DETAILED ACTION
This action is in response to communication filed on 19 December 2025. Claims 1-9, 12-16 and 18-20 are amended. No claim has been added or canceled. Claims 1-20 are pending in the application and have been considered below.
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
Based on applicant's amendment and response, claims 15-16 and 18-20 are no longer interpreted as invoking 35 USC§ 112(f)/sixth paragraph.
The rejection of claims 1-7 under 35 U.S.C. 101 is withdrawn based on applicant's amendment and response.
Based on applicant's amendment, the rejection of claim 18 under 35 U.S.C. 112(b) is withdrawn.
Response to Arguments
Applicant argues that [“Jo does not describe generating, based on applying a representation of at least a portion of the transcript to the language model, a representation of a caption from the transcript for a video segment of the plurality of video segments. Further, Jo does not describe inserting the caption from the transcript into frames of the video segment for display of the trimmed version of the input video” (Page 12)].
The argument described above has been considered, and are persuasive. Therefore, rejection has been withdrawn. However, upon further search and consideration, a new ground of rejection is made, citing the new reference DE JUAN et al. (US20240038271A1) [hereinafter JUAN] (see new claim 1 rejection below) .
Applicant argues that [“Accordingly, the combination of Lee and Jo does not teach or suggest "applying the caption to the video segment by inserting the caption from the transcript into a region of the frames of the video segment that is different than a detected region comprising a detected face in the video segment."” (Pages 13-14)].
Examiner respectfully disagrees. As Examiner argued in the previous Office Action, JO teaches “In one example of such displayed story information related to the synchronized video, face bounding boxes 840 can be overlaid on the video displayed on mobile device 820 to mark a face of a person who is important in the story in a particular scene between characters appearing in the video, as indicated in the annotation metadata for that video scene. Another example of such displayed story information related to the synchronized video includes summaries of video story information from the narrative metadata, such as character relationships 850 and scene story summary 860. Display of character relationships 850, particularly of characters of importance in the video's story, permits easy recognition of the story of the video by a human viewer and understanding of relationships between different characters by this viewer. Scene story summary 860 summarizes a particular scene using the narrative metadata that was created based on that particular scene. By directly providing access to additional story information related to the synchronized video on mobile device 820, a human viewer may be permitted to learn such additional information without having stop the video from playing and then search the Internet for the particular information. Instead, directly providing access to story information related to the synchronized video on mobile device 820 creates a seamless viewing experience for the user” (see fig. 8, elements 840-860, par. 0054)(emphasis added). Therefore, elements 840 show the faces of the characters, while elements 850 and 860 show captions where 850 shows the character relationship caption, and 860 shows a summary of story line; and 850 and 860 areas are distinct from 840 facial areas.
Thus, the combination of LEE, JUAN and JO adequately discloses applicant's claimed limitation. Examiner respectfully reminds Applicants that during examination, the claims must be interpreted as broadly as their terms reasonably allow. In re American Academy of Science Tech Center, 367 F.3d 1359, 1369, 70 U.S.P.Q.2d 1827, 1834 (Fed. Cir. 2004).
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, 4, 8, 11, 15 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over LEE et al. (US20250039336A1) in view of DE JUAN et al. (US20240038271A1) [hereinafter JUAN].
As to claim 1, LEE teaches one or more non-transitory computer storage media storing computer-useable instructions that, when executed by one or more computing devices, cause the one or more computing devices to perform operations (see fig. 4, par. 0006, wherein FIG. 4 shows an example system 400 that is configured to generate a video summary for a video recording of a virtual conference; as taught by LEE)
comprising: generating, based on applying a representation of an input video to a language model (see par. 0073, The chat and video conference provider 310 includes a model store 420. The model store 420 stores different artificial intelligence or machine learning (AI/ML) models that can be used during the process of generating a video summary for a video recording of a virtual conference. Various types of models or artificial intelligence algorithms may be used in example systems … Some AI/ML models are generative AI models, such as generative pre-trained transformer (GPT), Text-to-Text Transfer Transformer (T5), Bidirectional and Auto-Regressive Transformer (BART), Bidirectional Encoder Representations from Transformer (BERT), their variations, or other large language models (LLMs) or foundation models (FM). The AI/ML models in the model store 420 can be supervised or unsupervised learning models; as taught by LEE);
a trimmed version of the input video comprising a plurality of video segments of the input video (see par. 0020, wherein the communication platform determines portions in the transcript that match or are most relevant to the text or audio summary. Since the transcript includes time stamps, time ranges for the transcript portions can be identified. A first set of video portions corresponding to the identified time ranges are also identified. The first set of video portions identified via transcript can be mapped to the multiple portions of the audio summary. The communication platform thus identifies a first set of correspondences between the first set of video portions from the video recording and the text or audio summary; see also par. 0021, wherein in parallel or in series, the communication platform also identifies a second set of correspondences between a second set of video portions of the video recording and the text or audio summary. The communication platform analyzes the image data in the video recording and identifies the video images that match or are most relevant to the text or audio summary. Video portions that include these images are the second set of video portions mapped to the text or audio summary to form the second set of correspondences; see also par. 0022, wherein the communication platform identifies key moments or highlights from the first set of correspondences and the second set of correspondences; see also par. 0023, wherein this example provides a video summary of a video recording. The video summary includes an audio narrating the summary of the meeting along with key moments or highlights displaying in video; as taught by LEE);
and a transcript of the plurality of video segments (see par. 0019, wherein the communication platform includes a summarization model for generating a text summary for the video recording; as taught by LEE).
