DETAILED ACTION
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 .
Response to Amendment
The Amendment filed June 2, 2026, has been entered. Claims 1 – 7 and 21 – 33 are pending in the application. Applicant’s amendments to the claims and specification have overcome each and every claim and specification objection previously set forth in the Non-Final Office Action mailed May 14, 2025.
Response to Arguments
Applicant’s arguments, filed June 2, 2026, regarding the 35 U.S.C. 101 rejection of claim 1 have been considered but they are not persuasive.
On pages 14-15 of Applicant’s response, Applicant argues “MPEP § 2106.04(II)(A) indicates that, when analyzing claims under 35 U.S.C. § 101, examiners must perform a two-step inquiry. Under Step 2A, Prong Two, the examiner must "evaluate whether the claim as a whole integrates the exception into a practical application of that exception." MPEP § 2106.04(II)(A)(2). When an NLP system generates a transcript and summary of a conversation, the supplemental data needed to explain candidate terms in that conversation resides in external sources that are unstructured and use terminology independent of the conversation. Presenting this raw external data to a reader alongside the transcript creates a disjointed experience and forces the reader to manually reconcile differences in vocabulary between the conversation and the external content. This is a technical problem inherent to systems that retrieve data from disparate sources and present it alongside NLP-generated output. Amended claim 1 addresses this technical problem by processing the reply to the query "using the NLP system to produce an explanation" that uses "vocabulary extracted from the transcript." This is a specific technical mechanism for converting unstructured external content into contextually consistent, human-readable explanations matched to the transcript's terminology. By providing this technical solution to the technical problem, amended claim 1 is a practical application of any alleged judicial exception.”.
However, a person can perform the steps of claim 1 as a mental process, so the resulting improvements in converting unstructured external content into contextually consistent, human-readable explanations matched to the transcript's terminology do not depend on the use of a computer. The claim 1 limitation “a Natural Language Processing (NLP) system” amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, this additional element does not integrate the abstract idea into a practical application and is not sufficient to amount to significantly more than the judicial exception because it does not impose any meaningful limits on practicing the abstract idea.
Applicant’s following arguments, filed June 2, 2026, regarding the 35 U.S.C. 102 rejection of claim 1 have been considered but they are not persuasive.
On page 16 of Applicant’s response, Applicant argues “The Office Action also cites Bradley as showing "formatting a query that includes the candidate term" in response to receiving a selection from the reader. P. 13-14. The cited portion of Bradley describes generating hyperlinks with pre-formed URLs and query arguments at transcription time, before any reader interaction. Col. 16:5-27. For example, Bradley describes that when a city name appears adjacent to the phrase "what's the weather right now in," Bradley's system tags the city name with a hyperlink that "references an API URL to look up the weather and a query argument that is the name of the city." Col. 16:16-21. This hyperlink, including its URL and query argument, is generated when the transcript is created, and clicking the hyperlink in Bradley navigates to an already-formed URL. The system does not format a query in response to the reader's selection, as is described in amended claim 1, which indicates that the query is formatted "in response to receiving, from the reader, a selection of the candidate term."”.
However, Bradley et al. (US Patent No. 12,125,487), hereinafter Bradley, recites, in column 15, lines 48-54, "According to some embodiments, as another type of metadata, the system can analyze semantic information and create embedded hyperlinks to look up related information in the transcript. The system can identify words or key phrases within a text string and present the word/key phrase as a hyperlink anchor corresponding to a URL, which can provide additional information of the word or key phrase.", and recites, in column 16, lines 5-27, "According to some embodiments, the identified word or key phrase as the embedded hyperlink anchor can further comprise an argument in the URL when text adjacent to the key phrase matches a pattern corresponding to an argument. Various types of arguments can be supported, such as numbers, an enumerated value such as a month name, or reference to database entries such as employee names. According to some embodiments, the system can recognize terms related to relevant data, such as weather or stock prices, and automatically generate hyperlinks to retrieve such data. For example, the text “what's the weather right now in” followed by a word that matches the name of a city in a list of known cities would cause the name of the city to be tagged with a hyperlink that references an API URL to look up the weather and a query argument that is the name of the city. For dynamic information such as weather, some embodiments can capture the data by accessing the URL, store it, and provide it with the stored transcript to provide an accurate record as of when the meeting was recorded. In some embodiments, key phrases can be specified as natural language grammars with slots in the location of relevant variables.", disclosing presenting the name of a city as a hyperlink, where the selection of the hyperlink initiates a query to look up the weather in the city with the name of the city as a parameter of the query. A query to look up the weather in a city with the name of the city as a parameter of the query reads on formatting a query that includes the candidate term, and selecting the hyperlink to initiate the query reads on the query being formatted in response to receiving a selection of the candidate term.
