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
Claim Objections
1. Claims 17-20 are objected to because of the following informalities: Claim 7 is not falling within one of the four statutory categories of invention. Supreme Court precedent and recent Federal Circuit decisions indicate that a statutory "process" under 35 U.S.C. 101 must (1) be tied to another statutory category (such as a particular apparatus), or (2) transform underlying subject matter (such as an article or material) to a different state or thing. While the instant claim(s) recite a series of steps or acts to be performed, the claim(s) neither transform underlying subject matter nor positively tie to another statutory category that accomplishes the claimed method steps, and therefore do not qualify as a statutory process. Appropriate correction is required. Failure to make appropriate correction(s) would lead to 35 U.S.C. 101 rejection(s). Dependent claims 18-20 inherit the same defects.
Claim Rejections - 35 USC § 101
2. 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. Each of the independent claims recites steps that transcribing text of a transcription using incremental segmentation and summaries are generated and summarize the transcribed texts. All of the recited steps are processes that, under its broadest reasonable interpretation, cover the limitations under the organized human activity with paper and pen. The claims recite machine learning (ML) model but lack of detail in the claims as to the form of the machine learning model (e.g., layers, nodes, etc. and what they do) and how the ML model actually used in determining representation representing the transcribed text.
The claim features under its broadest reasonable interpretation, are certain methods of organizing human activity performed by generic computer components. For example, but for “receiving” [human behavior: collecting, obtaining], “determining” [human behavior: deciding, conclusive], and “summarizing” [human behavior: encapsulating], in the context of this claim encompasses methods of organized human activity. If the claim limitations, under its broadest reasonable interpretation, covers fundamental economic practice, commercial or legal interaction or managing personal behavior or relationships or interactions between people but for the recitation of generic computer components, then it falls within the "system/method of organized human activity" grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. 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.
"[A]fter determining that a claim is directed to a judicial exception, 'we then ask, [w]hat else is there in the claims before us?"' MPEP 2106.05 (emphasis in MPEP) citing Mayo, 566 U.S. at 78. "What is needed is an inventive concept in the non-abstract application realm." SAP Inc. v. lnvestPic, LLV, Appeal No. 2017-2081 (Fed. Cir. 2018). For step two, the examiner must "determine whether the claims do significantly more than simply describe [the] abstract method" and thus transform the abstract idea into patent-eligible subject matter. Ultramercial, Inc. v. Hutu, LLC, 772 F.3d 709 (Fed. Cir. 2014).
A primary consideration when determining whether a claim recites "significantly more" than abstract idea is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry. See MPEP 2106.0S{d). "If the additional element (or combination of elements) is a specific limitation other than what is well- understood, routine and conventional in the field, for instance because it is an unconventional step that confines the claim to a particular useful application of the judicial exception, then this consideration favors eligibility. If, however, the additional element {or combination of elements) is no more than well-understood, routine, conventional activities previously known to the industry, which is recited at a high level of generality, then this consideration does not favor eligibility." Id.
The Federal Circuit has held that "[w]hether something is well-understood, routine, and conventional to a skilled artisan at the time of the patent is a factual determination." Bahr, Robert (April 19, 2018). Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility Decision (Berkheimer v. HP, Inc.) citing Berkheimer at 1369. "As set forth in MPEP 2106.05(d)(I), an examiner should conclude that an element (or combination of elements) represents well-understood, routine, conventional activity only when the examiner can readily conclude that the element(s) is widely prevalent or in common use in the relevant industry. This memo [] clarifies that such a conclusion must be based upon a factual determination that is supported as discussed in section III [of the memo]." Berkheimer Memo at 3 (emphasis in memo).
Generally, "[i]f a patent uses generic computer components to implement an invention, it fails to recite an inventive concept under Alice step two." West View Research v. Audi, CAFC Appeal Nos. 2016-1947-51 (Fed. Cir. 04/19/2017) citing Mortg. Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324-25 (Fed. Cir. 2016) (explaining that "generic computer components such as an 'interface,' 'network,' and 'database' ... do not satisfy the inventive concept requirement"; but see Bascom (finding that an inventive concept may be found in the non-conventional and non-generic arrangement of the generic computer components, i.e., the installation of a filtering tool at a specific location, remote from the end- users, with customizable filtering features specific to each end user).