LEE does not expressly teach generating, based on applying a representation of at least a portion of the transcript to the language model, a representation of a caption for a video segment of the plurality of video segments; and applying the caption to the video segment by inserting the caption from the transcript into frames of the video segment for display of the trimmed version of the input video.
In similar field of endeavor, JUAN teaches generating, based on applying a representation of at least a portion of the transcript to the language model, a representation of a caption from the transcript for a video segment of the plurality of video segments (see figs. 4-6, par. 0091, wherein using one or more of the techniques provided herein, one or more tasks may be performed automatically. The one or more tasks may comprise: (i) generation of closed captions, of the first video 502, in the first language (e.g., original language of the first video 502) using the transcript 506, wherein the closed captions may be displayed during playback of the first video 502 to assist a viewer in understanding dialog of the first video 502; (ii) generation of subtitles, of the first video 502, in one or more languages different from the first language, wherein the subtitles may be displayed during playback of the first video 502 to assist a viewer in understanding dialog of the first video 502; as taught by JUAN);
and applying the caption to the video segment by inserting the caption from the transcript into frames of the video segment for display of the trimmed version of the input video (see fig. 5I, 0090, based upon a selection of the fifth selectable input 515 associated with the subtitle viewing option, the video interface may present the first video 502 (in conjunction with original audio of the first video 502, for example) in conjunction with subtitles in the target language. For example, the subtitles may be generated based upon the translated transcript 516 (in the target language); as taught by JUAN).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the LEE apparatus to include the teachings of JUAN for generating, based on applying a representation of at least a portion of the transcript to the language model, a representation of a caption for a video segment of the plurality of video segments; and applying the caption to the video segment by inserting the caption from the transcript into frames of the video segment for display of the trimmed version of the input video. Such a person would have been motivated to make this combination as it is beneficial for the user to be able to easily add relevant information about video contents to the video as metadata or subtitles as it can be difficult to generate that solely from a video in a video format. For example, even if characters or objects relevant to a story told in a video have been recognized, it remains difficult to designate a title for such characters or object or to infer a relationship between characters, objects, or events (see also JUAN, pars. 0001).
As to claim 4, LEE and JUAN teach the limitations of claim 1. LEE further teaches applying a prompt to the language model to identify a plurality of section headings for each subset of video segments of the plurality of video segments (see figs. 4-11, par. 0087, wherein the video summary generator 480 can implement a classification model to identify key moments in the video portions identified by the text aligner engine 460, the video portions identified by the video aligner engine 470, or the transcript, corresponding to different key moment types. For example, if a video recording is for a product demonstration, the product pictures and audience engagement (e.g., questions or emojis) can be identified as key moments; as taught by LEE),
wherein the representation of the caption for the video segment of the plurality of video segments is a section heading of the plurality of section headings (see par. 0033, wherein once characters and objects are recognized, at a frame captioning stage, relative positions of characters to other characters, characters to objects, and objects to other objects can be calculated and scenes described based on these relative positions. Further, at a scene captioning stage, actions are recognized, such as gestures and movements by a character and relative positions of the characters or objects to one another. Based on recognized pattern of actions, a character's activity can be classified (e.g., talking, arguing, running, driving, etc.). Based on such action classifications, a structure of the story (i.e., plot) of the video can be constructed, designated, and saved. Such various information is extracted from the video and saved as annotation metadata for video shots/scenes; as taught by LEE).