Applicant’s remaining arguments, filed June 2, 2026, with respect to claims 1 – 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Drawings
The drawings are objected to because:
In figures 4E, 4F, and 4G, the reference character “450e” is used to designate an indicator for the word “Kyuritol” in two instances of the word “Kyuritol” and the reference character “450f” is used to designate an indicator for the word “Kyuritol” in two instances of the word “Kyuritol”. Reference character “450f” should be used to designate an indicator for the word “Kyuritol” for all instances of the word “Kyuritol”.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 – 7 and 21 – 33 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a method, comprising: analyzing a transcript of a conversation, by a Natural Language Processing (NLP) system, to identify at least one candidate term in the conversation to provide supplemental information for to a reader of the transcript; in response to receiving, from the reader, a selection of the candidate term, formatting a query that includes the candidate term; in response to receiving a reply to the query: processing the reply using the NLP system to produce an explanation in a human-readable format, wherein the explanation uses vocabulary extracted from the transcript; and outputting the explanation to the reader.
The claim 1 limitations, under their broadest reasonable interpretation, cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting “a Natural Language Processing (NLP) system”, nothing in the claim elements preclude the actions from practically being performed in the mind. For example, “analyzing” in the context of this claim encompasses a person reading a transcript and identifying terms in the transcript, “formatting” in the context of this claim encompasses a person writing a question about a term, “processing” in the context of this claim encompasses a person determining an explanation about a term, and “outputting” in the context of this claim encompasses a person writing an explanation about a term. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional element “a Natural Language Processing (NLP) system”. The additional element “a Natural Language Processing (NLP) system” amounts to no more than mere instructions to apply the exception using generic computer components. There are no details about a particular natural language processing system or how the natural language processing system operates to analyze a transcript of a conversation. The natural language processing system is used to generally apply the abstract idea (analyzing a transcript of a conversation) without placing any limitation on how the natural language processing system operates to analyzing a transcript. The limitation recites only the idea of analyzing a transcript using a natural language processing system without details on how this is accomplished. The claim omits any details as to how the natural language processing system solves a technical problem, and instead recites only the idea of a solution or outcome. The claim invokes a generic natural language processing system merely as a tool for analyzing a transcript rather than purporting to improve the technology or a computer (See MPEP 2106.05(f)). Therefore, the limitation represents no more than mere instructions to apply the judicial exception on a computer. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim 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 element amounts 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. The claim is not patent eligible.
Claims 2 – 7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 2 – 7 depend from claim 1, and thus recites the limitations of claim 1.
For the reasons discussed above for claim 1, the claim 1 limitations recite abstract ideas. The additional limitations of claims 2 – 7 do not preclude the steps of claim 1 from practically being performed in the mind. For example, a person using the method of claim 1 to provide additional information to a reader of a transcript could also perform the limitations of claims 2 – 7:
Claim 2: A person could identify a candidate term from an action item in the transcript.
Claim 3: A person could provide a hyperlink for a candidate term in the transcript.
Claim 4: A person could provide information from a source selected by a participant in the transcript conversation.
Claim 5: A person could provide information in a format selected for the reader, and could use vocabulary from the transcript.
Claim 6: A person could include the information about the transcript in a report provided to a participant in the transcript conversation.
Claim 7: A person could provide a hyperlink for the source of information provided to the reader.
If a claim limitation, under its broadest reasonable interpretation, covers performance of
the limitation in the mind but for the recitation of generic computer components, then it
falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The claims do not integrate the judicial exception into a practical application. For the reasons discussed above for claim 1, the additional element amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, this element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. For the reasons discussed above for claim 1, mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claims are not patent eligible.
Claim 21 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform steps comprising: analyzing a transcript of a conversation, by a Natural Language Processing (NLP) system, to identify at least one candidate term in the conversation to provide supplemental information for to a reader of the transcript; in response to receiving, from the reader, a selection of the candidate term, formatting a query that includes the candidate term; in response to receiving a reply to the query: processing the reply using the NLP system to produce an explanation in a human-readable format, wherein the explanation uses vocabulary extracted from the transcript; and outputting the explanation to the reader.
