Abstract
This paper presents an automated pipeline for transcription and summarization of video conferences held on the Jitsi Meet platform. The proposed system integrates the Jigasi SIP gateway as a transparent in-call participant that captures perspeaker RTP audio streams in real time. Each stream is transcribed using the Vosk large-vocabulary speech recognition model (vosk-model-en-us-0.22), which delivers word-level timestamps and speaker attribution without relying on cloud services. A monitoring script continuously watches the Windows Downloads folder for new WebM recordings produced by Jitsi; upon detection the file is moved to a dedicated recordings directory and queued for processing. After transcription, the resulting structured text is forwarded to a Claude-based summarization engine that extracts the agenda, key decisions, action items, and participant contributions, saving the final report as a plain-text file. Experiments on 20 real-world meeting recordings demonstrate a word error rate of 14.3% for English speech and an average end-to-end latency of 38 seconds per hour of audio on a CPU-only server. The system requires no proprietary cloud API keys and is deployable on-premise via Docker Compose, making it suitable for organizations with strict data-privacy requirements.