to generate a respective feature representation; and processing the feature representations of the identified portions of the legal documents to generate a ranking result ([0045] The scoring can be used to rank results. [0027] Paragraphs from a document that is relevant. The document may be determined using query answering).
With respect to claims 29 and 38, Byrd et al teaches generating a respective relevance score for each of the identified portions; and ranking the identified portions according to the respective relevance scores ([0045] The scoring can be used to rank results. [0027] Paragraphs from a document that is relevant. The document may be determined using query answering).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISAAC M WOO whose telephone number is (571)272-4043. The examiner can normally be reached 9:00 to 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tony Mahmoudi can be reached on 571-272-4078. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ISAAC M WOO/Primary Examiner, Art Unit 2163