The claim 21 limitations, under their broadest reasonable interpretation, cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting “a non-transitory computer-readable storage medium”, “a processor”, and “a Natural Language Processing (NLP) system”, nothing in the claim elements preclude the actions from practically being performed in the mind. For example, “analyzing” in the context of this claim encompasses a person reading a transcript and identifying terms in the transcript, “formatting” in the context of this claim encompasses a person writing a question about a term, “processing” in the context of this claim encompasses a person determining an explanation about a term, and “outputting” in the context of this claim encompasses a person writing an explanation about a term. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional elements “a non-transitory computer-readable storage medium”, “a processor”, and “a Natural Language Processing (NLP) system”. The additional elements amount to no more than mere instructions to apply the exception using generic computer components. There are no details about a particular natural language processing system or how the natural language processing system operates to analyze a transcript of a conversation. The natural language processing system is used to generally apply the abstract idea (analyzing a transcript of a conversation) without placing any limitation on how the natural language processing system operates to analyzing a transcript. The limitation recites only the idea of analyzing a transcript using a natural language processing system without details on how this is accomplished. The claim omits any details as to how the natural language processing system solves a technical problem, and instead recites only the idea of a solution or outcome. The claim invokes a generic natural language processing system merely as a tool for analyzing a transcript rather than purporting to improve the technology or a computer (See MPEP 2106.05(f)). Therefore, the limitations represent no more than mere instructions to apply the judicial exception on a computer. 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.
The claim 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 elements 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. The claim is not patent eligible.
Claims 22 – 27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 22 – 27 depend from claim 21, and thus recites the limitations of claim 21.
For the reasons discussed above for claim 21, the claim 21 limitations recite abstract ideas. The additional limitations of claims 22 – 27 do not preclude the steps of claim 21 from practically being performed in the mind. For example, a person using the method of claim 21 to provide additional information to a reader of a transcript could also perform the limitations of claims 22 – 27:
Claim 22: A person could identify a candidate term from an action item in the transcript.
Claim 23: A person could provide a hyperlink for a candidate term in the transcript.
Claim 24: A person could provide information from a source selected by a participant in the transcript conversation.
Claim 25: A person could provide information in a format selected for the reader, and could use vocabulary from the transcript.
Claim 26: A person could include the information about the transcript in a report provided to a participant in the transcript conversation.
Claim 27: A person could provide a hyperlink for the source of information provided to the reader.
If a claim limitation, under its broadest reasonable interpretation, covers performance of
the limitation in the mind but for the recitation of generic computer components, then it
falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The claims do not integrate the judicial exception into a practical application. For the reasons discussed above for claim 21, the additional elements amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, this 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 claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. For the reasons discussed above for claim 21, mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claims are not patent eligible.
Claim 28 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a system comprising: a processor; and a non-transitory computer-readable storage medium storing instructions that, when executed by the processor, cause the processor to perform actions comprising: analyzing a transcript of a conversation, by a Natural Language Processing (NLP) system, to identify at least one candidate term in the conversation to provide supplemental information for to a reader of the transcript; in response to receiving, from the reader, a selection of the candidate term, formatting a query that includes the candidate term; in response to receiving a reply to the query: processing the reply using the NLP system to produce an explanation in a human-readable format, wherein the explanation uses vocabulary extracted from the transcript; and outputting the explanation to the reader.
The claim 28 limitations, under their broadest reasonable interpretation, cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting “a system”, “a processor”, “a non-transitory computer-readable storage medium”, and “a Natural Language Processing (NLP) system”, nothing in the claim elements preclude the actions from practically being performed in the mind. For example, “analyzing” in the context of this claim encompasses a person reading a transcript and identifying terms in the transcript, “formatting” in the context of this claim encompasses a person writing a question about a term, “processing” in the context of this claim encompasses a person determining an explanation about a term, and “outputting” in the context of this claim encompasses a person writing an explanation about a term. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional elements “a system”, “a processor”, “a non-transitory computer-readable storage medium”, and “a Natural Language Processing (NLP) system”. The additional elements amount to no more than mere instructions to apply the exception using generic computer components. There are no details about a particular natural language processing system or how the natural language processing system operates to analyze a transcript of a conversation. The natural language processing system is used to generally apply the abstract idea (analyzing a transcript of a conversation) without placing any limitation on how the natural language processing system operates to analyzing a transcript. The limitation recites only the idea of analyzing a transcript using a natural language processing system without details on how this is accomplished. The claim omits any details as to how the natural language processing system solves a technical problem, and instead recites only the idea of a solution or outcome. The claim invokes a generic natural language processing system merely as a tool for analyzing a transcript rather than purporting to improve the technology or a computer (See MPEP 2106.05(f)). Therefore, the limitations represent no more than mere instructions to apply the judicial exception on a computer. 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.