In accordance with the above guidance, the examiner has searched the claim(s) to determine whether there are any "additional elements" in the claims that constitute "inventive concept," thereby rendering the claims eligible for patenting even if they are directed to an abstract idea. Alice, 134 S. Ct. 2347 (2014). Those "additional features" must be more than "well understood, routine, conventional activity." See Alice. To note, "under the Mayo/Alice framework, a claim directed to a newly discovered ... abstract idea [] cannot rely on the novelty of that discovery for the inventive concept necessary for patent eligibility." Genetic Techs. Ltd v. Merial LLC, 818 F.3d 1369, 1376 (Fed. Cir. 2016); Diamond v. Diehr, 450 U.S. 175, 188-89 (1981).
As an example, the Federal Circuit has indicated that "inventive concept" can be found where the claims indicate the technological steps that are undertaken to overcome the stated problem(s) identified in Applicant's originally-filed Specification. See Trading Techs. Inc. v. CQG, Inc., No. 2016-1616 (Fed. Cir. 2017); but see IV v. Erie Indemnity, No. 2016-1128 (Fed. Cir. March 7, 2017) ("The claims are not focused on how usage of the XML tags alters the database in a way that leads to an improvement in technology of computer databases, as in Enfish.") (emphasis in original) and IV. v. Capital One, Nos. 2016-1077 (Fed. Cir. March 7, 2017) ("Indeed, the claim language here provides only a result-oriented solution, with insufficient detail for how a computer accomplishes it. Our law demands more. See Elec. Power Grp., 830 F.3d 1356 (Fed. Cir. 2016) (cautioning against claims 'so result focused, so functional, as to effectively cover any solution to an identified problem.')"). Furthermore, "[a]bstraction is avoided or overcome when a proposed new application or computer-implemented function is not simply the generalized use of a computer as a tool to conduct a known or obvious process, but instead is an improvement to the capability of the system as a whole." Trading Techs. Int'l, Inc. v. CQG, Inc., No. 2016-1616 (Fed. Cir. 2017) (emphasis added).
In the search for inventive concept, the Berkheimer Memo describes "an additional element (or combination of elements) is not well-understood, routine or conventional unless the examiner finds, and expressly supports a rejection in writing with, one or more of the following:
A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s).
A citation to one or more of the court decisions discussed in the MPEP as noting the well-understood, routine, conventional nature of the additional element(s).
A citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s).
A statement that the examiner is taking official notice of the well-understood, routine, conventional nature of the additional element(s).
See Berkheimer Memo at 3-4.
Accordingly, the examiner refers to the following generically-recited computer elements with their associated functions (and associated factual finding(s)), which are considered, individually and in combination, to be routine, conventional, and well-understood:
“a computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that, when executed by at least one computing, are configured to cause the at least one computing device to:”,
“a device comprising: at least one display; at least one processor; and at least one memory storing instructions, which, when executed by the at least one processor, cause the device to:”,
“a method comprising:”
As set forth in MPEP § 2106.0S(d)(I), an examiner should conclude that an element (or combination of elements) represents well-understood, routine, conventional activity only when the examiner can readily conclude that the element(s) is widely prevalent or in common use in the relevant industry. The Berkhiemer memo clarifies that such a conclusion must be based upon a factual determination that is supported as discussed in section III the memo. As seen in paragraphs ([28, 99, 104, 111]) of the instant Specification and Symantec.. 838 F.3d at 1.321, 110 USPQ2d at. 1362, the elements are viewed to be well-understood, routine and conventional.
In sum, the Examiner finds that the claims "are directed to the use of conventional or generic technology in a nascent but well-known environment, without any claim that the invention reflects an inventive solution to any problem presented by combining the two." In re TLI Communications LLC, No. 2015-1372 (May 17, 2016). Similar to the claims in SAP v. lnvestPic, "[t]he claims here are ineligible because their innovation is an innovation in ineligible subject matter." Appeal No. 2017-2081 (Fed. Cir. 2018). In other words, "the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the non-abstract application realm." Id. Accordingly, when considered individually and in ordered combination, the examiner finds the claims to be directed to in-eligible subject matter.
Next, it is determined whether the claim integrates the judicial expectation into a practical application by identifying whether “any additional elements recited in the claim beyond the judicial exception(s)” and evaluate those elements to determine whether the integrate the judicial exception into a recognized practical application.
In this case, the additional elements do not integrate the judicial application into a practical application. The claim does not recite (i) an improvement to the functionality of a computer or other technology or technical field ; (ii) a "particular machine" to apply or use the judicial exception; (iii) a particular transformation of an article to a different thing or state; or (iv) any other meaningful limitation.