Claim 8 amounts to the method, which is executed by the computer system comprising one or more processors and memory configured to provide computer program instructions to the one or more processors of claim 1. Accordingly, claim 8 is rejected for substantially the same reasons as presented above for claim 1 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 11 amounts to the method, which is executed by the computer system comprising one or more processors and memory configured to provide computer program instructions to the one or more processors of claim 4. Accordingly, claim 11 is rejected for substantially the same reasons as presented above for claim 4 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 15 amounts to the computer system comprising one or more processors and memory configured to execute computer program instructions stored on the computer storage media of claim 1. Accordingly, claim 15 is rejected for substantially the same reasons as presented above for claim 1 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 18 amounts to the computer system comprising one or more processors and memory configured to execute computer program instructions stored on the computer storage media of claim 4. Accordingly, claim 18 is rejected for substantially the same reasons as presented above for claim 4 and based on the references’ disclosure of the necessary supporting hardware and software.
Claims 2, 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over LEE et al. (US20250039336A1) in view of DE JUAN et al. (US20240038271A1) [hereinafter JUAN] and further in view of ITO et al. (WO2015033448A1).
As to claim 2, LEE and JUAN teach the limitations of claim 1. LEE and JUAN do not expressly teach applying a prompt to the language model to identify a plurality of words for emphasis as the representation of the caption for the video segment of the plurality of video segments; applying the caption to the video segment as the plurality of words are spoken during at least a portion of the video segment.
In similar field of endeavor, ITO teaches applying a prompt to the language model to identify a plurality of words for emphasis as the representation of the caption for the video segment of the plurality of video segments; applying the caption to the video segment as the plurality of words are spoken during at least a portion of the video segment (see fig. 6, page 7, ll. 7-19, wherein The subtitle scene keyword creation unit 232 extracts at least the subtitle data from the program being played back or being received (mainly the program being viewed and selected by the user by the operation) and extracts the character string of the subtitle data as the subtitle scene keyword. The retrieved subtitle scene keyword is, for example, a "noun" unit, and is stored in the database file 244 in the memory 240. The scene list creation unit 233 executes an operation when a user selects one of the keywords by manipulation while a plurality of the subtitle scene keywords described above are displayed on the display unit 134. At this time, the scene list creation unit 233 accesses the database file 243 based on the selected keyword. A scene selection item of the subtitle scene corresponding to the selected keyword is created and outputted to the display unit 134 as a scene list via the display control unit 234. Selection items at this time can be created for each program, and a plurality of selection items can be created within one program; see also page 13, ll. 27-32 to page 14, ll. 1-22; see also page 8, ll. 1-4; as taught by ITO).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the LEE and JUAN apparatus to include the teachings of ITO for applying a prompt to the language model to identify a plurality of words for emphasis as the representation of the caption for the video segment of the plurality of video segments; applying the caption to the video segment as the plurality of words are spoken during at least a portion of the video segment. Such a person would have been motivated to make this combination as it is beneficial for the user to be able to search the video based on a customized keyword, especially when there are many segments to the video. This narrows the user’s search result and makes it more accurate to directly go to the point of interest (see also ITO, page 2, ll. 10-30).
Claim 9 amounts to the method, which is executed by the computer system comprising one or more processors and memory configured to provide computer program instructions to the one or more processors of claim 2. Accordingly, claim 9 is rejected for substantially the same reasons as presented above for claim 2 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 16 amounts to the computer system comprising one or more processors and memory configured to execute computer program instructions stored on the computer storage media of claim 2. Accordingly, claim 16 is rejected for substantially the same reasons as presented above for claim 2 and based on the references’ disclosure of the necessary supporting hardware and software.
Claims 3, 10 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over LEE et al. (US20250039336A1) in view of DE JUAN et al. (US20240038271A1) [hereinafter JUAN] and further in view of ITO et al. (WO2015033448A1) and further view of HUANG et al. (US20220353469A1).
As to claim 3, LEE, JUAN and ITO teach the limitations of claim 2. LEE, JUAN and ITO do not teach applying a highlighting effect to a subset of words of the plurality of words.