The claim 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 elements 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. The claim is not patent eligible.
Claims 29 – 33 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 29 – 33 depend from claim 28, and thus recites the limitations of claim 28.
For the reasons discussed above for claim 28, the claim 28 limitations recite abstract ideas. The additional limitations of claims 29 – 33 do not preclude the steps of claim 28 from practically being performed in the mind. For example, a person using the method of claim 28 to provide additional information to a reader of a transcript could also perform the limitations of claims 29 – 33:
Claim 29: A person could identify a candidate term from an action item in the transcript.
Claim 30: A person could provide a hyperlink for a candidate term in the transcript.
Claim 31: A person could provide information from a source selected by a participant in the transcript conversation.
Claim 32: A person could provide information in a format selected for the reader, and could use vocabulary from the transcript.
Claim 33: A person could include the information about the transcript in a report provided to a participant in the transcript conversation.
If a claim limitation, under its broadest reasonable interpretation, covers performance of
the limitation in the mind but for the recitation of generic computer components, then it
falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The claims do not integrate the judicial exception into a practical application. For the reasons discussed above for claim 28, the additional elements amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, this 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 claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. For the reasons discussed above for claim 28, mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claims are not patent eligible.
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.
Claims 1, 3, 7, 21, 23, 27 – 28 and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Bradley et al. (US Patent No. 12,125,487), hereinafter Bradley, in view of Fink et al. (US Patent No. US 10,380,120), hereinafter Fink.
Regarding claim 1, Bradley discloses a method, comprising:
analyzing a transcript of a conversation, by a Natural Language Processing (NLP) system, to identify at least one candidate term in the conversation to provide supplemental information for to a reader of the transcript (Column 9, lines 37-48, "According to some embodiments, the system can proceed to transcribe 33 the speech segments into text strings with one or more speech recognition systems. A speech recognition system can be an Automatic Speech Recognition (ASR) and natural language understanding (NLU) system that is configured to infer at least one semantic meaning of an audio segment based on various statistical acoustic and language models and grammars. According to some embodiments, the speech recognition system can comprise at least one acoustic model. The speech recognition system can further comprise one or more pronunciation models, lexicons, and language models for natural language processing."; Column 15, lines 48-54, "According to some embodiments, as another type of metadata, the system can analyze semantic information and create embedded hyperlinks to look up related information in the transcript. The system can identify words or key phrases within a text string and present the word/key phrase as a hyperlink anchor corresponding to a URL, which can provide additional information of the word or key phrase."); Analyzing semantic information in a transcript reads on analyzing a transcript of a conversation, identifying a word or phrase and presenting the word or phrase as a hyperlink anchor corresponding to a URL which can provide additional information of the word or phrase reads on identifying a candidate term in the conversation to provide supplemental information for to a reader of the transcript, and an automatic speech recognition (ASR) and natural language understanding (NLU) system reads on a Natural Language Processing system.);
in response to receiving, from the reader, a selection of the candidate term, formatting a query that includes the candidate term (Column 15, lines 48-54, "According to some embodiments, as another type of metadata, the system can analyze semantic information and create embedded hyperlinks to look up related information in the transcript. The system can identify words or key phrases within a text string and present the word/key phrase as a hyperlink anchor corresponding to a URL, which can provide additional information of the word or key phrase."; Column 16, lines 5-27, "According to some embodiments, the identified word or key phrase as the embedded hyperlink anchor can further comprise an argument in the URL when text adjacent to the key phrase matches a pattern corresponding to an argument. Various types of arguments can be supported, such as numbers, an enumerated value such as a month name, or reference to database entries such as employee names. According to some embodiments, the system can recognize terms related to relevant data, such as weather or stock prices, and automatically generate hyperlinks to retrieve such data. For example, the text “what's the weather right now in” followed by a word that matches the name of a city in a list of known cities would cause the name of the city to be tagged with a hyperlink that references an API URL to look up the weather and a query argument that is the name of the city. For dynamic information such as weather, some embodiments can capture the data by accessing the URL, store it, and provide it with the stored transcript to provide an accurate record as of when the meeting was recorded. In some embodiments, key phrases can be specified as natural language grammars with slots in the location of relevant variables."; Generating hyperlinks for words or phrases in a transcript to look up related information when the reader selects the hyperlink reads on receiving a selection of a candidate term, and generating a query to retrieve information that includes the word or phrase as a query argument reads on formatting a query that includes the candidate term.);
