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 .
Claim Objections
Claim 7 is objected to because of the following informalities:
Claim 7 as recited is ambiguous as it contains redundant language. For the record, the examiner recommends claim 7 to be rewritten as follow, and interpretation will be as such until clarification is made of record or applicant accepts this proposal and makes changes accordingly.
7. The system of claim 6,
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Peters (US Patent Pub. No.: US 2022/0086393 A1) hereinafter Peters, in view of Wang (Chinese Patent Pub. No.: CN 114254653 A), hereinafter Wang, further in view of Okerlund (US Patent Pub. No.: US 2023/0273945 A1), hereinafter Okerlund.
Regarding claim 1, Peters teaches a system for automatic role detection of participants of interest (For example, during the conference, the system can automatically detect elements in the video streams of participants, such as gestures, facial expressions, and the participants' cognitive and emotional state. [0007]. As a simple example, the aggregate representation may indicate the number of participants in each of three categories respectively representing high engagement, moderate engagement, and low engagement. [0361]), the system comprising: a multimedia file (One or more cameras 1532 can capture images and/or video of the local participants 1530 during the communication session. [0355]) comprising an interview of one or more participants of interest (For example, the system can provide elements that summarize the current state of the video conference and its participants. [0007]) and one or more file components (The server 1510 can also perform analysis on media streams, e.g., on individual image frames, on video segments, on audio data, and so on. [0518]), the one or more file components comprising one or more of an audio file (The server 1510 can also perform analysis on media streams, e.g., on individual image frames, on video segments, on audio data, and so on. [0518]), and a video file (The server 1510 can also perform analysis on media streams, e.g., on individual image frames, on video segments, on audio data, and so on. [0518]); a processor operable to: segment the one or more file components into a plurality of segments (For example, the analysis could be performed for a specific lesson of a teacher to a class, or for portions or segments of the lesson. [0468]); assign, via an assigning algorithm, a role to each of the one or more participants of interest (As a simple example, the aggregate representation may indicate the number of participants in each of three categories respectively representing high engagement, moderate engagement, and low engagement. [0361]), wherein the assigning algorithm is a machine learning algorithm (In some implementations, analyzing the participant data and the result data comprises training a machine learning model based on the participant data and the result data. [0065]), the machine learning algorithm including a computer-implemented method comprising: receiving, from the one or more file components (The server 1510 can also perform analysis on media streams, e.g., on individual image frames, on video segments, on audio data, and so on. [0518]), an input dataset comprising the plurality of segments (For example, the analysis could be performed for a specific lesson of a teacher to a class, or for portions or segments of the lesson. [0468]), each of the plurality of segments comprising one or more partial or complete sentences spoken by the one or more participants of interest (The system 1510 can analyze records of content 2013 of communication sessions, such as content presented, words or phrases spoken, topics discussed, media types used, and so on, to determine when different content occurred and how content items relate to other events and conditions in the communication sessions. [0427]); identifying the one or more participants of interest contained within the multimedia file (As another example, the system can be used to assess an instructor's performance, e.g., with respect to objective measures of audience response or later outcomes, or relative to other instructors. This can help identify and provide evidence for identifying who is a top-notch engager and what techniques or characteristics they employ make them effective. [0214]), wherein identifying the one or more participants of interest comprises determining which of the one or more participants of interests is responsible for each of the plurality of segments (As another example, in an instructional setting, the system may detect that a person became confused at a certain time (e.g., corresponding to a certain topic, slide, or other portion of the instruction), and this can be indicated to the instructor. [0235]. The system 1510 can analyze records of participant actions 2012, and correlate instances of different actions with corresponding communication sessions and participants. [0427]); and assigning (The process 1700 includes obtaining a participant score for each participant in a set of multiple participants in a communication session (1702). [0379]), based on which of the plurality of distinct categories is identified with respect to each of the one or more participants of interest (As a simple example, the aggregate representation may indicate the number of participants in each of three categories respectively representing high engagement, moderate engagement, and low engagement. [0361]), a role to each of the one or more participants of interest (As a simple example, the aggregate representation may indicate the number of participants in each of three categories respectively representing high engagement, moderate engagement, and low engagement. [0361]); a user interface configured to dynamically display the multimedia file (In some implementations, the one or more computers are configured to switch between enhancing the video conference in multiple different modes. The modes can include a passive public mode in which the one or more computers provide an output media stream display indicator for each of the multiple endpoints to each endpoint in the video conference. [0086]).
