Real-Time Audio Transcription with Automated PDF Summarization and Contextual Insights
Year: 2024
Type: article
Abstract: This research provides a comprehensive examination of automated PDF summarization and real- time audio transcription systems, focusing on their integration to derive contextual insights. The study explores recent advancements in automatic speech recognition (ASR) technologies that enable instantaneous conversion of spoken language into text, as well as techniques for both extractive and abstractive summarization of PDF 4 documents. The paper investigates how combining these technologies can enhance applications across various sectors, including media, business, healthcare, and education, by delivering real-time, contextually relevant information. It also addresses key industry challenges, such as handling complex documents, ensuring scalability, achieving high transcription accuracy, and managing noisy environments. The research concludes with a discussion on potential future developments, including improving multilingual capabilities, reducing biases in AI models, and enhancing system integration with other technologies to provide more efficient and personalized insights.
Authors: S R Rakshitha, Sahana P Naik, Sanjana VS, Suprasanna V, Nayana C P
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W6893155306
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