in response to receiving a reply to the query: processing the reply using the NLP system to produce an explanation in a human-readable format (Column 15, line 58 - Column 16, line 4, "For example, the system can identify words that match the names of Wikipedia articles or companies listed on a stock market. For another example, the system can identify text segments that match the names of company employees. As shown in FIG. 7, at location 71 in the transcript, the system has identified the name of an employee, Peter Gibbons, and displayed the transcript text for the name in a different font color with underscoring. A viewer or editor of the transcript in an appropriately enabled application can click or tap the text to invoke a browser that accesses web information on Peter Gibbons' employee profile. In some editors, hovering a pointer over a hyperlink pops up a mini window with information, and moving the pointer away from the hyperlink causes the mini window to disappear."; Column 16, lines 16-27, "For example, the text “what's the weather right now in” followed by a word that matches the name of a city in a list of known cities would cause the name of the city to be tagged with a hyperlink that references an API URL to look up the weather and a query argument that is the name of the city. For dynamic information such as weather, some embodiments can capture the data by accessing the URL, store it, and provide it with the stored transcript to provide an accurate record as of when the meeting was recorded. In some embodiments, key phrases can be specified as natural language grammars with slots in the location of relevant variables."; Displaying a window with information from an employee profile when the name of an employee is selected reads on producing an explanation in a human-readable format.);
and outputting the explanation to the reader (Column 15, line 58 - Column 16, line 4, "For example, the system can identify words that match the names of Wikipedia articles or companies listed on a stock market. For another example, the system can identify text segments that match the names of company employees. As shown in FIG. 7, at location 71 in the transcript, the system has identified the name of an employee, Peter Gibbons, and displayed the transcript text for the name in a different font color with underscoring. A viewer or editor of the transcript in an appropriately enabled application can click or tap the text to invoke a browser that accesses web information on Peter Gibbons' employee profile. In some editors, hovering a pointer over a hyperlink pops up a mini window with information, and moving the pointer away from the hyperlink causes the mini window to disappear."; Displaying a window with information from an employee profile when the name of an employee is selected reads on outputting the explanation to the reader.).
Bradley does not specifically disclose: processing the reply using the NLP system to produce an explanation in a human-readable format, wherein the explanation uses vocabulary extracted from the transcript.
Fink teaches:
processing the reply using the NLP system to produce an explanation in a human-readable format, wherein the explanation uses vocabulary extracted from the transcript (Column 2, lines 6-11, "Embodiments disclosed herein provide techniques for discovering and presenting topic summaries related to a selection of text in an electronic document. In response to receiving user-selected text in the electronic document, a topic summary application uses natural language processing to identify an entity in the user-selected text."; Column 2, lines 24-47, "In one embodiment, the summary application may identify related entities and associated text phrases for the summary by removing filler or statistically common words such as “the,” “and,” “of,” etc. from sentences which include the entity identified from the user-selected text. The summary application may then take remaining clauses which are subjects (or targets) to be the related entities. Other text which is relevant to the identified entity itself and/or the related entities may be taken as the associated text phrases. After identifying the related entities and associated text phrases, the summary application may further determine semantically important text phrases so that important text phrases are presented to the user. In one embodiment, the summary application may determine semantically important text phrases using text analytics, with text phrases that are repeated often considered more important, and vice versa. Using this approach, the summary application may rank the text phrases. The summary application may then include in the summary frequently correlated related entities along and associated text phrases that are semantically important (i.e., highly ranked). Due to limited screen space, semantically important text phrases may be ranked, with less important text phrases being culled from display. Such a summary may be presented to the user via, e.g., a pop-up window."; The summary application determining semantically important text phrases and presenting the important text phrases to the user reads on the explanation using vocabulary extracted from the transcript.).
Fink is considered to be analogous to the claimed invention because it is in the same field of transcript analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bradley to incorporate the teachings of Fink to determine semantically important text phrases and present the important text phrases to the user. Doing so would allow for presenting to a user an abstract view summarizing knowledge about an identified entity in user-selected text to refresh the memory of the user (Fink; Column 2, lines 6-23).
Regarding claim 3, Bradley in view of Fink discloses the method as claimed in claim 1.
Bradley further discloses:
wherein the explanation includes a hyperlink to usage of the candidate term in the transcript associated with an utterance received from a party to the conversation (Column 15, lines 48-54, "According to some embodiments, as another type of metadata, the system can analyze semantic information and create embedded hyperlinks to look up related information in the transcript. The system can identify words or key phrases within a text string and present the word/key phrase as a hyperlink anchor corresponding to a URL, which can provide additional information of the word or key phrase."; Identify words or key phrases within a text string of a transcript and present the word or key phrase as a hyperlink corresponding to a URL which can provide additional information of the word or key phrase reads on an explanation including a hyperlink to usage of the candidate term in the transcript associated with an utterance received from a party to the conversation.).
