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 .
PATH TO ALLOWANCE
Examiner respectfully suggests Applicant telephone Examiner Adams (571-270-3688) prior to filing a response to the instant office action to discuss claim amendments to place Claim 1 and Claim 2 in a Condition for Allowance by curing the deficiencies under 35 U.S.C. section 112(b).
Double Patenting
The non-statutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A non-statutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a non-statutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claim 1 is/are rejected under the judicially created doctrine of non-statutory double patenting as being unpatentable over Claim 1 of U.S. Patent Application 12,532,053. This is a non-provisional double patenting rejection because the conflicting claims have issued to patent. Although the conflicting claim limitations are not recited identically, they are not patentably distinct from each other because they claim the same invention.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. The specification shall conclude with one or more claims particularly pointingout and distinctly claiming the subject matter which the inventor or a joint inventor regards as theinvention.
Claims 1-2 is/are rejected under 35 U.S.C. 112(b), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 1 recites “a server connected to the memory, the server capable of receiving inputs from a plurality of remote third-party client computers” whereby it is unclear from the claimed language how the ‘received inputs’ affect or interact with the known AI models/engine for a novel improvement. Applicant’s disclosure states Amazon’s Rekognition AI engine ‘provides accurate and reliable results for cue point/break points’ (US 2025-0133262 [0033]) whereby it is unclear how the claimed invention is a novel improvement over the Rekognition AI engine (as is recited in allowable Claim 2: “d). presenting the results in a graphical user interface GUI for review, so as to allow users to toggle between rules or profiles to further refine the results; e) recalibrating time codes based on user-selected rules and generating a review file that matches the source file”). Examiner respectfully suggests Applicant telephone Examiner Adams (571-270-3688) prior to filing a response to the instant office action to discuss claim language to place Claim 1 in a condition for allowance.
Claim 2 recites “ group consisting of ad breaks, adult language, nudity, and graphics” whereby it is unclear what type of ‘graphics’. Applicant’s published disclosure states ‘inappropriate graphics’ for example (US 2025-0133262 [0023]). Appropriate correction/clarification is required.
CLAIM INTERPRETATION
35 U.S.C. § 112(f)
MPEP 2181(I) discloses that a claim limitation will be presumed to invoke 35 U.S.C. 112(f) if it meets the following 3-prong analysis:
the claim limitation uses the phrase “means” or “step” or a term used as a substitute for “means” that is a generic placeholder;
the phrase “means” or “step” or the substitute term is modified by functional language, typically linked by the transition word “for” or another linking word; and
the phrase “means” or “step” or the substitute term is not modified by sufficient structure or material for performing the claimed function.
Claim 1 discloses limitations which are presumed to invoke 35 U.S.C. 112(f) as said limitations meet said 3-prong analysis.
Regarding Claim 1, an artificial intelligent engine for analyzing is considered to read on Fig. 1 AI engine 20.
REASONS FOR ALLOWANCE
As per Claim 1, the following is an Examiner’s statement of reasons for allowance, but for the outstanding double patenting rejection and rejections under 35 U.S.C. section 112(b): the closest prior art obtained from an Examiner’s search (BIN W MOHAMAD, US Pub. No.: 2022-0335246; NIHEI, US Pub. No.: 2024-0373073; DOUGLAS, US Pub. No.: 2017-0371961) does not teach nor suggest in detail the limitations:
“A system for editing a piece of audio video content to provide a plurality of cue points based upon a rule set, said system comprising: a) memory, the memory including a rule set for verifying cue points; b) a server connected to the memory, the server capable of receiving inputs from a plurality of remote third party client computers; c) an artificial intelligence engine for analyzing the piece of video content so as to identify events within the audiovideo piece content that include at least one content break from the group consisting of video black, silence, and scene changes; d) a CPU for generating cue points within the audiovideo piece content based upon the events identified by the artificial intelligence engine, and further verifying the validity of such cue points by comparing their location within the piece of audio video content with the rule set, excluding the cue points which violate the rule set, and marking the audiovideo piece with a timecode or frame numbers so as enable the identification of the valid cue points; and e) a second memory for storing the audiovideo piece with the verified cue points”
as well as the combination of all the limitations within the independent claims and the enabling portions of the specification.