The additional elements beyond the judicial exception are a computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instruction when executed by at least one computing device, a device, at least one display, at least one processor, at least one memory storing instructions. Using a computing device and module to identify and determine a value and disposition of an object is merely applying the judicial exception using a generic computing component. Additionally, the claim identifies and determines a value and disposition of an object - the claim does not improve the functioning of the computing device, or other technology or field.
The claims do not recite specific limitations (alone or when considered as an ordered combination) that were not well understood, routine, and conventional. As set forth in the Specification, the disclosed subject matter can be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter.
Dependent claims 2-10, 12-16 and 18-20 include further recited limitations, do not integrate the abstract idea into a practical application, and the additional elements taken individually and in combination, do not contribute to an inventive concept, In other words, the dependent claims are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 112
3. 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.
Regarding claims 5 and 14, the phrase "likely" renders the claim(s) indefinite because the claim(s) include(s) elements not actually disclosed (those encompassed by "likely"), thereby rendering the scope of the claim(s) unascertainable. See MPEP § 2173.05(d).
Claim Rejections - 35 USC § 103
4. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
5. Claims 1, 11, 17 are rejected under 35 U.S.C. 103 as being unpatentable over submitted prior art Niekrasz (2019/0327103) in view of Barzelay et al. (US Patent 11,521,018).
As to claim 1, Niekrasz teaches a computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that when executed by at least one computing device are configured to cause the at least one computing device to:
receive first transcribed text of a transcription stream (Fig. 7, 700 – obtain transcript of meeting; [0034] - transcription engine provides speech-to-text conversion on an audio stream or recording of the conversation occurring in a meeting and produces a text transcript);
determine, using an incremental segment generator ([0067] - they can be executed in an iterative, on-line, real-time manner, one utterance at a time; [0059] – segmentation module 352), a first representation ([0054] - utterance feature vector) representing the first transcribed text (utterance);
determine that the first representation does not satisfy a summarization stability metric ([0059] - the entropy of an episode feature vector may be defined as the sum of the entropy each utterance feature in the episode feature vector… the segmentation with the lowest score (i.e., the minimum total entropy) is selected as the segmentation instead of other high score; hence it would have been obvious that other high score is not selected as the segmentation does not satisfy; [0067]);
receive second transcribed text (utterance) of the transcription stream (Fig. 7, 700 – obtain transcript of meeting; [0034] - transcription engine provides speech-to-text conversion on an audio stream or recording of the conversation occurring in a meeting and produces a text transcript);
determine, using the incremental segment generator ([0067] - they can be executed in an iterative, on-line, real-time manner, one utterance at a time; [0059] – segmentation module), a second representation ([0059] - episode-level feature vector by adding together the utterance feature vectors of all the utterances in the episode) representing the first transcribed text and the second transcribed text (utterance);
determine that the second representation satisfies the summarization stability metric ([0067] - in the real-time mode, as utterances are processed one by one, the Communicative Activity Segmentation will eventually determine that an episode segmentation point has been reached. At this point, it is possible to proceed to Step 3 for any episodes that have been completed and the summary can be accumulated one segment at a time in a dynamic fashion); and
summarize the second representation using a summarizer to obtain a summary of the first transcribed text and the second transcribed text (Fig. 7, 710 and 712 – produce episode summary for respective activity episode that is dependent on determined conversational activity type associated with respective activity episode and combine plurality of episode summaries to generate summary of meeting; [0063, 0094] - combine the plurality of episode summaries to generate a summary of the meeting).
Niekrasz does not explicitly discuss machine learning model.
Barzelay teaches using the highest rank sentence and/or textual segment and may be a machine learning model trained to summarize the highest rank sentence and/or textual segment. The sentence may be summarized using the constituent word weights (e.g., relevancy scores) of the words of the sentence (col. 15, lines 5-10).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Barzelay into the teachings of Niekrasz for the purpose of utilizing machine learning model trained to summarize the highest rank sentence and textual segment by taking into account the sentence's relevancy score and, within each sentence, the word relevancy score of the words found in the sentence.
Claims 11 and 17 are rejected for the same reasons discussed above with respect to claim 1. Furthermore, Niekrasz teaches a device (200), at least one display (346); at least one processor (Fig. 3, 341) and at least one memory (Fig. 3, 347) storing instructions (Fig. 3 and related texts).
6. Claims 2, 12, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Niekrasz and Barzelay in view of Awadallah et al. (2019/0325023) and Chen et al. (US Patent 7,092,870).