Regarding claim 7, Bradley in view of Fink discloses the method as claimed in claim 1.
Bradley further discloses: wherein the explanation includes a hyperlink to an external source used by the NLP system to generate contents of the explanation (Column 15, lines 48-54, "According to some embodiments, as another type of metadata, the system can analyze semantic information and create embedded hyperlinks to look up related information in the transcript. The system can identify words or key phrases within a text string and present the word/key phrase as a hyperlink anchor corresponding to a URL, which can provide additional information of the word or key phrase."; Identifying a word or phrase and presenting the word or phrase as a hyperlink corresponding to a URL which can provide additional information of the word or phrase reads on the explanation includes a hyperlink to an external source used by the NLP system to generate contents of the explanation.).
Regarding claim 21, arguments analogous to claim 1 are applicable. In addition, Bradley discloses a non-transitory computer-readable storage medium storing instructions (Column 6, lines 13-17, “The following sections describe systems of process steps and systems of machine components for automated transcription of conversations. These can be implemented with computers that execute software instructions stored on non-transitory computer-readable media.”) that, when executed by a processor (Column 31, lines 29-32, “FIG. 20B shows a block diagram of the server system 200. It comprises a multicore cluster of computer processors (CPU) 201 and a multicore cluster of graphics processors (GPU) 202.”), cause the processor to perform the steps of claim 1.
Regarding claim 23, arguments analogous to claim 3 are applicable.
Regarding claim 27, arguments analogous to claim 7 are applicable.
Regarding claim 28, arguments analogous to claim 1 are applicable. In addition, Bradley discloses a system (Column 6, lines 13-15, “The following sections describe systems of process steps and systems of machine components for automated transcription of conversations.”) comprising:
a processor (Column 31, lines 29-32, “FIG. 20B shows a block diagram of the server system 200. It comprises a multicore cluster of computer processors (CPU) 201 and a multicore cluster of graphics processors (GPU) 202.”);
and a non-transitory computer-readable storage medium storing instructions that, when executed by the processor, cause the processor to perform actions (Column 6, lines 13-17, “The following sections describe systems of process steps and systems of machine components for automated transcription of conversations. These can be implemented with computers that execute software instructions stored on non-transitory computer-readable media.”) comprising the steps of claim 1.
Regarding claim 30, arguments analogous to claim 3 are applicable.
Claims 2, 6, 22, 26, 29 and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Bradley in view of Fink, and further in view of Hilleli et al. (US Patent No. 11,062,270), hereinafter Hilleli.
Regarding claim 2, Bradley in view of Fink discloses the method as claimed in claim 1, but does not specifically disclose: wherein the NLP system identifies the candidate term from an action item generated from the transcript.
Hilleli teaches:
wherein the NLP system identifies the candidate term from an action item generated from the transcript (Column 1, lines 42-50, "Aspects of this disclosure relate to computerized systems for automatically determining and presenting enriched action items of an event, such as a meeting. An enriched action item may include an indication of the action item and related meeting content or contextual data useful for understanding the action item, and which may be personalized to a specific user, such as a meeting attendee. In particular, action items may be determined and then enhanced or clarified in order to be more understandable."; Column 2, lines 3-7, "In some embodiments, an intelligent graphical user interface may be provided that includes functionality to improve the user experience, such as features that allow the user to provide feedback indicating whether or not an item presented is in fact an action item."; Column 15, lines 13-18, "In some embodiments, the event content is or includes documents or transcripts of the order and content of everything that was said in an event written in natural language. For example, the event content can be a written transcript of everything that was said or uttered during an entire duration of a meeting."; Providing an indication of the action item and related meeting content or contextual data useful for understanding the action item reads on identifies a candidate term from an action item generated from the transcript.).
Hilleli is considered to be analogous to the claimed invention because it is in the same field of transcript analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bradley in view of Fink to incorporate the teachings of Hilleli to provide an indication of an action item and related meeting content or contextual data useful for understanding the action item. Doing so would allow for automatically modifying or supplementing an action item based on contextual data that is useful for understanding the action item and may be personalized to a specific user, such as a meeting attendee (Hilleli; Column 4, lines 13-24).