The closest prior art of record or combination thereof: BIN W MOHAMAD in view of NIHEI in view of DOUGLAS does not teach or suggest in detail at least: 1). verifying the validity of such cue points by comparing their location within the piece of audio video content with the rule set, excluding the cue points which violate the rule set, and marking the audiovideo piece with a timecode or frame numbers so as enable the identification of the valid cue points or teach 2). generating cue points within the audiovideo piece content based upon the events of group consisting of video black, silence, and scene changes identified by the artificial intelligence engine as presented by the Applicant.
BIN W MOHAMAD only teaches AI models rules for editing and inserting cue-points in AV content based upon AI detection of the endpoints of a scene but is silent as to identifying silent or video black as well as silent as to at least verifying the validity of such cue points by comparing their location within the piece of audio video content with the rule set, excluding the cue points which violate the rule set, and marking the audiovideo piece with a timecode or frame numbers so as enable the identification of the valid cue points as claimed by Applicant.
NIHEI only discloses using AI to analyze AV content to detect points of video black, silence and scene change for future prediction of cue-points but is silent as to generating and editing to insert the cue-points based upon said detections as claimed by the Applicant as well as silent to rule comparisons.
DOUGLAS only discloses audio content processing with AI cue-point insertion by generating a beat grid representing the audio content, determining values for the beat grid of audio features of the content, calculating a score for the audio feature at each of a plurality of positions in the beat grid by comparing, at each of the plurality of positions, combinations of determined values of the audio feature before a respective position of the plurality of positions with determined values of the audio feature after the respective position and generating the cue point at a particular position of the plurality of positions, based on the calculated scores. However, DOUGLAS is silent as to at least marking the audio with timecodes or frame numbers, silent to generating cue points within the audiovideo piece content based upon the events of group consisting of video black, silence, and scene changes identified by the artificial intelligence engine, and silent to excluding cue points that violate a rule set as provided by the claimed invention.
The closest NPL KIM (KIM, “Robots, artificial intelligence, and service automation RAISA in hospitality: sentiment analysis of YouTube streaming data”, 2022) discusses generally intelligent AV content editing based upon rules via a plurality of clients but is silent as to at least verifying the validity of such cue points by comparing their location within the piece of audio video content with the rule set, excluding the cue points which violate the rule set, and marking the audiovideo piece with a timecode or frame numbers so as enable the identification of the valid cue points claimed by the Applicant
Whereas, as stated above, Applicant’s claimed invention recites a system for editing a piece of audio video content to provide a plurality of cue points based upon a rule set. The invention claims a system comprising memory including a rule set for verifying cue points, a server connected to the memory and capable of receiving inputs from a plurality of remote third party client computers, and an artificial intelligence engine for analyzing the piece of video content so as to identify events within the audiovideo piece content that include at least one content break from the group consisting of video black, silence, and scene changes. Finally, the invention claims a CPU for generating cue points within the audiovideo piece content based upon the events identified by the artificial intelligence engine, and further verifying the validity of such cue points by comparing their location within the piece of audio video content with the rule set, excluding the cue points which violate the rule set, and marking the audiovideo piece with a timecode or frame numbers so as enable the identification of the valid cue points as well as a second memory for storing the audiovideo piece with the verified cue points.
So as indicated by the above statements, Applicant’s proposed claim has been considered persuasive, in light of the claim limitations as well as the enabling portions of the specification.
The dependent claims further limit the independent claims and are considered allowable on the same basis as the independent claims as well as for the further limitations set forth.
