Abstract: Integrated video data presentations may allow active video browsing. Such presentations provide the user with information about the content of a particular sequence being tested while maintaining an important message. We suggest how to automatically make video summaries for longer videos. Our video access method involves two tasks: first, splitting the video into smaller, compatible parts and second, setting the levels into effects. Our proposed algorithm sections are based on analysis of word frequency in speech transcripts. After that the summary is made by selecting the parts with the highest scores depending on the length of time and these are illustrated. We created and conducted a user study to check the quality of the summaries made. Comparisons are made using our proposed algorithm and a random segment selection scheme based on mathematical analysis of user learning outcomes. Finally, we can see the summarized context of the video we want to know about. Summarization of the video is done by the Python API and NLP (Natural Language Processing). An API, or Application Programming Interface, is a server you can use to receive and send data using code. APIs are widely used to retrieve data, and that will be the focus of this first study. When we want to receive data from an API, we need to make a request. Applications are used across the web
Description:Field of the Invention
[0001] The YouTube transcript summarizer can be considered an innovation in the field of Natural Language Processing (NLP) and Machine Learning (ML)
Background
[0002] A large number of video recordings are made and shared online all day. It is very difficult to spend time watching such videos which may be longer than expected and sometimes our efforts may be in vain if we do not get the right information about it.
[0003] Summarize the text of those videos automatically allows us to quickly look at important patterns in the video and helps us save time and effort in all the content of the video
[0004] The YouTube Transcript Summarizer was created in response to the expanding landscape of digital material consumption and the changing needs for quick access to information. Users are confronted with an overwhelming amount of information due to the explosion of video content on websites like YouTube, which frequently makes it difficult for them to understand and remember important points. This technology solves this problem by automatically condensing lengthy video transcripts into clear, succinct summaries using state-of-the-art Sentiment Analysis and Natural Language Processing (NLP) technologies. This strategy contributes to enhanced accessibility for audiences with time constraints or different learning styles while also being in line with the growing trend for bite-sized material.
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[0005] Additionally, this invention's history acknowledges the urgent need for sustainable content consumption and the decrease of information overload. The negative effects of heavy data usage on the environment are becoming more and more obvious as online video platforms grow. This idea encourages more mindful content engagement by giving consumers the ability to quickly understand the essence of video content through concise summaries. This might potentially result in lower bandwidth use and, as a result, a smaller ecological footprint. This innovation offers a fresh approach to the problems associated with contemporary information consumption by fusing technology development, user-centered design, and environmental responsibility.
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Objects of the Invention
[0011] The objective of Invension are as follows :
• A YouTube transcript summarizer aims to provide a condensed and simplified version of the text transcript of a YouTube video.
• The objective is to help users save time and quickly understand the key points of the video without having to watch the entire content. , Claims:Presenting the tailored summaries to users through a user interface, enabling them to efficiently grasp the essence of the video content while accommodating their individualized requirements.
2. Processing video transcripts using the determined parameters to generate customized summaries that align with the user's preferences
3. Providing the generated summary for display to users seeking an abridged understanding of the video's content.
4. Generating a summary of the video by combining the selected segments
5. Analyzing the video stream to identify key events and segments.Selecting the most relevant segments based on predetermined criteria
| # | Name | Date |
|---|---|---|
| 1 | 202311056083-STATEMENT OF UNDERTAKING (FORM 3) [22-08-2023(online)].pdf | 2023-08-22 |
| 2 | 202311056083-REQUEST FOR EARLY PUBLICATION(FORM-9) [22-08-2023(online)].pdf | 2023-08-22 |
| 3 | 202311056083-FORM 1 [22-08-2023(online)].pdf | 2023-08-22 |
| 4 | 202311056083-DRAWINGS [22-08-2023(online)].pdf | 2023-08-22 |
| 5 | 202311056083-DECLARATION OF INVENTORSHIP (FORM 5) [22-08-2023(online)].pdf | 2023-08-22 |
| 6 | 202311056083-COMPLETE SPECIFICATION [22-08-2023(online)].pdf | 2023-08-22 |