Peters does not teach the following limitations as further recited, but Wang further teaches determining a sentence syntax structure for each of the one or more partial or complete sentences (Syntactic analysis is the process of performing lexical phrase analysis on natural language input by a user in order to recognize the syntactic structure of a sentence to achieve automatic syntactic analysis. Page 8 last paragraph) from each of the plurality of segments (Text Classification (Text Classification) trains corpora by using a supervised or unsupervised machine learning method to obtain a Classification model, and the Classification model can classify documents of unknown classes to obtain one or more predefined class labels, wherein the class labels are the classes of the documents. Page 5 6th paragraph); classifying, based on the determined sentence syntax (Syntactic analysis is the process of performing lexical phrase analysis on natural language input by a user in order to recognize the syntactic structure of a sentence to achieve automatic syntactic analysis. Page 8 last paragraph), each of the plurality of segments into a plurality of distinct categories (step S4, training the corpus by using a supervised or unsupervised machine learning method to obtain a classification model for classifying the unknown class of documents to obtain one or more predefined class labels. Abstract).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Peters to incorporate the teachings of Wang to classify, based on the determined sentence syntax, medium segments into distinct categories to ensure multimedia file processing is more efficient and intelligent.
The combination of Peters and Wang does not teach the following limitations as further recited, but Okerlund further teaches the one or more file components comprising one or more of a transcript file (In some embodiments, a transcript of speech is utilized as a source of input into one of more searches of electronically-stored state. [0142]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Okerlund to include a transcript file as one of the file components in order to improve multimedia file processing to be more efficient and intelligent.
Regarding claim 2, Peters in the combination teaches the system of claim 1, further comprising a gallery view module configured to isolate one or more video streams (For example, some video conference platforms may attempt to show each participant's video in a "gallery" view. [0004]), wherein at least one of the one or more video streams is assigned to at least one of the one or more participants of interest (If a web-based seminar or college class has 200 participants, but the presenter's endpoint can only display 5-10 participant video streams as is often the case, then the majority of the visual, non-verbal content contributed by the participants is entirely lost to the presenter. [0005]).
Regarding claim 3, Peters in the combination teaches the system of claim 2, wherein the user interface is further configured to label at least one of the one or more video streams assigned to at least one of the one or more participants of interest with the role assigned to the one or more participants of interest (FIG. 12A shows recommendations for conversation management with icons in the upper left corner (which reads on “to label”). The different shapes and/or colors can signal different needs. This view shows icons associated with actions that should be taken to address the needs of team members or to facilitate overall collaboration. For example, the square may indicate that the person needs to talk less ( e.g., they are dominating the conversation or having a negative effect on others) (which reads on “the role assigned to the one or more participants of interest”), a triangle may indicate that the person needs to be drawn into the conversation, etc. [0334].
PNG
media_image1.png
670
838
media_image1.png
Greyscale
).
Regarding claim 4, Okerlund in the combination teaches the system of claim 1, wherein the role to be assigned to at least one of the one or more participants of interest is a deponent (As shown, microphone 105 is arranged to capture audio reflecting statements made orally by deposer 103A, as well as deponent 103B. [0061]).