As per Claim 2, the following is an Examiner’s statement of reasons for allowance but for the outstanding rejections under 35 U.S.C. section 112(b): the closest prior art obtained from an Examiner’s search (BIN W MOHAMAD, US Pub. No.: 2022-0335246; NIHEI, US Pub. No.: 2024-0373073; TALAVERA, US Pub. No.: 2024-0039905) does not teach nor suggest in detail the limitations:
“A method for automating media content detection and validation, comprising: a) automatically ingesting media content into a storage system; b) applying AI models to detect audiovideo content selected from the group consisting of ad breaks, adult language, nudity, and graphics; c) filtering the detected audiovideo content using saved rules or profiles; d) presenting the results in a graphical user interface (GUI) for review, so as to allow users to toggle between rules or profiles to further refine the results; e) recalibrating time codes based on user-selected rules and generating a review file that matches the source file; and f) exporting the final results through formats such as JSON or direct download”
as well as the combination of all the limitations within the independent claims and the enabling portions of the specification.
The closest prior art of record or combination thereof: BIN W MOHAMAD in view of NIHEI in view of TALAVERA does not teach or suggest in detail at least applying AI models to detect audiovideo content selected from the group consisting of ad breaks, adult language, nudity, and graphics. The combination is silent as to JSON, filtering the detected audiovideo content using saved rules or profiles as well as silent as to recalibrating time codes based on user-selected rules and generating a review file that matches the source file as presented by the Applicant.
BIN W MOHAMAD only teaches AI models rules for editing and inserting cue-points in AV content based upon AI detection of the endpoints of a scene but is silent as to identifying content with adult language/ nudity as well as silent as to allowing a user to toggle between rules or profiles to further refine the results. Finally, the primary prior art of record does not teach recalibrating time codes based on user-selected rules and generating a review file that matches the source file or exporting the final results through formats such as JSON as claimed by Applicant.
NIHEI only discloses using AI to analyze AV content to detect points of video black, silence and scene change for future prediction of cue-points but is silent as to detections of inappropriate content as claimed by the Applicant as well as silent to rule comparisons. TALAVERA only discloses a GUI to allow a user of an AI training product to select and edit profiles/rules for content analysis using the AI models.
The closest NPL KIM (KIM, “Robots, artificial intelligence, and service automation RAISA in hospitality: sentiment analysis of YouTube streaming data”, 2022) discusses generally intelligent AV content editing based upon rules via a plurality of clients but is silent as to at least verifying the validity of such cue points by comparing their location within the piece of audio video content with the rule set, excluding the cue points which violate the rule set, and marking the audiovideo piece with a timecode or frame numbers so as enable the identification of the valid cue points claimed by the Applicant
Whereas, as stated above, Applicant’s claimed invention recites a method for automating media content detection and validation that includes automatically ingesting media content into a storage system and applying AI models to detect audiovideo content selected from the group consisting of ad breaks, adult language, nudity, and graphics. The invention further claims filtering the detected audiovideo content using saved rules or profiles, presenting the results in a graphical user interface (GUI) for review, so as to allow users to toggle between rules or profiles to further refine the results, recalibrating time codes based on user-selected rules and generating a review file that matches the source file, and exporting the final results through formats such as JSON or direct download.
So as indicated by the above statements, Applicant’s proposed claim has been considered persuasive, in light of the claim limitations as well as the enabling portions of the specification.
The dependent claims further limit the independent claims and are considered allowable on the same basis as the independent claims as well as for the further limitations set forth.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Claims 1-6 is/are allowed, but for the outstanding double patenting rejection and outstanding rejections directed towards 35 U.S.C. section 112(b).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Eileen Adams whose telephone number is 571-270-3688. The examiner can normally be reached on Monday-Friday from 8:30am-5:00pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, William Vaughn can be reached on (571) 272-3922. The fax phone number for the organization where this application or proceeding is assigned is 571-270-4688.
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/EILEEN M ADAMS/Primary Examiner, Art Unit 2481