As to claims 2, 12, and 18, Niekrasz teaches using an incremental segment generator ([0067] - they can be executed in an iterative, on-line, real-time manner, one utterance at a time; [0059] – segmentation module); and using the summarizer ML model to obtain the summary of the first transcribed text and the second transcribed text (Fig. 7, 710 and 712 – produce episode summary for respective activity episode that is dependent on determined conversational activity type associated with respective activity episode and combine plurality of episode summaries to generate summary of meeting; [0063, 0094] - combine the plurality of episode summaries to generate a summary of the meeting). Niekrasz and Barzelay do not explicitly discuss the computer program product of claim 1, the device of claim 11 , and the method of claim 17, further comprising encoding the first representation and the second representation as a semantic unit; and decoding the semantic unit.
Awadallah teaches receiving as inputs the semantic units of the lowest representation 310 and to output a smaller number of semantic units of the higher representation 320, wherein semantic units of each of lower representation 310 and higher representation 320 are vectors having an identical defined number of elements, and wherein semantic units of higher representation 320 may encode the same portion of the first sentence as the one or more semantic units of the lowest representation 310 ([0068]) and semantic units of a higher representation may be output by any other suitable machine learning function instead of a temporal convolutional neural network ([0073]).
Chen teaches system for transcribing (decoding) textual input data (handwritten or typed text) into a string of semantic units (e.g., syllables or morphemes) using a statistical language model and vocabulary based on semantic units (such as syllables or morphemes). The string of semantic units that result from a decoding process are stored in a semantic unit database (abstract; col. 2, lines 45-63; claims 19-20)
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Awadallah and Chen into the teachings of Niekrasz and Barzelay for the purpose of compressing information of the portion of the first sentence as a particular semantic unit encoding the same portion of the first sentence as was represented by a plurality of word embeddings and using semantic units allows language models to be constructed which represent semantic information and providing improved decoding accuracy.
7. Claims 3 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Niekrasz (2019/0327103) and Barzelay et al. (US Patent 11,521,018) in view of Doebelin et al. (2020/0327432).
As to claims 3 and 13, Niekrasz and Barzelay do not explicitly discuss the computer program product of claim 1 and the device of claim 11, wherein the first representation includes a first semantic graph and the second representation includes a second semantic graph.
Doebelin teaches the semantic-based approach include semantic representation of a document being used to feed into a natural language generation (NLG) system. This method may focus on identifying noun phrases and verb phrases by processing linguistic data and may further include multiple semantic models, an information item-based method, and a semantic graph-based method. The multimodal semantic model includes building a semantic model, which may capture concepts and relationship among concepts. The semantic model may be built to represent the contents (text and images) of multimodal documents. The important concepts may be rated based on a specified measure and finally, the selected concepts may be expressed as sentences to form a summary. The information item-based method may summarize a document abstract representation of source documents, rather than from sentences of source documents. The abstract representation may be an information item, which may be the smallest element of coherent information in a text. The semantic graph-based method may summarize a document by creating a semantic graph called a rich semantic graph of the original document. The method may further include reducing the generated semantic graph and then generating a final abstractive summary from the reduced semantic graph ([0079]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Doebelin into the teachings of Niekrasz and Barzelay for the purpose of leveraging a semantic representation of textual content that is both machine readable and structured, rather than relying solely on raw word sequences; encoding the core events, entities, and relationships in a text as a graph, and abstracting away from surface linguistic details.
8. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Niekrasz, Barzelay, and Doebelin in view of Temkin et al. (2020/0251111).
As to claim 4, Niekrasz, Barzelay, and Doebelin do not explicitly discuss the computer program product of claim 3, wherein the stability metric is determined from graph properties of the first semantic graph and the second semantic graph.
Temkin teaches The semantic graph describes properties of data objects in an enterprise system, as well as relationships between those data objects. For example, an employee of a company may access a document. The semantic graph may identify the document, as well as components of the document, functions used to generate metrics in the document, data sources that the document included content from, and so on. When the employee submits a query, the usage history showing the access to the document and the semantic graph data indicating relationships of other objects to the document may be used to interpret the employee's query and provide a personalized result. For example, if the document related to production volume for widgets, and the employee asked “what is the latest information for widgets?”, the system may respond by indicating the latest production information due to the usage information indicating a prior interest in the production volume metric. For another employee who recently accessed information about sales of widgets, however, the response to the question “what is the latest information for widgets?” may be a metric indicating a monetary amount of sales. In both of these cases, the semantic graph used to link terms in the query (e.g., widgets) to specific data objects (e.g., tables, columns, documents, metrics, attributes, etc.) ([0072]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Doebelin into the teachings of Niekrasz, Barzelay, and Doebelin for the purpose of linking terms in the query using semantic graph to specific data objects such as tables, columns, documents, metrics, attributes, etc. that can be refined based on a user's personal history, (Temkin [0072]).
9. Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Niekrasz (2019/0327103) and Barzelay et al. (US Patent 11,521,018) in view of Wolf et al. (2022/0318522).
As to claim 5, Niekrasz teaches in the real-time mode, as utterances are processed one by one, the Communicative Activity Segmentation will eventually determine that an episode segmentation point has been reached. At this point, it is possible to proceed to Step 3 for any episodes that have been completed and the summary can be accumulated one segment at a time in a dynamic fashion ([0067]); (Fig. 7, 700 – obtain transcript of meeting; [0034] - transcription engine provides speech-to-text conversion on an audio stream or recording of the conversation occurring in a meeting and produces a text transcript). Niekrasz and Barzelay do not explicitly discuss the computer program product of claim 1 and the device of claim 11, wherein a prediction characterizing an extent to which a summary of current transcribed text generated by the summarizer ML model is likely to be changed upon receipt and summarization of subsequent transcribed text.
Wolf teaches provide an improvement in customization of predictive text summaries. The change summarization network provides an initial text summarization, based on an input text and reading parameters, and also provides a summary of changes to the text based on user interaction and events. Advanced comparison techniques (based on natural language processing) are used to compute the deviation of content that provide variants of text summaries to a user ([0021]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Wolf into the teachings of Niekrasz, Barzelay, and Doebelin for the purpose of customizing text summarization on a user-specific basis, saving user time in having to re-read new documents or manually looking for changes in different versions of a document (Wolf, [0021]).
10. Claims 9 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Niekrasz (2019/0327103) and Barzelay et al. (US Patent 11,521,018) in view of Cheung et al. (2021/0151058).
As to claims 9 and 15, Niekrasz and Barzelay do not explicitly discuss the computer program product of claim 1 and the device of claim 11, wherein instructions, when executed by the at least one computing device, are further configured to cause the at least one computing device to display the summary using a head-mounted display (HMD).
In the same field of endeavor, Cheung teaches a head-mounted display (HMD) and the display includes an HMD display application engine 440 and rendering engine 422 may generate and render for display a user interface for displaying transcription and/or additional data ([0070]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of the known technique of displaying a transcription on an HMD display. One of ordinary skill in the art would have recognized technique provides the rationale to arrive at a conclusion of obviousness. See KSR International Co. v. Teleflex Inc., 82 USPQ2d 1385 ((U.S. 2007).
11. Claims 10 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Niekrasz (2019/0327103) and Barzelay et al. (US Patent 11,521,018) in view of Rosenberg (2022/0038577).
As to claims 10 and 16, Niekrasz teaches the computer program product of claim 1 and the device of claim 11, wherein instructions, when executed by the at least one computing device, are further configured to cause the at least one computing device to generate a summary stream corresponding to the transcription stream (Fig. 7, 700 – obtain transcript of meeting; [0034] - transcription engine provides speech-to-text conversion on an audio stream or recording of the conversation occurring in a meeting and produces a text transcript and Fig. 7, 706 – generate summaries, produce summary for respective activity episode that is dependent on determined conversational activity type associated with respective activity episode).
Niekrasz and Barzelay do not explicitly discuss the summary stream including the summary.
Rosenberg teaches real time caption of call center conversations and at the same time a summary of the call sentence by sentence is determined based on real time intent extraction; call transcript and summary are displayed side by side simultaneously in real time (Figs. 1 and 2, [0024-0029, 0032]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Rosenberg into the teachings of Niekrasz and Barzelay for the purpose of matching the intent in real time, the intent recognizing unit may use the mapping and creating a string of text that forms part of the call summary, and illustrating a call summary overlaying or side-by-side with a conversation transcript . One of ordinary skill in the art would have recognized technique provides the rationale to arrive at a conclusion of obviousness. See KSR International Co. v. Teleflex Inc., 82 USPQ2d 1385 ((U.S. 2007).
Allowable Subject Matter
12. Claims 6 and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Claims 7 and 8 are objected because they depend on objected claim 6. Claim 20 is objected because they depend on objected claim 19.
Conclusion
13. Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUYNH H NGUYEN whose telephone number is (571)272-7489. The examiner can normally be reached Monday-Thursday 7:30AM-5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ahmad Matar can be reached on 571-272-7488. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/QUYNH H NGUYEN/Primary Examiner, Art Unit 2693
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