Regarding claim 5, Okerlund in the combination teaches the system of claim 1, wherein the plurality of distinct categories (It is common knowledge that the categories can be assigned according to the goals wished to be achieved.) comprise Question (In another embodiment, the system accesses stored and/or time-stamped audio and, utilizing a user interface, a user may replay for other participants a portion of recorded audio to, for example, accurately reiterate a question posed by an attorney or an answer provided by a witness. [0118]), Answer (In another embodiment, the system accesses stored and/or time-stamped audio and, utilizing a user interface, a user may replay for other participants a portion of recorded audio to, for example, accurately reiterate a question posed by an attorney or an answer provided by a witness. [0118]), Clarification Question (In some examples, once all deposition participants have responded to either clarify all identified ambiguities ( see errata sheet information, infra) or accept the initial transcript, the software application executing on local computing device 810 may send an indication to generate a final transcript to the remote computing device 820. [0135]), Clarification Answer (In an embodiment, at step 2112, the ALPA prompts the user in real-time for clarification regarding which 'Joe is being referred to. [0188]), Other Speakers (In some examples, audio translation engine 207 (e.g., speaker identification module 232) parses individual voices from a recording containing the speech of multiple individuals, and individuals may be identified through a variety of means, including by data from a user-specific voice profile, which may include data that can help identify the speech acts of one speaker from the sometimes contemporaneous speech acts of other speakers. [0098]), Oath Question (Accordingly, system 200 outputs audio instructions or presents on a display ( of user interface 109) a textual description of the oath, and request signatures or the traditional vocal assent to proceed under oath from the required participants. [0074]), and Oath Answer (Audio translation engine 207 may then prompt the participants to administer an oath or otherwise prompt an individual to electronically or verbally attest (using, for example, an e-signature or, by giving verbal assent) to a pre-drafted oath. [0114]), wherein Answer (In another embodiment, the system accesses stored and/or time-stamped audio and, utilizing a user interface, a user may replay for other participants a portion of recorded audio to, for example, accurately reiterate a question posed by an attorney or an answer provided by a witness. [0118]), Clarification Question (In some examples, once all deposition participants have responded to either clarify all identified ambiguities ( see errata sheet information, infra) or accept the initial transcript, the software application executing on local computing device 810 may send an indication to generate a final transcript to the remote computing device 820. [0135]), and Oath Answer (Audio translation engine 207 may then prompt the participants to administer an oath or otherwise prompt an individual to electronically or verbally attest (using, for example, an e-signature or, by giving verbal assent) to a pre-drafted oath. [0114]) are sentences articulated by a deponent (As shown, microphone 105 is arranged to capture audio reflecting statements made orally by deposer 103A, as well as deponent 103B. [0061]).
Regarding claim 6, Okerlund in the combination teaches the system of claim 5, wherein only a portion of the plurality of distinct categories is associated with the role (In some examples, audio translation engine 207 (e.g., speaker identification module 232) parses individual voices from a recording containing the speech of multiple individuals, and individuals may be identified through a variety of means, including by data from a user-specific voice profile, which may include data that can help identify the speech acts of one speaker from the sometimes contemporaneous speech acts of other speakers. [0098]. In other words, the category of Other Speakers may not be associated with the role as it identifies people who are not participants of interest but happen to speak at the same time as the participants of interest.).
Regarding claim 7, Okerlund in the combination teaches the system of claim 6, (In another embodiment, the system accesses stored and/or time-stamped audio and, utilizing a user interface, a user may replay for other participants a portion of recorded audio to, for example, accurately reiterate a question posed by an attorney or an answer provided by a witness. [0118]), Clarification Question (In some examples, once all deposition participants have responded to either clarify all identified ambiguities ( see errata sheet information, infra) or accept the initial transcript, the software application executing on local computing device 810 may send an indication to generate a final transcript to the remote computing device 820. [0135]), and Oath Answer (Audio translation engine 207 may then prompt the participants to administer an oath or otherwise prompt an individual to electronically or verbally attest (using, for example, an e-signature or, by giving verbal assent) to a pre-drafted oath. [0114]) are associated with the role of a deponent (As shown, microphone 105 is arranged to capture audio reflecting statements made orally by deposer 103A, as well as deponent 103B. [0061]).
Method claims 8-14 are drawn to the method of using the corresponding apparatus claimed in claims 1-7. Therefore method claims 8-14 correspond to apparatus claims 1-7 and are rejected for the same reasons of obviousness as used above.
Claims 15-20 are drawn to a non-transitory computer readable storage medium storing instructions executable by a processor for executing the method of using the corresponding apparatus as claimed in claims 1-7. Therefore, claims 15-20 correspond to apparatus claims 1-7, and are rejected for the same reasons of obviousness as used above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEI ZHAO whose telephone number is (703)756-1922. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, VU LE can be reached at (571)272-7332. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/LEI ZHAO/Examiner, Art Unit 2668
/VU LE/Supervisory Patent Examiner, Art Unit 2668
Prosecution Insights