WhisperSum: Unified Audio-to-Text Summarization

In an era overwhelmed by information, efficiently extracting relevant data from audio sources is crucial. This study introduces WhisperSum, a solution combining OpenAI's Whisper for accurate voice transcription with spaCy's advanced natural language processing (NLP) for extractive text summarization. WhisperSum transcribes audio files into text, analyzes the content, and produces concise summaries to help users quickly understand key information. The web application, built using Flask, offers a user-friendly interface for easy audio uploads, real-time transcription, and summary retrieval. The system integrates Whisper's transcription capabilities with the NLP tools of spaCy, ensuring accuracy and efficiency. WhisperSum achieved high performance, with precision, recall, and F1-scores of 91.98%, 92.12%, and 92.04%, respectively, highlighting its effectiveness in accurately transcribing and summarizing audio content while minimizing errors and maintaining comprehensive coverage. The application is valuable for content management, education, and journalism, providing a streamlined solution to information overload. WhisperSum enhances decision-making by ensuring the accessible availability of crucial information, demonstrating the significant potential of integrating advanced NLP and transcription technologies.