In similar field of endeavor, HUANG teaches applying a highlighting effect to a subset of words of the plurality of words (see fig. 8, par. 0111, wherein at 802, the technique 800 includes generating a highlighted transcript as a copy of the transcript with a subset of the strings highlighted. A selected string is highlighted. For example, the selected string may have been selected as important or relevant using techniques described in relation to FIG. 5, 6, 7, 11, or 13. For example, the highlighted transcript may be displayed as a copy of the transcript with the selected strings color coded with a different color (e.g., yellow or red) than the strings of the transcript that have not been selected. Other visual indications may be used to indicate which strings in the transcript have been selected; as taught by HUANG).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the LEE, JUAN and ITO apparatus to include the teachings of HUANG applying a highlighting effect to a subset of words of the plurality of words. Such a person would have been motivated to make this combination as it is beneficial for the user to have the keywords highlighted so it is easier to attract the attention of the user (see HUANG, par. 0044).
Claim 10 amounts to the method, which is executed by the computer system comprising one or more processors and memory configured to provide computer program instructions to the one or more processors of claim 3. Accordingly, claim 10 is rejected for substantially the same reasons as presented above for claim 3 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 17 amounts to the computer system comprising one or more processors and memory configured to execute computer program instructions stored on the computer storage media of claim 3. Accordingly, claim 17 is rejected for substantially the same reasons as presented above for claim 3 and based on the references’ disclosure of the necessary supporting hardware and software.
Claims 5-6, 12-13 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over LEE et al. (US20250039336A1) in view of DE JUAN et al. (US20240038271A1) [hereinafter JUAN] and further in view of JO (US20200125600A1).
As to claim 5, LEE and JUAN teach the limitations of claim 1. LEE and JUAN do not expressly teach applying a prompt to the language model to identify a list of items spoken during the video segment as the representation of the caption for a video segment of the plurality of video segments; and applying the caption to the video segment as the list of items are spoken during at least a portion of the video segment.
In similar field of endeavor, JO teaches applying a prompt to the language model to identify a list of items spoken during the video segment as the representation of the caption for a video segment of the plurality of video segments; and applying the caption to the video segment as the list of items are spoken during at least a portion of the video segment (see par. 0034, wherein at a dialogue analysis phase speech (e.g., spoken lines) is analyzed and parts of speech (POS), named entities, emotions, intent, acts of speech (e.g., utterances), tone, and/or honorifics are recognized and saved as metadata for speech. At a plot analysis phase, acts of speech are analyzed and conversation is broken into event-units. Further, relationships between events are analyzed. Such information is saved as narrative metadata; see also par. 0039, wherein to align an order of scenes between video and script, video processor 110 can generate subtitles or a transcript (including timestamps) from spoken speech/audio in a scene using, for example, voice or speech recognition technology; see also par. 0044; as taught by JO).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the LEE and JUAN apparatus to include the teachings of JO applying a prompt to the language model to identify a list of items spoken during the video segment as the representation of the caption for a video segment of the plurality of video segments; and applying the caption to the video segment as the list of items are spoken during at least a portion of the video segment. Such a person would have been motivated to make this combination as it is beneficial for the user to be able to easily add relevant information about video contents to the video as metadata, as it can be difficult to generate that solely from a video in a video format. For example, even if characters or objects relevant to a story told in a video have been recognized, it remains difficult to designate a title for such characters or object or to infer a relationship between characters, objects, or events (see also JO, pars. 0003-0005).
As to claim 6, LEE and JUAN teach the limitations of claim 1. LEE and JUAN do not expressly teach applying the caption to the video segment by inserting the caption from the transcript into a region of the frames of the video segment that is different than a detected region comprising a detected face in the video segment.
In similar field of endeavor, JO teaches applying the caption to the video segment by inserting the caption from the transcript into a region of the frames of the video segment that is different than a detected region comprising a detected face in the video segment (see fig. 8, par. 0054, wherein in one example of such displayed story information related to the synchronized video, face bounding boxes 840 can be overlaid on the video displayed on mobile device 820 to mark a face of a person who is important in the story in a particular scene between characters appearing in the video, as indicated in the annotation metadata for that video scene. Another example of such displayed story information related to the synchronized video includes summaries of video story information from the narrative metadata, such as character relationships 850 and scene story summary 860. Display of character relationships 850, particularly of characters of importance in the video's story, permits easy recognition of the story of the video by a human viewer and understanding of relationships between different characters by this viewer. Scene story summary 860 summarizes a particular scene using the narrative metadata that was created based on that particular scene. By directly providing access to additional story information related to the synchronized video on mobile device 820, a human viewer may be permitted to learn such additional information without having stop the video from playing and then search the Internet for the particular information. Instead, directly providing access to story information related to the synchronized video on mobile device 820 creates a seamless viewing experience for the user; as taught by JO).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the LEE and JUAN apparatus to include the teachings of JO applying the caption to the video segment by inserting the caption from the transcript into a region of the frames of the video segment that is different than a detected region comprising a detected face in the video segment. Such a person would have been motivated to make this combination as it is beneficial for the user to be able to easily add relevant information about video contents to the video as metadata, as it can be difficult to generate that solely from a video in a video format. For example, even if characters or objects relevant to a story told in a video have been recognized, it remains difficult to designate a title for such characters or object or to infer a relationship between characters, objects, or events (see also JO, pars. 0003-0005).
