audio-transcriber

To transcribe a YouTube video to Markdown with speaker identification, provide the video link to the audio transcriber. It downloads audio via yt-dlp, uses MLX Whisper for transcription, and applies SpeechBrain diarization to label speakers automatically.

Yes, you can transcribe audio locally on Apple Silicon without an internet connection. The transcription process uses MLX Whisper, enabling fast, offline processing while generating professional Markdown documents with identified speakers.

Yes, this transcription method extracts visual context from video files. When processing videos, it detects and extracts specific frames from moments where speakers reference visual elements, embedding these frames into the final Markdown output.

For speaker diarization during audio transcription, you need SpeechBrain and scikit-learn. These dependencies analyze audio features to identify and label different speakers, structuring the conversation clearly within the resulting Markdown file.

You convert meeting recordings into searchable text documents by processing audio or video files with local transcription. MLX Whisper generates accurate text, while speaker diarization and visual frame extraction provide context in a structured Markdown format.

A limitation when using MLX Whisper for video transcription is that it requires Apple Silicon hardware for local processing. Additionally, while visual frames are extracted, the tool focuses on transcription and diarization rather than full video analysis.