Youtube Transcript Sumariser- application of API

for basic information of youtube transcript summariser..

1. YOUTUBE TRANSCRIPT SUMMARIZER

2. Introduction: The YouTube viewership reached around 2.3 billion in 2020 and continues to grow rapidly. Approximately 300 hours of YouTube videos are uploaded every nanosecond. A Google study revealed that nearly one-third of YouTube users in India access videos on their mobile devices, spending over 48 hours per month on the platform. Despite the vast content available, finding specific information in lengthy videos is frustrating and time-consuming. Existing ML video summarization methods require substantial processing power and time due to numerous frames. Addressing this, we suggest using the LSA Natural Language Processing algorithm for more efficient processing.

3. Abstract: The YouTube summarizer is a digital tool and natural language processing to condense extended YouTube videos into brief summaries, providing essential insights. Its objectives include time-saving, improved accessibility, and an enhanced viewing experience for content creators and viewers. Utilizing advanced algorithms and machine learning models, the tool analyzes topics, key points, and timestamps. Successful implementation mandates careful consideration of system requirements, encompassing hardware specifications and security protocols. This enhances accessibility for individuals with disabilities or limited time, thereby facilitating knowledge sharing and research .

4. TITLE AUTHOR OBJECTIVE METHOD-OLOGY FEATURES DATE OF PUBLISH Automated YouTube Video Transcription P Nagaraj ;   B Rohith ;   B Sai Vasanth ;  G Veda Varshith Reddy ;   A Koushik Teja Creates a Python video summarization system emphasizing audio for efficient content retrieval and browsing. Build a module that generates audio paraphrases from transcribed text, preserving key statements and concepts with NLP techniques for contextual accuracy. Speech Recognition Integration Audio Paraphrasing Summary Integration 24-05-2023 Video Transcript Summarizer Atluri Naga Sai Sri Vybhavi ; Laggisetti Valli Saroja ; Jahnavi Duvvuru ;  Jayanag Bayana Design a globally accessible system for summarizing and providing educational content, considering language diversity and cultural nuances Integrate modules for popular web platforms (YouTube, Facebook, Google, Instagram), using platform-specific APIs to fetch video transcripts and metadata for summarization . NLP-Driven Key Element Identification Educational Content Prioritization Global Accessibility Considerations 14-04-2022 Literature Survey:

5. TITLE AUTHOR OBJECTIVE METHOD-OLOGY FEATURES DATE OF PUBLISH Text Summarizer Transcript Generator Eesha Inamdar, Varada kalaskar, Vaidehi Zade Uses NLP techniques to identify key elements in YouTube video transcripts, extracting important phrases, keywords, and contextual information. . Use Spacy for preprocessing (cleaning, stop word removal), frequency normalization, and calculating sentence weightage to generate concise and informative summaries Spacy Integration Frequency Normalization Text Preprocessing Weighted Sentence Calculation 2022 YouTube Transcript Summarizer Gousiya Begum, N.Musurat Sultana, Dharma Ashritha This project aims to alleviate the challenges posed by the overwhelming volume of online video content, where creators may prioritize views over content accuracy. Develops using Spacy for effective text summarization, mitigating misleading content on YouTube Misleading Content Mitigation User Empowerment Deployment Versioning 03-03-2022

6. Software Requirements: Operating system : Windows 10. Coding Language : Python Web Framework : Flask

7. Hardware Requirements: System : Pentium i3 Processor. Hard Disk : 500 GB. Monitor : 15 ’’ LED Input Devices : Keyboard, Mouse Ram : 4 GB

8. Existing System: The Current Working/Processing of Extension is not at its best speed accuracy or satisfactory fast. Whenever a user performs summarization, the summarization is only available for the videos who already have subtitle eligibility. Subtitle eligible video. Audio summary is not at its accuracy level. Extra short summary in text of extra small videos.

9. Disadvantages of Existing system: Current extension lacks optimal speed, accuracy , and summarization for videos without built-in subtitles. Summarization requires subtitles, leading to errors in large videos exceeding the 1024-word limit. Larger videos can't produce audio summaries due to capacity constraints.

10. Proposed System :

11. Advantages of Proposed System: Speed Accuracy Larger videos eligible for summarization Summarization of no-subtitle eligible videos.

12. Functional Requirements: Automatic Speech Recognition : Recognizes spoken words in YouTube videos for accurate transcription. Natural Language Processing : Analyzes transcriptions to identify topics, key points, and timestamps for summarization. Summarization Algorithm: Implements an effective algorithm for condensing video transcripts into concise summaries. User Authentication: Ensures secure access to the system with unique credentials for users. Database Management: Stores and retrieves video transcripts, summaries, and user data efficiently. User Interface: Provides an intuitive interface for users to interact with and initiate summarization tasks. Compatibility: Ensures compatibility with various devices and browsers for a diverse user base.

13. Non-Functional Requirements: Performance: Processes summarization tasks swiftly to provide a seamless user experience. Scalability: Handles a growing user base and increasing data volume without compromising performance. Security: Implements robust security protocols to protect user data and ensure privacy. Reliability: Ensures consistent and accurate summarization results across different videos and users. Accessibility: Enhances accessibility for users with disabilities through features like screen reader compatibility . Usability: Provides an intuitive and user-friendly interface for users to navigate and understand the summarization process. Maintainability: Allows for easy maintenance and updates to address evolving requirements and technology changes.

14. SYSTEM ARCHITECTURE:

15. Data Flow Diagram:

16. Use Case Diagram:

17. Chrome Extension Manifest:

18. EXECUTION: CHROME EXTENSION :

19. TRANSCRIPT SUMMARISING :

20. Result:

21. Conclusion: The YouTube Transcript Summarizer Chrome Extension, powered by advanced natural language processing and SpaCy, delivers accurate and concise video summaries, meeting diverse user needs for efficient content consumption. With a modular design, specialized audio paraphrase integration, and real-time processing, it excels in adaptability and scalability. Ongoing user feedback and iterative enhancements will undoubtedly reinforce its role as an invaluable tool, enhancing the YouTube viewing experience.

22. 18-Mar-24 22