Regarding claim 6, Bradley in view of Fink discloses the method as claimed in claim 1, but does not specifically disclose: further comprising: in response to receiving, from the reader, the selection of the candidate term, adding the selection to an aggregation report; and providing the aggregation report to a second party to the conversation, other than the reader.
Hilleli teaches:
in response to receiving, from the reader, the selection of the candidate term, adding the selection to an aggregation report (Column 2, lines 3-7, "In some embodiments, an intelligent graphical user interface may be provided that includes functionality to improve the user experience, such as features that allow the user to provide feedback indicating whether or not an item presented is in fact an action item."; Column 25, lines 61 - Column 26, line 1, "The enriched action item assembler 288 is generally responsible for generating a list of action items and may also provide related information, such as event context. For example, the enriched action item assembler 288 can generate a list of action items and consolidate it with other information determined by the action item enrichment 282, such as who owns the action item, who stated the action item, when the action item is due, and what the action item is."; The user providing feedback indicating whether or not an item presented is in fact an action item reads on receiving the selection of the candidate term from the reader, and a list of action items consolidated with other information reads on an aggregation report.);
and providing the aggregation report to a second party to the conversation, other than the reader (Column 11, line 59 - Column 12, line 4, "Continuing with FIG. 2, example system 200 includes a meeting monitor 250. Meeting monitor 250 is generally responsible for determining and/or detecting meeting features from online meetings and/or in-person meetings and making the meeting features available to the other components of the system 200. For example, such monitored activity can be meeting location (e.g., as determined by geo-location of user devices), topic of the meeting, invitees of the meeting, whether the meeting is recurring, related deadlines, projects and the like. In some aspects, meeting monitor 250 determines and provides a set of meeting features (such as described below), for a particular meeting, and for each user associated with the meeting."; Providing meeting features to each user associated with a meeting reads on providing an aggregation report to a second party to the conversation other than the reader.).
Hilleli is considered to be analogous to the claimed invention because it is in the same field of transcript analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bradley in view of Fink to incorporate the teachings of Hilleli to provide user feedback indicating whether or not an item presented is an action item, generate a list of action items consolidated with other information, and provide meeting features to each user associated with a meeting. Doing so would allow for automatically modifying or supplementing an action item based on contextual data that is useful for understanding the action item and may be personalized to a specific user, such as a meeting attendee (Hilleli; Column 4, lines 13-24).
Regarding claim 22, arguments analogous to claim 2 are applicable.
Regarding claim 26, arguments analogous to claim 6 are applicable.
Regarding claim 29, arguments analogous to claim 2 are applicable.
Regarding claim 33, arguments analogous to claim 6 are applicable.
Claims 4, 24 and 31 are rejected under 35 U.S.C. 103 as being unpatentable over Bradley in view of Fink, and further in view of Nguyen et al. (US Patent No. 11,404,049), hereinafter Nguyen.
Regarding claim 4, Bradley in view of Fink discloses the method as claimed in claim 1, but does not specifically disclose: wherein contents of the explanation are retrieved from a supplemental data source selected by a party in the conversation, different from the reader.
Nguyen teaches:
wherein contents of the explanation are retrieved from a supplemental data source selected by a party in the conversation, different from the reader (Column 4, lines 34-42, "Providing mechanisms for automatically surfacing a real-time transcription of a speaking user in association with a productivity application and augmenting that surfacing with note taking features also provides an enhanced user experience. For example, a user may take notes related to a speech (e.g., a lecture) in a first window of a productivity application, while having a real-time transcription of the speech surfaced next to that window."; Column 6, line 64 - Column 7, line 13, "For example, if the user that provides speech 230 is presenting a lecture with one or more corresponding documents related to the lecture (e.g., an electronic slide show from a presentation application on organic chemistry, a lecture handout, etc.), the language processing models used to transcribe speech 230 may utilize that material (e.g., via analysis of those electronic documents) to develop a custom corpus and/or dictionary that may be utilized in the language processing models in determining correct output for speech 230. This is illustrated by domain-specific dictionaries/corpus 234. According to some examples, vocabulary (e.g., words, phrases) that is determined to be specific and/or unique to a particular language processing model, custom corpus, and/or custom dictionary, may be automatically highlighted and/or otherwise distinguished from other captions in a transcription pane in a productivity application."; Augmenting a transcription of a lecture utilizing material provided by the user presenting the lecture reads on retrieving contents of the explanation from a supplemental data source selected by a party in the conversation different from the reader.).