Claim 12 amounts to the method, which is executed by the computer system comprising one or more processors and memory configured to provide computer program instructions to the one or more processors of claim 5. Accordingly, claim 12 is rejected for substantially the same reasons as presented above for claim 5 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 13 amounts to the method, which is executed by the computer system comprising one or more processors and memory configured to provide computer program instructions to the one or more processors of claim 6. Accordingly, claim 13 is rejected for substantially the same reasons as presented above for claim 6 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 19 amounts to the computer system comprising one or more processors and memory configured to execute computer program instructions stored on the computer storage media of claim 5. Accordingly, claim 19 is rejected for substantially the same reasons as presented above for claim 5 and based on the references’ disclosure of the necessary supporting hardware and software.
Claim 20 amounts to the computer system comprising one or more processors and memory configured to execute computer program instructions stored on the computer storage media of claim 6. Accordingly, claim 20 is rejected for substantially the same reasons as presented above for claim 6 and based on the references’ disclosure of the necessary supporting hardware and software.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over LEE et al. (US20250039336A1) in view of DE JUAN et al. (US20240038271A1) [hereinafter JUAN] and further in view of FANCELLU (US20210326643A1).
As to claim 7, LEE and JUAN teach the limitations of claim 1. LEE and JUAN do not expressly teach identifying an image corresponding to the caption; and applying the caption to the video segment with the image corresponding to the caption.
In similar field of endeavor, FANCELLU teaches:
identifying an image corresponding to the caption (see figs. 5A-5D and 8, par. 0082, wherein as shown in FIG. 5D, the user device 210 may provide, for display via the UI 500, text information 518 in the text information area 504. In this case, the text information 518 may corresponds to caption information of the image information 516 a-516 d based on the selection of the captions icon 510; as taught by FANCELLU);
and applying the caption to the video segment with the image corresponding to the caption (see fig. 9, par. 0153, The user device 210 may provide, for display, a response that includes image information and text information that is responsive to the query. As an example, the response may be a subset of a video that corresponds to the query. As mentioned above elsewhere herein, a user of the user device 210 might not be interested in watching an entire video, and may desire to more quickly identify a pertinent section of the video. In this case, the user device 210 may provide a response that identifies the pertinent portion of the video; as taught by FANCELLU).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the LEE and JUAN apparatus to include the teachings of FANCELLU identifying an image corresponding to the caption; and applying the caption to the video segment with the image corresponding to the caption. Such a person would have been motivated to make this combination as it is beneficial for the user to have an image related to the caption to make it easier to recognize the video segment with a visual cue (see FANCELLU, par. 0002-0004).
Claim 14 amounts to the method, which is executed by the computer system comprising one or more processors and memory configured to provide computer program instructions to the one or more processors of claim 7. Accordingly, claim 14 is rejected for substantially the same reasons as presented above for claim 7 and based on the references’ disclosure of the necessary supporting hardware and software.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Publication Number
Filing Date
Title
US7339992B2
2002-12-06
System and method for extracting text captions from video and generating video summaries
US20030163816A1
2002-02-28
Use of transcript information to find key audio/video segments
US20160014482A1
2015-07-13
Systems and Methods for Generating Video Summary Sequences From One or More Video Segments
US9176987B1
2014-08-26
Automatic face annotation method and system
US10950254B2
2018-10-25
Producing comprehensible subtitles and captions for an effective group viewing experience
US10299008B1
2017-11-21
Smart closed caption positioning system for video content
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 KOOROSH NEHCHIRI whose telephone number is (408)918-7643. The examiner can normally be reached M-F, 11-7 PST.
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, William L. Bashore can be reached at 571-272-4088. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KOOROSH NEHCHIRI/Examiner, Art Unit 2174
/WILLIAM L BASHORE/ Supervisory Patent Examiner, Art Unit 2174
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