DETAILED ACTION
Claims 1-18 are pending.
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 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.
Claim(s) 1-3, 5-7, 11-13, 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kang (US 2015/0195608) in view Gandhi et al. (US 2019/0215542), and further in view of Wu et al. (US 10681104).
Claim 1, Kang teaches a computer-implemented method for synchronizing audio and video using pause gap analysis, the method comprising:
splitting a video into an audio stream and a video stream (p. 0062);
identifying time points at which there is no sound in the audio stream and deriving pause gaps in the audio stream (i.e. audio silence detector) (p. 0091, 0164);
Kang is not entirely clear in teaching a computer-implemented method for synchronizing audio and video using pause gap analysis, the method comprising:
applying a binary classifier to predict sound presence or absence in frames of the video stream and deriving pause gaps in the video stream;
identifying desynchronization between the pause gaps in the video stream and the pause gaps in the audio stream; and
aligning the pause gaps in the video stream with the pause gaps in the audio stream, based on metadata of the pause gaps in the video stream.
Gandhi teaches the specific features of:
applying a binary classifier to predict sound presence or absence in frames of the video stream and deriving pause gaps in the video stream (i.e. analyzing jumps in time stamps of the video stream) (p. 0024-0025, 0035);
identifying desynchronization between the pause gaps in the video stream and the pause gaps in the audio stream (i.e. time stamp jumps greater than 1 sec) (p. 0035); and
aligning the pause gaps in the video stream with the pause gaps in the audio stream (i.e. collapsing audio and/or video to maintain synchronization) (p. 0035-0037).
Therefore, it would be obvious to one of ordinary skill in the art before the effective invention was filed to have provided synchronization of streams as taught by Gandhi to the system of Kang to sync audio and video streams that lose synchronization (p. 0024).
Wu teaches the specific feature of:
“aligning the pause based on metadata of the pause gaps in the video stream” (i.e. manifest data for presentation times) (col. 1-2, lines 36-28).
Therefore, it would be obvious to one of ordinary skill in the art before the effective invention was filed to have provided manifest for presentation times as taught by Wu to the system of Kang to effectively shift segments into synchronization (p. 0024).
Claim 5, Kang teaches the computer-implemented method of claim 1, further comprising:
feeding the video stream into the binary classifier (i.e. scene change detection) to obtain binary values which indicate whether the sound presence or absence in the frames of the video stream (i.e. using black frames) (p. 0192).
Claim 6, Kang is silent regarding the computer-implemented method of claim 1, wherein, by aligning the pause gaps in the video stream with the pause gaps in the audio stream, the video stream and the audio stream are synchronized.
Gandhi teaches the computer-implemented method of claim 1, wherein, by aligning the pause gaps in the video stream with the pause gaps in the audio stream, the video stream and the audio stream are synchronized (i.e. collapsing audio and/or video to maintain synchronization) (p. 0035-0037).
Therefore, it would be obvious to one of ordinary skill in the art before the effective invention was filed to have provided synchronization of streams as taught by Gandhi to the system of Kang to sync audio and video streams that lose synchronization (p. 0024).
Claim 7 recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 1.
Kang inherently discloses recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 1.
Kang inherently discloses recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 3.
Claim 11 recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 5.
Kang inherently discloses recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 5.
Claim 12 recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 6.
Kang inherently discloses recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 6.
Claim 13 is analyzed and interpreted as an apparatus of claim 1.
Claim 17 is analyzed and interpreted as an apparatus of claim 5.
Claim 18 is analyzed and interpreted as an apparatus of claim 6.
Claim(s) 2-3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kang (US 2015/0195608) in view Gandhi et al. (US 2019/0215542), and further in view of Wu et al. (US 10681104), and further in view of Ishtiaq et al. (US 2015/0082349).
Claim 2, The computer-implemented method of claim 1, further comprising:
splitting a training video (i.e. audio or video) into a training audio stream and a training video stream (p. 0062);
identifying time points at which there is no sound in the training audio stream and deriving pause gaps in the training audio stream (i.e. audio silence detector) (p. 0091, 0164).
Kang is not entirely clear in teaching The computer-implemented method of claim 1, further comprising:
converting the training audio stream into a binary stream with sound flags identifying the time points; and
using the sound flags and frames in the training video stream to train the binary classifier.
Ishtiaq teaches The computer-implemented method of claim 1, further comprising:
converting the training audio stream into a binary stream with sound flags identifying the time points (i.e. periods of silence) (p. 0117); and
using the sound flags (i.e. periods of silence) and frames in the training video stream to train the binary classifier (i.e. training modules to detect audio features) (p. 0117)
Therefore, it would be obvious to one of ordinary skill in the art before the effective invention was filed to have provided detection of audio features as taught by Ishtiaq to the system of Kang to determine periods of silence in the audio stream (p. 0117).
Claim 3, Kang is silent regarding the computer-implemented method of claim 2, wherein the training video is a normal video which has no desynchronization of the training audio stream and the training video stream.
Ishtiaq teaches the computer-implemented method of claim 2, wherein the training video is a normal video which has no desynchronization of the training audio stream and the training video stream (i.e. trained models come from normal audio and vide content) (p. 0115-0117, 0129).
Therefore, it would be obvious to one of ordinary skill in the art before the effective invention was filed to have provided detection of audio features as taught by Ishtiaq to the system of Kang to determine periods of silence in the audio stream (p. 0117).
Claim 8 recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 2.
Kang inherently discloses recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 2.
Claim 9 recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 3.
Claim 14 is analyzed and interpreted as an apparatus of claim 2.
Claim 15 is analyzed and interpreted as an apparatus of claim 3.
Claim(s) 4, 10, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kang (US 2015/0195608) in view Gandhi et al. (US 2019/0215542), and further in view of Wu et al. (US 10681104), and Kumar et al. (US 2024/0098346).
Claim 4, Kang is silent regarding the computer-implemented method of claim 2, wherein training the binary classifier is through supervised machine learning.
Kumar teaches the computer-implemented method of claim 2, wherein training the binary classifier is through supervised machine learning (p. 0036).
Therefore, it would be obvious to one of ordinary skill in the art before the effective invention was filed to have provided machine learning for scene detection as taught by Kumar to the system of Kang to allow boundary locations to be identified (p. 0036).
Claim 10 recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 4.
Kang inherently discloses recites “A computer program product for synchronizing audio and video using pause gap analysis, the computer program product comprising a computer readable storage medium having program instructions stored therewith” for performing the steps of claim 4.
Claim 16 is analyzed and interpreted as an apparatus of claim 4.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-18 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Claims 1-18 are rejected.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUSHFIKH I ALAM whose telephone number is (571)270-1710. The examiner can normally be reached 1:00PM-9:00PM.
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MUSHFIKH I. ALAM
Primary Examiner
Art Unit 2426
/MUSHFIKH I ALAM/Primary Examiner, Art Unit 2426 6/4/2026
Prosecution Insights