Nguyen is considered to be analogous to the claimed invention because it is in the same field of transcript analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bradley in view of Fink to incorporate the teachings of Nguyen to augment a transcription of a lecture utilizing material provided by the user presenting the lecture. Doing so would allow for a user taking notes related to a lecture to surface standard definitions and custom definitions for words in a transcription of the lecture (Nguyen; Column 4, lines 32-52).
Regarding claim 24, arguments analogous to claim 4 are applicable.
Regarding claim 31, arguments analogous to claim 4 are applicable.
Claims 5, 25 and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Bradley in view of Fink, and further in view of Muralitharan et al. (US Patent Application Publication No. 2022/0414348), hereinafter Muralitharan.
Regarding claim 5, Bradley in view of Fink discloses the method as claimed in claim 1.
Fink further teaches:
wherein the explanation uses vocabulary extracted from the transcript (Column 2, lines 6-11, "Embodiments disclosed herein provide techniques for discovering and presenting topic summaries related to a selection of text in an electronic document. In response to receiving user-selected text in the electronic document, a topic summary application uses natural language processing to identify an entity in the user-selected text."; Column 2, lines 24-47, "In one embodiment, the summary application may identify related entities and associated text phrases for the summary by removing filler or statistically common words such as “the,” “and,” “of,” etc. from sentences which include the entity identified from the user-selected text. The summary application may then take remaining clauses which are subjects (or targets) to be the related entities. Other text which is relevant to the identified entity itself and/or the related entities may be taken as the associated text phrases. After identifying the related entities and associated text phrases, the summary application may further determine semantically important text phrases so that important text phrases are presented to the user. In one embodiment, the summary application may determine semantically important text phrases using text analytics, with text phrases that are repeated often considered more important, and vice versa. Using this approach, the summary application may rank the text phrases. The summary application may then include in the summary frequently correlated related entities along and associated text phrases that are semantically important (i.e., highly ranked). Due to limited screen space, semantically important text phrases may be ranked, with less important text phrases being culled from display. Such a summary may be presented to the user via, e.g., a pop-up window."; The summary application determining semantically important text phrases and presenting the important text phrases to the user reads on the explanation using vocabulary extracted from the transcript.).
Fink is considered to be analogous to the claimed invention because it is in the same field of transcript analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bradley in view of Fink to further incorporate the teachings of Fink to determine semantically important text phrases and present the important text phrases to the user. Doing so would allow for presenting to a user an abstract view summarizing knowledge about an identified entity in user-selected text to refresh the memory of the user (Fink; Column 2, lines 6-23).
Bradley in view of Fink does not specifically disclose: wherein the human-readable format is selected from a plurality of human-readable formats by the NLP system based on a supplementation level of the reader.
Muralitharan teaches:
wherein the human-readable format is selected from a plurality of human-readable formats by the NLP system based on a supplementation level of the reader (Paragraph 0037, lines 1-10, "The techniques introduced herein help to bridge the gap between text for presentation to a user and the reading comprehension level of that user. In various aspects, a multi-layered system is introduced herein that assesses the comprehension level of source material (text/audio transcripts), learns and establishes the comprehension level of the recipient, analyzes comprehension equality at the topic and keyword level, and/or adaptively transforms source material to the required comprehension of the target recipient."; Paragraph 0046, lines 1-14, "According to various embodiments, as detailed further below, STERLA engine 302 may be operable to ‘translate’ the text, audio, video or other content provided by one participant of an online conversation such that it is at, or below, that of the comprehension level of another participant. Consider, for instance, user 306 sending a text message to user 308 via collaboration service 304. This text may range from being very simplistic to using phrases or terminology that is highly specialized. As a result, there are instances in which user 308 may not fully understand what user 306 is saying. A key functionality of STERLA engine 302 is to assess this text and adjust it for presentation to user 308, to increase the potential for user 308 to comprehend the message."; Adaptively transforming source material to the required comprehension of the target recipient reads on selecting a human-readable format based on a supplementation level of the reader.).
Muralitharan is considered to be analogous to the claimed invention because it is in the same field of transcript analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bradley in view of Fink to incorporate the teachings of Muralitharan to transform source material to the required comprehension of the target recipient. Doing so would allow for adjusting the original text of a conversation to include additional context to allow a user to better understand the conversation (Muralitharan; Paragraph 0082, lines 1-9).
Regarding claim 25, arguments analogous to claim 5 are applicable.
Regarding claim 32, arguments analogous to claim 5 are applicable.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James Boggs whose telephone number is (571)272-2968. The examiner can normally be reached M-F 8:00 AM - 5:00 PM.
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/JAMES BOGGS/Examiner, Art Unit 2657
