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Video content integrity identification method and device, equipment and storage medium

A technology of video content and completeness, applied in the field of deep learning, can solve problems such as low review efficiency, disallowing video release, and long time consumption, and achieve the effect of improving review efficiency

Pending Publication Date: 2021-02-26
TENCENT TECH (SHENZHEN) CO LTD
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For illustration, these short videos may contain some incomplete audio content. For example, the singing voice in the short video stops abruptly. The review result of the short video platform for such short videos is that the video content is incomplete and the video is not allowed to be released. on short video platforms
[0004] In the above situation, manual review requires reviewers to watch each short video uploaded to the short video platform, the review process takes a long time and the review efficiency is low

Method used

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  • Video content integrity identification method and device, equipment and storage medium
  • Video content integrity identification method and device, equipment and storage medium
  • Video content integrity identification method and device, equipment and storage medium

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Embodiment Construction

[0036] In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0037] First, the nouns involved in the embodiments of the present application are introduced.

[0038] Mel Frequency Cepstral Coefficients (MFCC): It refers to the linear transformation of the logarithmic energy spectrum based on the nonlinear Mel Scale of sound frequency in the field of sound processing. The Mel frequency is a concept based on the auditory characteristics of the human ear. The Mel frequency has a nonlinear correspondence with the sound frequency, and the Mel frequency cepstral coefficient uses this correspondence to calculate the spectral characteristics of the sound. The process of MFCC generally includes: pre-emphasis, framing, windowing, Fast Fourier Transform (Fast Fourier Transform, FFT), Mel filter bank a...

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Abstract

The invention discloses a video content integrity identification method, and device, equipment and a storage medium, and relates to the field of deep learning. A video integrity identification model is constructed through an artificial intelligence technology, and a function of identifying video integrity is realized by utilizing computer equipment. The method comprises the steps of obtaining a video file and video publishing information of the video file, wherein the video publishing information represents information provided when video content corresponding to the video file is published; separating audio data from the video file; extracting audio features from the audio data, and extracting text features from the video release information; splicing the audio features and the text features to obtain spliced features; and identifying the spliced features to obtain the integrity of the video content corresponding to the video file. By identifying the vector after the audio feature andthe text feature corresponding to the video file are spliced, the integrity of the video content is determined by integrating the features of multiple dimensions, so that the accuracy of video integrity auditing is improved.

Description

technical field [0001] The present application relates to the field of deep learning, in particular to a method, device, device and storage medium for identifying the integrity of video content. Background technique [0002] Short videos refer to videos ranging in length from a few seconds to several minutes, and are usually presented in front of users in the form of feeds in applications. [0003] The short video creator uploads the short video to the short video platform, and the short video platform reviews the uploaded short video, and the short video that passes the review is recommended to the user's corresponding client according to the relevant recommendation algorithm. In some cases, short video creators publish a large amount of similar or repeated video content in order to increase revenue. Many of these video content are automatically edited by video editing tools, so that the quality of the short video cannot be guaranteed. For illustration, these short videos ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G10L25/03
CPCG10L25/03G06V20/40G06V20/46
Inventor 刘刚
Owner TENCENT TECH (SHENZHEN) CO LTD
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