audio-transcriber

You can transcribe audio recordings into structured Markdown meeting minutes by using local transcription engines to generate text, apply speaker diarization, add timestamps, and produce metadata for meetings, interviews, or podcasts.

Yes, faster-whisper can perform speaker diarization and generate timestamped transcripts, outputting structured Markdown documents with speaker labels and metadata for various audio formats and languages.

The best way to generate executive summaries and action items from audio files is through on-demand LLM-assisted processing, which transforms raw audio transcriptions into structured Markdown reports with attendees, decisions, and next steps.

You do not need an LLM to convert audio to text and create meeting notes, as local engines handle zero-configuration transcription. An LLM is optional and used specifically for on-demand, prompt-driven summary generation.

Yes, this audio transcription approach works with large audio files and multiple languages, processing recordings across formats and sizes while leveraging local engines for reliable transcription and structured Markdown output.