Video Summarization for Marathi Language

Video Summarization for Marathi Language

Prof. Indira Joshi1, Shruti Aurade2, Nishant Sanap3, Nisha Kangane4

1Indira Joshi, Associate Professor, Computer Engineering, NHITM

2Shruti Aurade, Computer Engineering, NHITM 3Nishant Sanap, Computer Engineering, NHITM 4Nisha Kangane, Computer Engineering, NHITM

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Abstract - The Video Summarization Platform using Python Flask is a comprehensive tool designed to summarize Marathi and English videos while providing summaries in Hindi, Marathi, and English languages. Leveraging machine learning and natural language processing (NLP) techniques, this platform offers a sophisticated solution for efficiently extracting key information from videos. The platform begins by transcribing the audio content of the video into text using automatic speech recognition (ASR) technology. This transcription process ensures that the platform can accurately analyze and summarize the video's content. Next, the text is translated into the target languages, namely Hindi, Marathi, and English, enabling users from diverse linguistic backgrounds to access the summarized content. To generate concise and informative summaries, advanced NLP algorithm is applied. This algorithm analyze the transcribed text to identify the most significant phrases, sentences, and concepts. By considering factors such as keyword frequency, semantic relevance, and context, the platform effectively distils the video's content into digestible summaries. Additionally, machine learning models are employed to classify the type of video content. These models are trained on diverse datasets encompassing various video genres and topics. By recognizing patterns and features within the video content, the platform can accurately categorize videos into distinct types, such as news, interviews, tutorials, or entertainment. The platform's user interface, powered by Python Flask, offers a seamless experience for users to upload videos, select their preferred language for summarization, and receive concise summaries in their chosen languages. The intuitive design ensures accessibility and ease of use, catering to both novice and advanced users. Overall, the Video Summarization Platform serves as a valuable resource for individuals seeking efficient ways to consume multimedia content. Whether for educational, informational, or entertainment purposes, this platform empowers users to access summarized video content in multiple languages, facilitated by cutting-edge machine learning and NLP technologies.

Key Words: Transcription, Marathi-speaking users, Marathi YouTube videos, video content, transcription, summary, translation, Natural Language Toolkit (NLTK), content comprehension, user interaction data, past summaries, recommendation