Automated Office Meeting Summarization with NLP- Based Video Transciption and Speaker Diarization
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Date
2024
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Abstract
Automatic Speech Recognition (ASR) technology has revolutionized the way
to capture and transcribe spoken words, enabling effective documentation
and analysis of verbal communication. Despite significant advances, existing
ASR systems for office meetings face persistent problems such as limited
speaker diarization, insufficient punctuation recovery, and variable accuracy
across languages. These limitations often result in transcripts that are difficult
to follow and less useful for detailed meeting records. This project aims to
develop an improved ASR system tailored specifically for office meeting
environments. By utilizing advanced deep learning models and integrating
features such as speaker diarization and punctuation recovery